My Digital FootPrint

The CDO is dead, long live the CDO

noreply@blogger.com (Tony Fish) — Fri, 05 Jan 2024 09:24:00 +0000

Hierarchy appears to be the only option to pull a large group of individuals together toward a common goal. Many insects did it well before humans, but over the last 10,0000 years, humans have moved from decentralised clans into centralised nation-states consisting of hundreds of millions of people. From the pharaohs to Max Weber’s 20th bureaucratic management structure, we can now exist only in such a system because as a society or organisation grows beyond a few dozen people, the hierarchical pyramid is seen as the only option for the organisation. The justification is that it is nature and natural.

The “ideal organisation” was defined by Max Weber as a clear and strong hierarchy underpinned by the division of tasks based on specialisation. A fundamental assumption was that each unit takes care of one piece of the chain and the division of tasks within the unit is clearly defined, work can be executed much more efficiently. Weber envisioned this as a “superior structure” because it focused on rationality and equal treatment of all - assuming everyone was happy with their 1984 dystopian jobs and oversight. By formalising processes within organisations, but especially in government, favouritism and abuse of power could be prevented - as he assumed that those in charge and specialised workers remained. A really poor underlying assumption was that people act rationally, efficiently, and professionally. He also ignored the concept of shareholder primacy that would emerge. However, so strong is the argument that it remains the leading business philosophy today, and we still teach that hierarchy, administration and bureaucracy driven by efficiency and effective thinking underpinned by a better division of tasks and responsibilities to drive organisational performance measurable objective is still best practice. The justification is that it represents nature and is natural.

Different models emerged from the internet, web, and digital thinking allowing us to ponder if something better is possible. Small iterations, such as matrix management, never really changed the fundamentals and whilst embracing all stakeholders and ESG has added complexity to the decisions and models - hierarchy remains. However, it is possible to sense in the noise signals that “Data” is finally about to disrupt and dislodge a love/ hate affair with hierarchy, power, and control.

Counter to this and according to both scientists, individuals, including leaders, do not make their decisions after a thorough analysis, but first decide, unconsciously and intuitively, and then rationalise their decision. We have become experts in seeking out framed and biased data to justify and provide a rational argument for a decision we have already made.

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Endless inches have been written about structure, who and how to lead and what a digital organisation looks like. However, right now, we are likely to be in the death phase for a pure CDO (chief data/ digital officer) role as it becomes clear that the CTO, CIO and CDO roles have very similar mandates and are now actually competing for power, resources and a clear value to the organisation. The ridged ideals of separation and specialism models driving structures, management, incentives, KPI’s and hierarchy cannot work with the emergence of highly complex interdependency in a digital age - are we witnessing that the division of labour falls apart at scale because of complexity and speed?

For a complicated task, the separation of that task into modules, and components to create the scale of efficiency and effectiveness works, and it works really well. For any task where the output directly and immediately, because of close feedback loops, changes the inputs for the next unit of creation and consumption - the hierarchy fails. The ridged division of labour into separate tasks, modules, parts or components does not work - because it fundamentally needs repeatability.

When operating at speed and scale - but there is a high level of repeatability, hierarchy delivers, and we know its problems. However, data is enabling us to operate at speed, scale and uniqueness (non-repeatability) - this is different.

However, data is enabling us to operate at speed, scale and uniqueness (non-repeatability) - this is different.

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We have recognised for a while that leadership/ chief roles are actually a representation of the ontology of an organisation (structure), the question has never been if you need a CEO, CFO, CMO, CTO as these were clearly delineated roles and specialisms. We understand the roles, mandates, powers and delegated authority the experts and leaders bring and have.

In a digital business, we have created four roles CTO, CIO, CDO and CISO. But the reality is that the CMO and CDO need the CFO’s data. The CFO wants the COO and CMO’s data. The CIO has lots of data but no direct path to showing value. The CISO needs other data from outside the organisation and the CTO needs data the CMO has not yet imagined. Organisations opted to create new roles such as Chief Data or Digital Officer to address the emerging complexity and to avoid too much power being vested in the CTO.

Breaking the axis of old - the CEO/ CFO

The CEO/CFO axis has this framing; we’ll do more things that are cheaper in the short term and less of those that are more expensive in the long term as our incentive and remuneration guide us. In a company with unified incentives, there is a uniciation of framing which means it is difficult for new ideas to emerge. This incentive friction or incentive dependency means we always face the same decisions in the same way.

Many leaders are realising that data is forging changes, and this change is not about tech, data or analysis, but it is about whether we, the leadership, exec or board, are making the right decisions. Decisions of the past were framed by the ideal hierarchy underpinned by efficiency and effectiveness at scale driven by the demands for specialisation. However, to know we are making the right decision going forward, we need to understand we have the right choices today, which means we need all “data” and our data can no longer be about isolation, separation or specialisation.

I expect that we are about to see a new axis of power arrive with the emergence of a new chief role as we realise, we need a new power dynamic structure. A two-way axis (CEO/CFO) becomes a three-way stool. The emergence of the CEO/ CFO/ CxO. The CEO/ CFO will maintain the remits of controlling and understanding the speed and scale at which the hierarchy operates, with the new role focussing on uniqueness - how data breaks the old hierarchy. It does not matter what you call the X, the point is what is their mandate. They have to own:

the data philosophy
all data emerging from the company and its ecosystem
data governance and security
direct the current and future platform's abilities, functionality and performance

The point here is that this role is not about the analysis of the data but about ensuring the quality, attestation, providence, provenance, function, form, taxonomy, ontology and pedagogy of the data needed for decision and that we will continue to access to and enjoy the data we need to make better decisions.

The critical point is that once the CEO/CFO could know if they were making the right decisions as the framing they needed was about efficiency and effectiveness within a specialism model, however going forward, this axis is not only insufficient, it is damaging. This new third member is needed to provide modern-day stabilisation and governance to ensure that as an expanded team, “we know we are making the right decisions”, as we must regularly ask efficacy questions that were not needed under the old repeatability model, as the mission was sufficient as the guide.

The first victim will be the CDO, as it exists in a specialisation-driven hierarchy that has no choice but to change - not its structure and how it thinks.

What has the executive team already forgotten about hard-fought lessons about leadership learned in COVID times?

noreply@blogger.com (Tony Fish) — Tue, 24 Oct 2023 07:38:00 +0000

Crisis situation are characterised by being urgent, complicated, nuanced, ambiguous and messy. The easy part is acknowledging that crisis presents exceptional and unprecedented challenges for organisations and leadership teams. In such periods, the stakes appear higher, and the decisions made can have far-reaching consequences.
The question of whether a leadership team should think, act and behave differently during times of war, conflict, and crisis is undoubtedly open for debate. But what did the last global pandemic (crisis) teach us, and what lessons learned have we forgotten in the light of new wars?

Pre-pandemic leadership framing about how to deal with a crisis.

The vast majority of how to deal with a crisis pre-pandemic was based on coaching, training and mentoring but lacked real experience of the realities because global crises do not happen at scale very often. Whilst essential to prepare, thankfully most directors never get to work in a crisis and learn. Pre-COVID, the structured and passed down wisdom focussed on developing the following skills.

Be Adaptable: In times of crisis, including war and conflict, the operating environment becomes highly volatile and uncertain. A leadership team must become more adaptable and flexible to respond to rapidly changing circumstances. Directors are trained to be more willing to recognise and pivot their strategies and make quick decisions, unlike stable times, where longer-term planning is often feasible.

Unity and Cohesion: A leadership team should act cohesively during a crisis and drop the niggles and power plays. Clear communication and collaboration among executives and directors are essential to ensure everyone is aligned and working towards a common goal. Unity is critical in times of uncertainty to maintain the organisation's stability and morale.

Decisiveness: Crisis demands decisiveness, with fewer facts and more noise, from its leaders. In the face of adversity, a leadership team should be ready to make tough choices promptly which will be very different to normal day-to-day thinking. Hesitation can be costly, and the consequences of indecision are amplified and become more severe during a crisis.

Resource Allocation: A crisis will strain resources, making efficient and effective allocation idealistic and not practical. A leadership team should reevaluate its resource allocation, prioritising the needs based on the best opinion today, which will mean compromise and sacrifice. It is about doing your best, as it will never be the most efficient, effective or right.

Risk Management: In times of crisis, certain risks are heightened. A leadership team must adjust its risk management strategy, potentially being more conservative and prudent to safeguard the people and the organisation's long-term viability.

This is a lovely twee list, they are obvious, highly relevant and important, but the reality is totally different. Leaders and directors quickly move past these ideals to the reality of crisis management.

The day-to-day stress and grind of crisis surface the unsaid, hostile and uncomfortable - all aspects we learned in COVID and include.

Consistency: Maintaining a level of consistency across the leadership’s behaviour, regardless of the personal view and external circumstances. Drastic changes in leadership style create additional confusion and anxiety, creating an additional dimension to the existing crisis.

Ethical Compass: The moral and ethical compass of a leadership team should not waver in times of crisis. Principles such as honesty, integrity, acceptance, and respect (for all views and opinions that are legal) should be upheld, as compromising on ethics can lead to long-term damage to the individual and organisation's reputation. Different opinions matter, as does the importance of ensuring they are aired and discussed openly, however hard and uncomfortable. We might not agree because of our own framing, but that does not mean we actually know what is true or false.

Strategic Focus: While adaptability is important, a leadership team should not lose sight of its agreed long-term strategic vision. Abrupt changes can disrupt the organisation's core mission and values. Strategies may need to be tweaked, but the overarching values and vision should remain consistent, even in the face of uncertainty. If it does not - then there is a massively different issue you are facing.

Transparency: Honesty and transparency are essential, particularly during times of crisis. A leadership team should communicate openly with themselves, employees and stakeholders, providing them with a clear understanding of the challenges and the strategies being employed to overcome them. Those prioritising themselves over the cause and survival need to be cut free.

Legal and Regulatory Compliance: A leadership team should not compromise on legal and regulatory compliance, however much there is a push to the boundaries. Violating laws or regulations can lead to severe consequences that may outweigh any short-term benefits. Many will not like operating in grey areas, which might mean releasing of the leadership team.

Crisis on Crisis: because we don't know what is going on in someone else's head, heart or home, individuals can quickly run into burnout. We don’t know who has a sick child, a family member has cancer, lost a loved one or is just in a moment of doubt. Each leadership team should assume that everyone in their team needs help and support constantly.

What have we already forgotten?

Post-pandemic leadership quickly forgot about burnout, ethics, transparency and single-mindedness to revert to power plays, incentives and individualism. It was easy to return to where we are most comfortable, and most experiences exist - stability and no global crisis. Interest rates and debt access are hard but are not a crisis unless your model is shot. The congratulatory thinking focussed on we survived the global crisis, it was a blip that is unlikely to be repeated.

The unique challenges and pressures of war demand adaptability, unity, decisiveness, and resource allocation adjustments - essential skills. However, we have learned that this focus should not come at the expense of consistency, ethical integrity, strategic focus, transparency, and legal compliance. A leadership team's ability to strike this balance can determine the organisation's survival and success during the most trying times. Ultimately, leadership must adapt while maintaining its core values and principles to navigate the turbulent waters of wartime effectively.

Whether a leadership team should act differently in times of war is a matter of balance, but the lessons and skills we have need to be front and centre. Today, focus on the team and spend more time than ever checking in on your team, staff, suppliers and those in the wider ecosystem. Crisis and conflict destroys life and lives at many levels.

We are on the cusp of AI developing traits or adapting in the same way living organisms do through evolution.

noreply@blogger.com (Tony Fish) — Mon, 18 Sep 2023 13:53:00 +0000

Mothwing patterns, often including structures resembling “owl eyes,” are a prime example of nature’s adaptation to survival.

Mothwing eyes are intricate patterns that have evolved over millions of years through a process of natural selection. Initially, moths developed cryptic colouration to blend into their environments, evading predators. Over time, some species developed wing scales with microstructures that reduced light reflection, helping them remain inconspicuous. These structures eventually evolved into complex arrays resembling the texture of eyes to deter predators, a phenomenon called “eyespot mimicry.” This natural error-creation adaptation likely startled or confused predators, offering those moths an advantage — precious moments to escape. The gradual development of these eye-like patterns underscores the intricate interplay between environmental pressures and biological responses, resulting in the remarkable diversity of moth wing patterns seen today.

Critically, moths are not and were not conscious in or of the development of eyespot mimicry or any other evolutionary adaptations. They did not think, “Let us moths create a pattern on the wing to confuse the owl.” Evolution is a gradual, unconscious process that occurs over generations through the mechanism of natural selection. Individual organisms do not consciously choose or design their adaptations; rather, random genetic mutations lead to variations in traits within a population. Suppose a particular trait, such as the “eyes” pattern on wings, provides some advantage in terms of survival or reproduction. In that case, individuals possessing that trait are more likely to pass on their genes to the next generation. Over time, these advantageous traits become more prevalent in the population. This process occurs without the organisms having any conscious intent or awareness of the changes in their traits. It results from environmental pressures and the differential survival and reproduction of individuals with different traits.

AI can develop new traits with advantages, but that does not make it conscious.

AI (as of 2023) does not possess consciousness or intent like humans. However, consciousness and the development of new survival traits are unrelated. Indeed, neither is the characteristic of “independent decision-making” linked to survival. Adaption, evolution and the crafting of new advantage does not have any links to higher-order thinking or awareness.

AI operates based on algorithms, data, and programming, and any development of new traits or capabilities at the start (where we are today) will be a direct result of deliberate human design and engineering rather than unconscious adaptation.

Whilst simple algorithms can simulate processes that resemble aspects of evolution, such as genetic algorithms and neural architecture search, to optimise certain parameters or designs. Whereas AlphaGo (Google Deepmind) demonstrated the ability to learn and improve its gameplay through a combination of deep neural networks and reinforcement learning techniques based on data. AlphaZero went further insomuch that it doesn’t even need a data set to start as it is generated through selfplay.

What is happening here?

AlphaGo & AlphaZero demonstrated that processes guided by predefined objectives and criteria set by human programmers or researchers have enabled new traits (moves) to be crafted. These “AI” implementations do not have self-awareness or independent decision-making ability, but that does not prevent the autonomous development of new traits or adaptations in the same way living organisms do through evolution. AlphaGo’s capabilities are still within the bounds of its programmed algorithms and training data. It doesn’t possess a consciousness and is a product of human engineering, designed to excel at a specific task, but as with AlphaZero and AlphaFold, such systems can create new traits and advantages.

Whilst AI systems such as AlphaGo/ AlphaFold showcase the power of AI to adapt and improve within predefined parameters, it highlights that we are on the cusp of AI developing traits or adapting in the same way living organisms do through evolution.

We are on the cusp of AI developing traits or adapting in the same way living organisms do through evolution.

We should not be surprised as these AI systems are trying to mimic how humans and living organisms learn and evolve; therefore, a natural consequence is evolution, the development of traits based on “errors” that provide an advantage.

There is a very fine line between AI systems operating under the guidance of human-defined objectives and constraints and such systems creating errors and adaptations, essentially improvements based on patterns learned from data, just like nature. The observation becomes interesting as data can now be created independently of human activity using selfplay.

The development of new traits or improvements in AI based on “errors” in data will soon mimic the unconscious forces of natural selection, which we will only see once it has been created. Critically, we have to question “how will we know” because it is new and different. This question is one that regulation is not set up to address or can solve, and it is why regulating the AI industry makes no sense.

The development of new traits or improvements in AI based on “errors” in data will soon mimic the unconscious forces of natural selection, which we will only see once it has been created.

Questions for the directors and senior leadership team.

We are fully into automation and the implementation of AI across many of our systems, and indeed, we are using the data to make improvements that we did not see. Have you questioned if this new trait has an advantage, and how have you determined it has an advantage and for whom? Is the advantage for you, your ecosystem, your customer or your AI?

Thank you Scott for seeding this.

The unintended consequence of data is to introduce delay and increase tomorrow's risk.

noreply@blogger.com (Tony Fish) — Mon, 18 Sep 2023 13:51:00 +0000

The (un)intended consequence of focusing on data, looking for significance, determining correlation, testing a hypothesis, removing bias and finding the consensus is that you ignore the outliers.

Hidden in the outliers of data are progress, innovation, invention and creativity, and the delay is that by ignoring this data and the signals from it, we slow down everything because we will always be late to observe and agree on what is already happening with those who are not driven by using data to reduce and manage today's risk. Our thrust to use data to make better decisions and apply majority or consensus thinking creates delays in change and, therefore, increases future risk.

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In our increasingly data-driven world, the unintended consequence of data often manifests as delay. While data is hailed as the lifeblood of decision-making, its sheer volume and complexity can paradoxically slow down processes, hinder innovation, and impede productivity. This phenomenon underscores the critical importance of managing data effectively to avoid unintended delays.

One primary way data leads to delay is through information overload. As organisations accumulate vast amounts of data, sorting through it can be overwhelming. Decision-makers may spend excessive time sifting through data, distinguishing relevant insights from the noise. This can result in analysis paralysis, where decisions are postponed indefinitely and opportunities are missed.

Data can also introduce delays when it is siloed within organisations. Departments may collect and store data independently, leading to fragmentation and redundancy. When data is not easily accessible across the organisation, collaboration suffers, and decision-making processes become fragmented. This can slow down projects and hinder the ability to respond swiftly to changing market conditions.

Moreover, the increasing focus on data privacy and security regulations has introduced a layer of complexity and delay. Organisations must navigate a labyrinth of compliance requirements, which can slow down data sharing and processing. The need for stringent data protection measures can sometimes clash with the need for agility and speed in decision-making.

The unintended delay caused by data can be mitigated through effective data management strategies. Investing in data analytics tools and platforms that can streamline data processing and analysis is crucial. Fostering a data-centric culture that encourages data sharing and collaboration can help break down organisational silos.

In conclusion, data is a powerful asset but can also be a source of unintended delay if not managed properly. Organisations must recognise the potential pitfalls of data overload, fragmentation, and compliance challenges and take proactive steps to mitigate these issues. With the right strategies and tools in place, data can be a catalyst for informed decision-making and innovation rather than a source of delay.

Why finding purpose feels impossible and why we should be talking more about balance

noreply@blogger.com (Tony Fish) — Wed, 22 Mar 2023 15:43:00 +0000

Overview

Balance is a necessity in every aspect of life. Knowing if we are in or out of balance directly affects our ability to survive and thrive; therefore, this thought piece brings something new to understanding balance and by association purpose.

Adaptation and homeostasis are the natural world's way of creating an unstable equilibrium. This dynamic system is unpacked and repurposed to present a solid argument for leadership teams and boards of directors to shift questions to ones that understand how to balance two powerful opposing forces. Balancing the development of the new whilst maintaining and preserving the existing has always been challenging, but here is a model that makes it easier.

In nature, we observe that organisms with little or no adaptation to ever-changing environments struggle to survive, whereas those that are pushing the evolutionary envelope and mutating into more suitable candidates for their ecosystem thrive. We also know that homeostasis and memory are key factors in maintaining stability. We find the same duality phenomena is reflected in the business world as we try to find a balance between creating new and maintaining what we have.

Nature does not favour new over old but ebbs and flows, appearing to have a fluid, ever-changing dynamic stability; however, businesses try to prioritise based on a purpose, and this piece highlights that often there is an unwillingness to consider both perspectives in balance, which is detrimental. What are the right questions to ask to determine if your purpose or strategy will disrupt fragile balances or if you are aligned and can thrive?

This is a 20-minute read which will challenge your perceptions and presuppositions of the role you inhabit and the role your ecosystem plays on you.

Can you, I, us, society or business have a single purpose?

In our natural world, two dependent systems keep our fragile life from ending. One is the ability to mutate and adapt, and the other is maintenance (homeostasis) and memory. When we observe the dynamic expansions and contractions in our natural world, we see the two-sides of this dynamic system competing. We can label these forces as “error creation” and “error correction”, and there is a never-ending ebb and flow between the two states, which creates a dynamic stability or an unbalanced equilibrium; two oxymorons which we will explore below. The ability to see both sides of a perspective gives us a wider vantage point that can help us unlock powerful insights into why a single unified purpose is not feasible, why AI will not take over, and how to avoid failure in times of uncertainty.

Is believing in a unified purpose a protective delusion?

The theory of evolution is a scientific explanation for how life on Earth has changed over time and how different species have arisen from common ancestors. It is based on the idea that all living things share a common ancestry and that the diversity of life we see today results from gradual changes over millions of years through a process called natural selection. Natural selection is the process by which certain traits become more or less common in a population based on their effects on survival and reproduction. Random mutation being the way to create new traits and adaptation, are central to the theory of evolution.

Homeostasis is maintenance, it refers to the ability of an organism to maintain a stable internal environment despite changes in the external environment. It is essential for the survival and well-being of an organism, and disruptions to this balance can have serious consequences. Memory refers to the process of storing, retaining, and retrieving information both individually and at a societal level; consider here how history, culture, law and even paintings and architecture are memory. Memory gives an organism the ability to maintain a sense of stability despite being in a changing environment, as one is able to recall the expected outcome of a familiar circumstance. Homeostasis and memory are critical for stability and survival.

These concepts, mutation & adaptation and homeostasis & memory, have been observed for thousands of years, and as humans unpack the complex connectivity between them, we can better articulate what we observe, which is why it can be so difficult to find and follow a singular goal to its completion. The connection between them has elements of both immediacy and delay: mutation demands an immediate response from homeostasis, yet also drives changes over time through immunity responses"; In the long run, human changes create environments for different mutations.

To the observer who notices that there are no arrows, there is a reason for that. It is about the connection, relationship, and coupling, not the directionality of flow.

Life is often framed as a competitive arms race: the survival of the fittest between living organisms that adapt to a constantly variable, but ultimately stable system. Mutations are randomness in the complex life coding system that creates new traits. Mutations can create an advantage in the arms race as they can lead to unique traits which make an organism fitter for its environment. Advantageous traits tend to thrive, whereas non-advantageous traits will either cease to exist or live on at a subsistence level.

Cyber security is positioned as a similar modern-day example of an arms race, but in reality, it is one system (virus) that is looking for a vulnerability to give it an advantage, and the other system running anti-virus is responding/ adapting to prevent it. The virus can only be created because the system has a fundamental flaw (weakness), and it is a race between those who want to uncover it and those who want to hide it, but the flaw exists. It is not the same.

One could use the free market economy as a modern example of this phenomenon of mutation and homeostasis, whereby we use the words “innovation” and “competition” as synonyms for “mutation” and “survival of the fittest”. To describe innovation as solely beneficial, or solely detrimental would be incorrect; likewise, it is not reasonable to suggest that stability is solely one or the other. In all aspects of life, there is a balance between chaos and order, mutation and homeostasis, and innovation and tradition. Therefore, when we re-frame our thinking, we see that believing in a single, unified purpose is a delusion, as this singular goal only represents one side of a dynamic system whereby control on one end does not create the end game, and we only have a bright future because we have two.

A preference for labelling

If I gave you a choice between “innovation” and “mutation”, which one do you associate with value, creativity and growth?

Transposing the words that describe our natural world directly into a business environment would create fear, uncertainty and doubt. “We are working hard on innovation” sounds more impressive and reasonable than “we are creating new mutations.” “We mostly operate in a competitive market” sounds so much more plausible than “it is an arms race for the survival of the fittest”. Words matter, and because they do, we can use words to create dynamics to be more or less willing to discuss and debate hard topics in the boardroom.

The next section utilises the word “error”; in this context, an "error" is the gap between expected and observed. I understand that many readers will want to stick with their natural framing of an error as right/ wrong, but “error” can mean:

a moral offence;
belief in something untrue;
the state or condition of being wrong in conduct or judgement;
a mistake, blunder, lapse, or slip;
a deviation from perception, expected, accuracy or correctness;
the difference between the observed and actual

Error in this work is closer to the framing of the lower three bullets than the top three.

How does a system based on “error creation” and “error correction” sound?

The dynamic of our natural world system is that one system is creating something new and different whilst the other is trying to correct and mitigate the change. One is bringing in the new, and the other defending the existing. One is the hope of something better, whilst the other is happy not to take the risk and maintain the same. Both sides create risk; strangely, different risks are created by each side, but nevertheless, risk. Error creation, in this instance, is invention, innovation and creativity. Error correction is stability and familiar processes that we know (and trust) from historical experience. The risk in the former is change, and the risk in the latter is to become not relevant. They are different risks.

The risk in the former is change, and the risk in the latter is to become not relevant. They are different risks.

How often do we translate the message we receive from leadership that we need to be both “more innovative” whilst simultaneously “improving efficiency and effectiveness” as a demand to compromise on everything and lack focus? Perhaps we should see this balance as the maintenance of an equilibrium of "error creation" and "error correction" because it creates something new that we label as value.

Leadership that fails to recognise there is a need for balance will fail; we first need to determine where we are in the system and which system we favour; from there, it should be easier to determine what journey we are on and where the north star is.

This is not “trial and error”, as before a trial, there has to be a hypothesis, and the error is a deviation in the results from the expected/ predicted. It is neither “error and trial”, where an error is created without a hypothesis and using some measure, one tries to determine if the error was successful. Then there is AB testing. However, these are all controlled point methods and are not about dynamic reactive complex systems.

The answer to the universe, world and everything (#douglasadams)

To fans of The HitchHickers Guide to the Universe, we know the answer is 42, but the question remains; we just needed another 5 minutes! My struggle with the answer, as given, was whether it was relevant when the question was asked or given since 7.5 million years passed, and a lot happens in big time frames. I would have loved to have asked Douglas.

So often, there is a dynamic between two competing ideas, both trying to be the more important single unifying idea or purpose. Humans want to be both heard and belong. It is not that one is better than the other, but one is more error creation (listen to my new idea) and one more error correction (stability of belonging). Some business leaders will say their purpose is “shareholder primacy”, whilst others say their core purpose is to “improve the lives of their customer”. This is a nonexclusive club - and there are many others - however, most companies settle on a purpose that is a compromise. It is safe to say that business purpose varies depending on the specific goals and values of the company and its stakeholders. It could be argued that the purpose of a business is to balance creating more value for the majority of the customers, shareholders, employees, and wider society as a whole than the destruction or erosion of value for others. Purpose itself is achieved through various competing ideas, such as developing innovative products or services, providing high-quality customer service, maintaining ethical business practices, and contributing to the ecosystem the organisation operates in.

When we reflect on this concept, we see that a business is itself demanding that it “creates errors” and “correct errors.” Remember, this is not “mistakes” or moral pearls; this is seeing innovation as creating change, which is an error to the system of no change. Businesses need to create new ideas and innovations but also correct errors that try to change the stability of process efficiency. Leadership needs to craft a level of instability whilst maintaining equilibrium. Note: another framing of “error” could be morally unethical behaviour and trading without reason whilst insolvent. These activities are not errors; they are illegal, and it is not what we are focused on.

Leadership needs to craft a level of instability whilst maintaining equilibrium.

Perhaps we should accept that there cannot be one single unifying purpose, and we exist in a place where some individuals, leaders, and teams favour change (error creation) and some stability (error correction), but without both, we would lose our ever-changing dynamic stability.

The Purpose and origin of Innovation (as an example of error creation)

Innovation refers to the process of creating something new or improving upon an existing product, service, or process. The purpose of innovation is to bring about positive change and to solve problems more effectively or efficiently. Innovations can be incremental or disruptive, with the latter representing a significant shift in how things are done.

The origin of innovation can be traced back to human curiosity and the desire to improve the quality of life. Throughout history, humans have constantly sought ways to improve their lives, whether it be through inventions such as the wheel or electricity, or the development of new technologies like mobile phones and the web. Innovation has played a vital role in driving progress and advancing society.

Innovation has become increasingly important as businesses seek to stay competitive and meet the changing needs of consumers. Companies invest in research and development to create new products and services to improve efficiency, increase profits, and create new market opportunities. Governments also encourage innovation through funding research and development, providing incentives for businesses, and fostering collaboration between industry and academia.

Overall, the purpose and origin of innovation are rooted in human ingenuity and the desire to create something new and better. Innovation has been and will continue to be a critical driver of progress and growth in all aspects of society, including how we achieve sustainability.

We like innovation as long it is not called error creation or mutation, but the reality is, no matter how hard we try, they are one and the same. If you naturally align with an error correction ontology, you may have a creative mindset and enjoy the process of disruption, change, and the outcomes of instability.

There are exceptions: fraud, bribery and corruption.

The Purpose and origin of Accounting (as an example of error correction)

The origins of accounting can be traced back thousands of years to ancient civilisations such as the Babylonians, who kept records of their transactions on clay tablets. In medieval Europe, accounting was used primarily by merchants and bankers to keep track of their financial transactions. The original purpose of business accounting was to provide shareholders with accurate and timely information about the financial performance and position of an organisation.

Accounting is a system of recording, analysing and summarising financial transactions to prevent errors, provide accuracy, and present information that is useful in making business decisions. Over time, accounting has evolved into a sophisticated discipline with its own set of principles and standards. In addition to serving the needs of businesses, accounting also serves the broader needs of society. For example, accounting information is used by governments to track tax revenues and by investors to make investment decisions. Accounting also plays an important role in maintaining the integrity of financial markets by providing reliable information about the financial performance of companies.

We may naturally align to the framing of finance as long it is not called error correction, doing the same, preventing change and improving stability, but the reality is, no matter how hard we try, they are one and the same. If you naturally align with an error correction ontology, you may have a more accounting mindset, whereby you will naturally look for order amidst chaos and create stable processes out of a loose set of desires.

There are exceptions: fraud, bribery and corruption.

How do other business functions align?

Marketing, sales, and product development appear to tend towards error creation, with operations, legal, and accounting systems tending towards error correction. It is possible that where technology and HR sits is critical to the overall balancing culture of the company and if the company favours error creation (creative, imaginative, innovative) or error correction (stable, historical, and dutiful.)

The descriptions above used “tend towards.” The basic function of accounting is to remove errors, but it also has to improve continually because of the necessity of continually correcting new errors. The basic function of marketing is creativity, never repeating campaigns and coming up with new and different ideas. But if marketing were only creative, it would not be able to align and build upon what is already there and how the market behaves. Creative flair for error creation is tempered by the history and context of error correction. All functions demand both, and we need to understand how the balance is created by the purpose, function, and culture of the team.

Teams define culture. Teams are made of individuals who are either going to be more aligned to error-creating or error-correcting. Whilst we prefer to label individuals as “creative” or “checklist,” these do describe the characteristics, leadership attitudes, and biases that are critical to determining what function a department actually fulfils. These balances are not simple; indeed, they are complex.

Creative flair for error creation is tempered by the history and context of error correction.

A board needs to comprehend, appreciate, and understand if the balance is right. If a board is not diverse in thought, skill, and discipline, that balance may not be found or is easily lost, and the culture of one or the other can lead a business to failure, especially with an overly dominant financial focus as accounting tends to focus on being financially risk-averse. It is worth noting that balance, in this sense, is not about equality; the balance creates enough errors to improve continually (agile) but with enough error correction to be resilient.

The balance must create enough errors to improve continually (agile) but with enough error correction to be resilient.

Wider perspective

The error creation/correction model can scale to other forms of thinking:

Fear can be seen as error creation, whereas trust is error correction. There is undoubtedly a complex relationship between fear and trust that is both immediate and develops over time. Trust can correct fear that is related to an error originating from the past, but trust can also create a new path.
The concept of 'self' is error-creation, whereby we tend to express our individuality within a system of societal norms and memory which seeks stability and error correction. Individuals create eros, and their movement (many followers) creates a change which eventually becomes the new normal.
Freedom allows for error creation, whilst control demands correction from deviation. Too much freedom or too much control both appear terminal based on history. Prison and punishment systems struggle with this balance on so many levels, even using “error correction” as an idea in a different context.
Both error creation and error correction harbour risk, and both can be seen as creating more risk. Benefit demands an understanding of the value and cost of moving away from the known and can be seen as both more error creation (advantage) and correction (prevention).

These examples are non-linear, and balance does not necessarily mean 50:50 and perhaps a less controversial language might be to substitute “error” with “difference.” The difference is the way in which two things, when compared, are not the same.

What else have you observed that represents two sides of a dynamic complex relationship, where one or both favour error creation and one error correction?

It is worth pondering about how and why we try to reduce the complexity of the balance into a single ROI figure in order to pass a hurdle and justify a decision. Can ROI ever capture consequences?

What happens when we get it wrong?

Wrong, in this case, is where the balance is lost, and too many errors or too much correction ends in survival becoming unviable, with death being the only inevitable outcome. Business failure.

In the wild, a mutation that does not provide an advantage can easily be lost, and an overly controlled stable environment can dwindle to nothing if it fails to adapt to modernity.

In the economics of a business, the same is true: an innovation will not give an advantage forever, and the next innovation may not provide a new advantage. Equally, too much control and stability as a result of finance controls and regulation will result in the company becoming outdated in comparison to its environment or ecosystem - the result is the company or sector will enter a slow decline. #banking

A company does not exist on its own but in a complex ecosystem, and the balance may be achieved within the ecosystem and not just in the health or balance of a single company. In nature, the predator-prey model often forgets that the rabbit/fox needs other food and water, as well as the rabbit/fox having other threats. A company may well be out of balance in itself, but balance is remediated by others in the ecosystem, which is why strategy is not just about innovation, but the balance that is maintained by the ecosystem in order to create dynamic stability. It is important to understand who is moving towards stability and who is moving towards innovation; otherwise, the whole ecosystem itself can fall out of balance.

This highlights that any theory of error creation/correction must embrace relevance on at least four levels: individual, team, organisation, and ecosystem. A purpose may articulate what you want, but a purpose that is not dynamic in its ability to move and balance error creation and error correction at all levels is going to be short-lived.

Reframing AI away from “Intelligent Machinery.”

Defining the term 'artificial intelligence' presents us with a problem. The problem is that human intelligence fundamentally depends on a balanced system where error creation and error correction co-exist. Many of the most historic creative minds, insightful thinkers and leading scientists were neurodiverse (error-creating) and spent their lives fighting systems of error correction (academic, power, religious.) Flat earthers, climate deniers and Copernicus with the heliocentric model of the solar system are a few that history has thrown up.

Using the lens of error creation and correction, we can say that we are building ever more advanced error correction systems from big data tools, identification and removal of bias, better accounting, DNA manipulation, eradicating viruses, and using tech to provide compliance, governance, and oversight. In this perspective, it becomes more obvious that we do not currently focus on using ever more advanced tech to actually create errors as a route for advantage. If AI were like nature, an AI that only corrects or one that only creates errors could not survive.

If AI only needs to find and fix errors through the error correction lens, then AI will only be half a system and will be artificial but not intelligent. Data can be error-correcting and error-generating, but if we don't know this part of the ontology, we will never be able to gain more intelligence.

The diagram below expands on this thinking to suggest that there is more than just one system on the error-correcting side. Error correction is more complex as it needs to amend errors which are not advantageous, and promote the development of errors which are. It is equally true that the error creation side has to have a system that moderates errors, or it would be too wild, and create destruction before the opportunity arose to test if a new trait provided an advantage. The closed-loop system is full of complex feedback loops to both control and promote; with both immediacy and delay. What is evident is that the system is neither stable nor unstable but has pulsing oscillation, which keeps it in a delicate balance.

The axis of thriving and death

What came first, the chicken or the egg?

In a world where error correction (driven by the desire to use experience and the past as the solid foundation) is the initiation or y-axis, and the response is error creation (creativity, invention and innovation) or x-axis, we get thinking dominated by being controlled first, and being unstable second, which creates the volatility and ambiguity that allows for dynamic stability, it is a place where we can thrive and grow. This could be our economic and political world viewed through the lens of law, policy, study, social norms, culture, and data.

In a world where error creation (driven by a desire for change, innovation, creativity, adventuring, pioneering, and invention) is the initiation, and the response is error correction (finance, risk management and control), we get instability dominating our thinking, and the environment is unbalanced, yet still in equilibrium. Complexity and uncertainty become leading ideas. In a place of unbalanced equilibrium, we are still able to thrive and grow. This could be our economic and political world viewed through the lens of research, hypothesis, invention, ideation, hope, and imagination.

It would appear that: dynamic stability + unbalanced equilibrium creates a balanced system that thrives.

What we should avoid are too much control and too much error - the question is, what do any of these worlds look or feel like, and how will we recognise them?

The last thing a fish will become aware of is water teaches us that our current environment can feel normal when in reality, it may be out of balance. If we cannot see or know the balance, we have lost our propensity to manage change.

Why does all this matter

Leadership through one lens (unbalanced equilibrium) depends on being curious, whereas leadership from the other lens (dynamic stability) demands a focus on efficiency and effectiveness, but both perspectives need to continually improve how they inform and direct decision making.

We often see fantastic single-idea books that encourage leadership to optimise decision-making towards growth driven by error creation (how to disrupt yourself, agile, reinvention, cross the chasm, the new normal, change management, repurpose, innovation, re-engineering); it is likely, with such a narrow focus, to lead to poor decision-making, as the benefits and outcomes for error correction are ignored or suppressed. This is equally true in reverse, and there are equally brilliant books that optimise for error correction (efficiency, time management, effectiveness, infinite, leadership, tick lists, ethics, merit, principles, governance, accounting, and statistics).

If we try to get the balance for a better outcome from both error creation and correction, we will likely get sub-optimal results for both. Even with all the resources in the world, nature still ebbs and flows, as it cannot optimise for both and has learnt to make compromises, but we thrive because of it.

The title of this long read is “Why finding purpose feels impossible”; on reflection, the title could equally have been “Why a singular unified business purpose is impossible for everyone”. If we accept we have to balance error creation and correction, a single purpose has to favour or optimise for one or the other, which means that many employees and stakeholders feel the stated “purpose” does not align with or represent them. Balance is rarely 50:50, it can come in many forms: 0:100, 80:20, 99:1, etc. Balance exists, but the context is dependent on the purpose you are trying to achieve. This is where exceptional leadership comes into its own.

The takeaway for leadership

A critically important task/ role for leadership, the board, executives, and governance are to determine:

If our organisation favours error-creation or error-correction
Where is the balance for our organisation?
Are we in balance? If not, are we planning to or sourcing the skills necessary to improve balance?
How is balance in our ecosystem achieved, what are others doing?
Is our organisation/ecosystem in or out of balance, and does our action change anything?

The most important purpose for leadership, the board, executives and governance are to understand and determine if our organisation and ecosystem are in or out of balance.

The problem with strategy and purpose is that we can have agreed and have an agreement, but that does not mean we agree. Working out balance is complex, whereas how we are performing against the plan is rather more straightforward.

To determine and find balance, we must shift our focus from individual, singular and expert towards collective, group and ecosystem. Whilst the former is positioned as strong leadership, and the latter is portrayed as introducing delay, compromise, tension and conflict - it is evident that to thrive, we must know how to find and deliver balance.

Can models help us navigate uncertainty?

noreply@blogger.com (Tony Fish) — Tue, 21 Feb 2023 10:36:00 +0000

Probably not but at there end there are 10 ways to prevent assumptions becoming culture

Post the 2008 global financial crisis, the president of the European Central Bank, Jean-Claude Trichet, said in an opening address at the ECB Central Banking Conference Frankfurt, 18 November 2010, “As a policymaker during the crisis, I found the available models of limited help. In fact, I would go further: In the face of the crisis, we felt abandoned by conventional tools.”

The Gap

Many in executive and leadership positions have faced for a while a feeling that our models, simulations and computations are ill-suited to addressing big, messy, complicated real-world problems. There is a gap between the reality we read and measure today and the model that predicted today a short period ago. Since we have yet to create new models and continue to utilise the same ideals, we know there is a gap between prediction and reality, and that gap is leading to poor decisions, which make us see a bigger gap.

Decisions based on models today have short and long-term consequences. Poor decisions because of broken models lead to us missing an agreed performance metric and impact our children as they live with choices removed and unintended outcomes.

It is accepted by some commentators that utility maximisation (the economic concept) is a poor way to navigate uncertainty. The reason is that uncertainty means you cannot be sure you are optimising for the best thing in the short and long term. The map and directions our economic models provide cannot deliver a compass for wicked problems such as climate change and pandemics.

A reason our models fail may be that they start with the wrong outcome preference, framing and assumption, which over time are transformed to no longer be preferences, framings and assumptions but beliefs and culture, and we cannot change them before they break — path dependency. An assumption our utility maximisation economic model took a while back was to value the time of humans unequally (discrimination), and now technology laboured to convert the earth's unvalued natural resources. With this model, humanity ignores the consequences of previous generations' assumptions because they are now cultural, which we experience as differing views on the environment, society and climate.

Does system thinking break at earth scale?

Many of our complex models start with a decomposition ideal to break apart complexity into small discrete components that we find we can model and explore. However, even our understanding of atoms, once the most fundamental building block, actually contains secrets that we still can't fathom; such is the joy of quantum mechanics. As we break things apart, we break connections we did not know existed, and so we cannot recombine the components and make what we started with.

Components don't combine to make the hole. I can put all your chemistry in a bucket, but it will not make you.

If our model depends on the complete understanding of the smallest part and that the understanding is perfect and precise, then when doubt arises or the proof comes that this smallest part is not what we assumed, why do we think that the model will retain its ability to provide precise prediction? When we study our smallest component parts in isolation, what linkages were there to other parts that we did not observe?

Our systems thinking and models depend on a form of separation, boundary, and interface that help us detail how these small components interact. We have a duality of issue insomuch that if our understanding of the smaller part is not right and we also make an error in the dependencies about how this small part interacts, effects, affects and connects to other small parts, we end up with non-linear errors in our models. Exponential (non-linear) errors, just like exponential growth, get big very quickly.

There is a branch of thinking that retains the idea that we will get a large-scale model right because we should be able to model each small basic component part and the dependency between all parts, but we face a dichotomy that we don't know that if the whole can be represented by the parts, because of variables in time delays and the emergence of new recursive loops in the system, which is why our system thinking breaks at earth's scale. At scale, the earth is not a static model but a dynamic living, moving, changing and adapting system of systems. The earth is adopting (not learning), and today's system creates a dynamic change that means tomorrow's system has different dependencies. Our decisions impact and direct that change.

In the small backwater of behaviours, economics and social psychology, there is a discipline called anthropology, the study of human behaviours, which searches for differences and how these tiny one-off behaviours and ideas may be the future and may scale. Hidden in plain sight among all the noise and hubris is the new dynamic changes, which means that our understanding of the small parts and the dependency must adapt continually, or we must recognise that small errors at scale will give false conclusions. It is not that the emerging feedback loop existed when it started; it was created because of the dynamic nature of complex systems. We lack right now the tools to create such new dynamic loops. This means that all our models are wrong; we just don't know by how much.

We lack right now the tools to create such new dynamic loops. This means that all our models are wrong; we just don't know by how much.

Just because all models are wrong, that does not mean they are not useful, but it does mean we need all models and cannot align to only one when we are dealing with issues at the earth scale. This implies that 1.5 degrees are both right and wrong, as is 3.5 degrees. Indeed the idea that any temperature is right or wrong is naive. Further, any one metric that we use as a tool for complex decision-making is going to be wrong.

Decisions based on metrics.

The consequence of the maximisation theory that drives our model has ignored or unvalued some cost. It also maximises for a single outcome, which is never possible. This means that the opposite side of that coin is true, that there will always be an overstatement of revenue and margin that can lead to false intentions.

We are drawn to decisions not based on costs but on the increment between revenue and costs (margin); we shortcut the complexity of the model to a single figure, ROI. Just like temperature in climate models. ROI decisions based on only costs do not exist and, therefore, as a viewpoint, it is discounted - reinforcing culture/ framing and mindset. ROI will always fail as a decision tool as there will always be undervalued costs and hurdles that mean we stretch the assumptions, but we love the idea of boling complexity down to a simple linear narrative.

Can models navigate uncertainty, probably not, but they are the best tool we have. Assuming they are a true compass is a dangerous game, especially if we have a culture that means we cannot challenge the model itself.

I suppose here is the reality, system thinking will fail at the earth scale because assumptions become culture, and we don’t have any examples that culture changes before it breaks. If the model cannot be challenged, we will have to wait until it breaks.

We don’t have any examples that culture changes before it breaks.

Leadership can stop assumptions from becoming culture

Assumptions can become part of a culture when they are repeated and reinforced over time, often without questioning or examining their accuracy or relevance. Assumptions become a part of culture when they are widely held and perpetuated through social norms and values.

To prevent assumptions from becoming entrenched in the company culture, it's important that leadership take steps to challenge and question them, as well as to actively promote more inclusive and open-minded ways of thinking.

So we we asked ChatGPT for some specific recommendations on how to prevent assumptions becoming culture; we will leave it up to you to judge.

ChatGPT please give some specific steps that can help prevent assumptions from becoming a culture?

Encourage critical thinking: Promote a culture of critical thinking and encourage people to challenge assumptions and beliefs that are taken for granted. This can help to break down the barriers that prevent people from questioning assumptions and can lead to more open-minded and inclusive thinking.
Encourage and promote diversity: Encourage diversity in all forms, whether it's through hiring practices, community events, or other initiatives. This can help to break down stereotypes and promote understanding across different cultures and perspectives by exposing people to a wider range of perspectives and experiences.
Foster open communication: Create a culture of open communication where people feel comfortable sharing their thoughts and ideas without fear of judgment. This can help to prevent assumptions from becoming entrenched by allowing people to openly question and discuss them.
Educate everyone: Provide education and training on topics such as cultural competency, unconscious bias, and diversity and inclusion. This can help people to become more aware of their own assumptions and biases, and can promote more inclusive thinking. Share your findings and insights with others. Explain why certain assumptions are inaccurate and how they can be harmful. Encourage others to question their assumptions as well.
Lead by example: It's important to lead by example. Model the behavior that you want to see in others by questioning your own assumptions and being open to new perspectives. By doing so, you can help to create a culture where assumptions are not accepted without question, and where people are encouraged to think critically and with an open mind.
Emphasize transparency: Encourage open and honest language, and be transparent about the assumptions that underlie decisions and actions. This can help to build trust and promote accountability.
Continuously assess and evaluate: Regularly review assumptions and cultural norms to determine whether they are still relevant and accurate. This can help to prevent assumptions from becoming outdated or misaligned with current needs and realities.
Be aware of your assumptions: Start by examining your own assumptions and biases. Ask yourself where they come from and whether they are based on evidence or stereotypes. Awareness is the first step in changing behavior.
Challenge assumptions: When you encounter assumptions that don't feel right, question them. Look for evidence that supports or contradicts them. If an assumption is not based on evidence, it should be discarded.

Hold people accountable: Finally, hold people accountable for their assumptions. Call out harmful assumptions when you see them, and encourage others to do the same. Make it clear that assumptions are not acceptable in your culture.

Bias and Trauma

noreply@blogger.com (Tony Fish) — Wed, 15 Feb 2023 09:46:00 +0000

I have been exploring the research and concepts that bias and trauma are deeply linked. The linkage and directionality are much debated. Trauma creates bias, and equally, bias creates trauma. It would appear that either can be a starting point, but they definitely feed each other, creating complex positive (healing) and negative (detrimental) feedback loops which extend beyond the individual and their immediate relationships to wider society.

Using systems-mapping to address Adverse Childhood Experiences (ACEs) and trauma: A qualitative study of stakeholder experiences

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0273361

Why does this matter, as all data has a bias?

Fundamental to a decision-making role based on data is to demand that we recognise bias and try to remove bias; however, I am now thinking that if we remove the bias, we assume there is no trauma, and therefore, everyone will be rational. Yes, there are some big ugly assumptions in that statement, but the purpose here is about the flow of challenging thinking and not academic rigour to prove something we already know.

In removing the bias, we ignore that bias feeds trauma and that equally, trauma feeds bias; a decision made without this context has no coupling to the reality of the situation. The alternative is that we live with the bias in our data, known and unknown; however, we don't know if the analysis for this person in this situation reflects/ fuels/heals their bias/ trauma or not.

Therefore, the framing of removing bias is not valid; equality, a framing that recognises bias, is not valid as it cannot represent the individual.

Houston, we have a problem. Do we have to reframe bias?

I am all up for understanding bias, but it has become more evident to me that in my thrust to be curious about bias, I have to accept that I am going to have to operate in a dynamic feedback loop, and it will uncover/ reveal trauma. Revelling trauma or bias crosses the creepy line. The creepy line is a very subjective idea and is different for everyone. When I published “My Digital Footprint” back in 2009, I wrote a lot about the creepy line where data collection can be the same, but how you present the data back to the user will either add value or unnerve them. But to know what a user will accept, you test the user's concepts of a creepy line continually to find out when what you are saying becomes unacceptable and back off — deep personalisation. The creepy line and the concepts of privacy are deeply interlinked. Privacy is linked to perceptions of risk, and risk acceptance or adversity equally links to trauma and bias.

Bias, trauma, risk and privacy matter at both levels, macro and micro, but that is a big rabbit hole where we get into identity, but I am interested here in decision-making.

What I am left questioning is whether understanding bias is the right thing to do. Conceptually should we spend more time understanding if this bias feeds something OR if this bias is fed by something OR both? Would both provide new insights to help us give the user better choices and make better decisions, or are we edging toward influence and control and, in doing so, remove agency?

CEO Take Away

Trauma and bias are critical to decision-making. In the board room and leadership executive setting, should we unpack bias and ignore trauma? Bias is easy to talk about, trauma remains “unsaid” - I am not even sure if we assume. The point is, can we use bias as a proxy? Knowing that many CEO’s and founders are driven by trauma, is understanding bias going to take us to a place that will be easier or more difficult to talk about how we make decisions?

Worth reading CEO childhood trauma, social networks, and strategic risk-taking

Love this - but let's not pretend we all agree on what or why we are doing something.

noreply@blogger.com (Tony Fish) — Tue, 14 Feb 2023 15:37:00 +0000

The future isn’t what it used to be: Here's how strategic foresight can help; it is a high-quality, well-written, thoughtful piece from WEF. It is presented by Olivier Woeffray, Practice Lead, Strategic Intelligence, World Economic Forum and Paulo Carvalho, Executive Director, MBA, Lisbon School of Economics & Management.

The truth of the opening statement set the scene, “[We are moving] from a world of relative predictability … to a world with more fragility – greater uncertainty, higher economic volatility, geopolitical confrontations.”

However, something niggled me. I love the future system and exponential thinking; however, I was wondering if the Venn diagram was the right one, but that took me off into thinking about the presentation, not the content. My gut said I was missing something, but I could add all my initial objections into the future or systems thinking buckets. I was warming to the model and indeed feel it is a positive and valuable contribution, but it assumes we have already agreed on two concepts:

what we are optimising for, and
the top-level ontology.

We have yet to agree on what we are optimising for, aka the Peak Paradox framing; we have to acknowledge there are different purposes, and it is not that any are good or bad; they are different. The 13 SDGs have conflicts and cannot all be achieved.

I would also like to know if we have or can agree on a top-level ontology and how to frame what we are optimising for.

The WEF framing assumes we have and can agree on the macroeconomics and therefore focuses on the micro. The model is very valid and helpful at a micro level, but the individuals should test the assumptions, the framing and the perspectives about the macro. Future framing definitely should embrace long-term philosophies of de-growth, sustainability and transparency, but because they are beyond the long-term planning and strategy horizons, they are discounted. Because so much of business is framed by “what problem does this solve”, “free market competition”, and “what is the action”, future thinking is limited to a narrow scope and does not embrace a different ontology or a different optimisation purpose.

Love this - but let's not pretend we all agree on what or why we are doing something.

https://www.weforum.org/agenda/2023/02/strategic-intelligence-why-foresight-key-future-readiness/

Peak Paradox and #privacy

noreply@blogger.com (Tony Fish) — Wed, 04 Jan 2023 10:09:00 +0000

I have explored privacy and identity in a previous post, taken from the perspective of the individual.

This post is from the perspective of the state/ nation/ law. I commented on Michael Becker's LinkedIn post about his list of words and definitions for the identity/ privacy space. I commented that everyone remains fixated on making their particular solution work to a problem the user has not got which is "#privacy." Whilst every language and country has an ideal notion of privacy, the wide variety of cultures means there is no unified “concept of privacy”, even if privacy is explicitly named or defined in their specific language law or culture.

I asked #chatGPT, the “AI” bot from Google, the question, “how would a capitalist and socialist view privacy?”

“Capitalists would see privacy as an important aspect of individual liberty and autonomy and they view privacy as a property right that can be traded or sold, and they may support policies that allow companies to collect and use personal data as long as they have obtained the necessary consent.

A socialist would define privacy as the right to personal autonomy and control over one's own thoughts, feelings, and personal information. It is the ability to make decisions about how and with whom one shares personal information, without interference or coercion from external forces such as the government or capitalist institutions. In a socialist society, privacy would be protected as a fundamental human right and would be respected and upheld by the community as a whole.”

StJohn Deakins added to the comments by suggesting we move on from ideals of the political spectrum to examples.

Korea: dictatorship with command economy: Kim owns you and owns your data, including your thoughts (rights to brain data will become a seriously scary "thing" in the next decade)

China: one-party state, ruling on behalf of 'the people’ with a state-controlled market economy: the party owns you and your data (on behalf of the Chinese people)

USA: individualist democracy with a free market (where companies have the same legal rights as individuals). You own your data, and others own it, too (lots of them).

EU: social democracy with a free market (where markets serve people, and people choose how). You own your data (as a human right). You, in theory, participate in choosing how.

It is remarkably common that concepts can be well-defined in language and law, but there remains to be a wide variance in the understanding and use. Words and language are dynamic and never stationary, and we should not try to own or control them, defining for a context is critical. Just consider love, truth, safety, honesty, work, trust, beauty and risk.

Plotting Privacy on the Peak-Paradox framework makes me consider how the different interruptions are framed by the purposes presented in the mapping. It is evident that the interruption for privacy must vary as we move about our understanding of what we are optimising for. Within Peaks, such as the Peak Individual Purpose, there is a creation of dilemmas, for example, Mark Zuckerberg, who wants privacy for himself but not for any of his #meta users.

To add an additional layer to the complexity onion of privacy, it should be noted that the concept of privacy probably exists in each of us until there is an external demand or constraint. As unpacked in this post, where I pick up on the work of two behavioural scientists, John Darley and Daniel Batson, who published in 1973 “From Jerusalem to Jericho: A study of Situational and Dispositional Variables in Helping Behavior.” It was an investigation into the psychology of prosocial behaviour. The research demonstrates that when we introduce time pressure, our dispositional factors (I like privacy) stand for nothing and that we will act differently because of the constraints.

When you design for privacy, you need to understand what the user is optimising for and be aware that your design will change what privacy means to the users because it is a constraint.

We can be very good at answering questions, but why don't we challenge them?

noreply@blogger.com (Tony Fish) — Tue, 03 Jan 2023 14:10:00 +0000

A problem (among many) with data is that many people ask questions that are easy. How many and who clicked this button? These are easy to ask, occupy time, fill in KPI cards and are often easy to answer. Why do so few kick back to ask if it is the right question? Why did they click the button? Oh, we don’t have that data!

But we can create constraints that mean we get biased data as we don’t understand human behaviour in context.

----

In 1973 two behavioural scientists, John Darley and Daniel Batson published "From Jerusalem to Jericho: A study of Situational and Dispositional Variables in Helping Behavior." It was an investigation into the psychology of prosocial behaviour.

Darley and Batson picked students who were studying to be priests at the Princeton Theological Seminary to determine how situational factors influenced prosocial behaviour. Hypothesis: When someone is kind to another, is that because he or she has some innate qualities that lead to kindness—or because some situational factors simply determine and allow for kind behaviours.

The famous study was across three days in late fall; they had a bunch of seminary students come to a building, meet with a researcher, and fill out a bunch of surveys. The surveys partly addressed if the students were religious primarily for intrinsic or for extrinsic reasons (with “intrinsic reasons” being like “I am motivated to do good in the world” and “extrinsic reasons” being like “I really want to get into heaven.”). Then the participants were told that they needed to prepare a brief talk about The Good Samaritan — which is a story about how a hapless victim on the side of the road was just passed by holy individuals, whilst a non-holy Samaritan took the time to stop and help the fellow out. The story's context is significant as the participants were told that they needed to walk to a nearby building to meet up with another team member and then give their sermon. However, using random selection, the student was told that they:

Had plenty of time, and were early.
Were on time, but should head over now so as not to be late, or
We're running late, and really needed to run without delay - no excuse.

Obviously, the situation was rigged, and all participants found a fallen stranger (an actor) in a narrow alleyway who acted sick on the ground and in need of help. The narrow alleyway was selected as there was a choice: help this guy or step over him!

The “time constraint” crafted behavioural change as:

63% of participants in the “early” condition stopped to help the stranger.
45% of participants in the “on-time” condition stopped to help the stranger.
10% of participants in the “late” condition stopped to help the stranger.

60% of the participants were unwilling to help the “victim.” This is ironic because the participants were Princeton students studying to be priests and about to give a talk on the lessons of the Good Samaritan, but this was manipulated because of the constraints.

A side note before the core finding is that dispositional factors (what you believed) had no bearing on helping behaviour. In other words, people who reported as religious for intrinsic reasons were no more likely than others to stop to help.

When it comes to human behaviour, we have a strong bias toward thinking that people do what they do because of internal traits that drive their behaviours (Dunning, Ross & Nisbett, 1990). The Overconfidence Effect in Social Prediction. Data shows us that dispositional factors are relatively weak predictors of what we do, whilst situational factors (which we cannot see or measure and often seem benign or inconsequential) play a powerful role in shaping our behaviours.

We can only answer the question we have data to, but that does not mean the answer is right or the data is a good predictor because we don't understand the constraints.

CEO Take Away

If data supports your decisions, who is accountable and responsible for ensuring it answers the question we want and is not just data without context? In the next board agenda, put an item as part of AOB, “Do we understand situational bias in our data?” If there is no debate or looks of bewilderment, perhaps it is time to ask better questions of those who think that the data is accurate.

What is the toughest position? A CEO or a goalie?

noreply@blogger.com (Tony Fish) — Mon, 05 Dec 2022 07:54:00 +0000

Which one of the roles is the most challenging, as both are isolated and unforgiving? In either position, the opposition will not like you when you're doing well. When doing badly, your supporters are not on your side. Irrespective of if it is a good or bad day in the office, everyone else knows they can do your job better than you can, and your backers are never happy, always wanting more. So what is the toughest position?

Being ahead

If you're thinking three, four, or five plays ahead, you're not suitable for this role.

There is a reality to both roles that you have to be ahead, to be in the right position at the right time to ensure success, but everyone else just thinks you are lucky. Anyone can do the job, but those who can see signals and read the play will excel.

Blame

No matter how many great things you do, everyone only remembers you for the one you missed

In either position, you have to accept that you’re the last person in the line of defence, and you will regularly take the brunt of the criticism when it goes wrong. But these abilities, to remain humble and stay positive combined with power, agility, and quickness, make those in these positions the strongest leaders.

Touchline criticism

They need an element of insanity, as there is no hiding place.

Criticisms from the sideline can be heard when you stand in one spot; their views are loud and clear. Abuse is particularly annoying when you know the media and crowd have zero experience with your role and do not know the context.

The bottom line is that you have to ignore all those distractions. People on the sidelines are fickle. Anything you do — good or bad — will alter their opinions on you pretty quickly. Stick to what you're good at, and you’ll prove them wrong.

Preparation

Success depends upon previous preparation; without such preparation, there will surely be failure.

In lower levels, particularly in SMEs and youth football, there’s a tendency to stick the CEO in position or the keeper in goal and pelt multiple objects their way from point blank range. It’s one of the worst ways for a leader to prepare. A leader will take charge and create proper warmup routines, which others feel do not warm them up and this creates tensions and conflicts.

Messy

So there’s an enormous blue frog with your name on it.

The CEO deals with people and all the messy complications people bring to any team. A goalie has to deal with a muddy puddle that is cold and wet. Those who lead deal with how they will approach it before they play and not during.

Training

Coaching is not the filling of a pot but the lighting of a fire

It’s 10 of them for every 1 of you. Unfortunately, CEOs and goalkeepers are regularly neglected in team coaching and training sessions. With so many players to work on, leaders and keepers don’t receive the attention they need as they are unique and special; however, they are the ones who can lift everyone else.

Second chance

Is it unprecedented for two CEOs or goalkeepers in competition can both enjoy the result?

Being a CEO or goalkeeper is the most unforgiving position and offers little opportunity for redemption. Sales directors and strikers, for example, can make several poor efforts at a goal and then “get into” the game. If they land the deal or score, those poor efforts are entirely forgotten.

When you step out, you have to be ready because redemption is an uphill struggle. If you make a mistake, you may not get another chance to put it right. You can only keep your head up, stay focused, and learn from it.

Alone on a bad day

Only a CEO can understand the challenges faced by a goalkeeper.

There’s nothing worse than the journey home when you’re kicking yourself over a mistake you made. It’s those key moments that ruin an evening or weekend for everyone. CEOs and goalkeepers truly carry the burden of their errors. No other position holds themselves singularly responsible. With that in mind, it’s unsurprising that some professionals have to quit for a lifestyle with a little less stress. Mental strength, a positive attitude and the determination to go again are required. Wounds will heal. CEO and keepers are easily victimised by their high level of responsibility. It takes guts to be one.

With all that said

Only an outstanding leader can make their team victorious.

Chaos and the abyss

noreply@blogger.com (Tony Fish) — Tue, 22 Nov 2022 10:37:00 +0000

This read describes the space between chaos and the abyss, where we find ourselves when we allow machines to make decisions without safeguarding collective criticism or realise they can change our minds.

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There is a reality that we are not forced to recognise our collective ethical and own moral bias without others. However, these biases are the basis of our decision-making, so asking a machine to "take an unelected position of trust" and make a decision on our collective behalf creates a space we should explore as we move from human criticism to machine control.

Machines are making decisions.

Automation is incredibly powerful and useful, and we continue to learn to reduce bias in automated decision-making by exploring data sets and understanding the outcomes by testing for bias. As we continue testing, iterating and learning about using past data for future decisions, we expose many of our human frailties and faults.

The decisions we ask machines to make today are easily compared to where we think we are going. However, since I cannot confirm or write down my cognitive biases today (out of the 180 plus available). If asked which biases would be the same tomorrow, I would be unable to tell you. Therefore, I am even less convinced that, as a team, we can agree on our team biases as these will change as a new sun rises because we all have eaten our own choice of food, have different biology, chemistry and bacteria and have had divergence experiences since the last sunrise.

AI and Hypocrisy

Hypocrisy is the practice of engaging in the same behaviour or activity for which one criticises another. Our past and present actions can be different, but because of our past, we have learnt, and change has happened, but that does not mean we should not be able to call out when someone is making the same mistakes.

A defence used by those called out is to cry “hypocrisy”. Human rights issues and football spring to mind. How can you judge when you did the same? As a Brit, we are responsible for some of the worst abuses of power and wrong thinking, but we are changing; I agree that it is not fast or far enough. However, the point here is that humans learn and can call something out to other humans if they are making the same mistakes. I accept we are not very good at either.

However, contemporary discourse is that if your past is flawed, you are not empowered to be critical of others. However, if we ever believe that we are beyond criticism, fault or learning, surely we become delusional and unable to see the wrong we are doing, believing we are more moral or ethical. But what about machines? When machines make a biased decision, who is there to be critical or will the AI call hypocrisy?

I struggle with the idea that the company values, purpose and culture are good predictors of the decision-making processes that we have in place because of bias. A good human culture can exist, but that is one of learning, but that does not mean the machine that powers the organisation is aligned with learning in the same direction.

This thinking about hypocrisy and culture creates gaps, voids and chasms filled with chaos between individuals' integrity, the integrity of the wider team/ company and what decisions we ask machines (automation) to make. This is not new, and such gaps have been the study by many philosophies and political scientists since Aristotle.

So how do we enable a machine to make a decision based on data but then allow other machines to see the inconsistency and defend hypocrisy? This is the space between chaos and the abyss.

So how do we enable a machine to make a decision based on data but then allow other machines to see the inconsistency and defend hypocrisy?

Being explainable is not the problem.

Explainable is in fashion in AI; however, events of 2020 to 2022 have presented rich picking from COVID lockdowns, the cost of living crisis, football WorldCup hosting and COP28 to say that explainable is not much use when decisions impact humans. Equally, making an algorithm or the code behind it explainable does not solve the problem. Neural networks are accurate but un-interpretable, whereas Decision Trees are interpretable but inaccurate. I can explain an outcome, but that does not mean I can predict it. We can explain mass shootings, but that is of little value or comfort to those who lost a loved one.

Jumping into the abyss.

Machines with bias in decision-making are not new, nor is explainable AI thinking. However, when we (humans) are criticised or called out, we often become defensive and don't change. Will machines be different? Calling out that someone is wrong does not persuade them to follow a different path. Calling out a decision made by a machine is not going to change the machine's decision-making process.

Here is the final jump. How to change someone's mind is a super article from Manfred F. R. Kets de Vries at Insead. It sets down The Scheherazade method of Seven steps to change a person’s mind. Now when a machine learns that it is easier to change a human mind by following these steps, are we in danger of seeding the last part of independent thinking to the machine? We will not see the problems as our minds have been aligned to someone elses decision-making methods (calling out loyality). It is why we need a void between morals and ethics and should celebrate unethical moral and immoral ethics as they show us the tensions and gaps in our thinking and allow us to learn.

This is a nod to Brian Cork based on his comment on a previous article on Fear thank you.

We need more unethical morals!

noreply@blogger.com (Tony Fish) — Thu, 17 Nov 2022 13:45:00 +0000

I explore ethics, morals and integrity in the context of decision-making. This piece explores the void between ethics and morals and why we need this place to exist because it allows us to explore the reason why unethical morals force us to new thinking.

The difference in definition between Ethics and Morals

Definition: Ethics are guiding principles of conduct of an individual or group.

Definition: Morals are principles on which one’s judgments of right and wrong are based.

Therefore an important difference between ethics and morals is that ethics are relatively uniform within a group, whereas morals are individual and heavily influenced by local culture and beliefs.

How to change someone's mind is a super article from Manfred F. R. Kets de Vries at Insead. It is important because if we want more people in the moral group, we need those with different ethics to change. And if we want to update our morals, we need to be able to change our ethics.

In Manfred’s article, I believe that ethics and morals become mixed up between what a writer means and what the reader understands. It is very confusing when a narrative uses the ideals of ethics and morals but only applies one of the words.

What we are aware of is that there is a dynamic relationship between what an individual thinks and what a group thinks and how both an individual can affect group thinking and group thinking affects individuals. #Morals are based on our own #principles - which are influenced by our society's values. Those values create unique #ethics, which are "rules" a particular societal system gives to those in that place.

Because values are not principles, and rules are not values, it creates friction which we see as moral and ethical voids - spaces where you can have unethical morals. Rules, how we control ethical behaviour is always a laggard, which means those at the forefront of change see the void and gaps between the perceived new values and the old rules.

From a linear world viewpoint, we understand this dynamic relationship between ethics and morals as they both challenge and refine each other for the betterment (we aspire to) of both, but there is a time lag.

However, simple language and diagrams create this rather naive viewpoint because what we witness is that our morals are challenged by society, yet we often need a movement before our collective ethics create better moral outcomes and new rules.

Therefore we have a time-lagged gap or void which prevents the full alignment of morals and ethics. I never realised how important this time lag is. Without a time lag, which creates separation, we would never improve but rather get trapped in negative and unproductive ways because we all accept this moral or ethical behaviour as the best we can do.

It is in this void we find all the complexity of modern society and politics.

This gap represents the tensions that boards and leadership teams have to face as they find that they need to find a strategy and route between the new thinking and the old rules.

COVID19, climate change, sustainability, and poverty are just some examples that have made us more aware of the gaps between different nations' rules, constraints and resources which provide their ethics and different mental model for a morally better society. If it is or not is yet to be determined.

Therefore I believe we should be asking for more “unethical moral”, and more “immoral ethical” dilemmas; as this will focus our attention on the void between our existing rule set and the new rules we need if we are to make a world more inclusive, accepting and transparent and less biased, cruel and prejudiced.

I repeat …. we need more unethical morals!

Why does fear fill the gap?

noreply@blogger.com (Tony Fish) — Wed, 09 Nov 2022 10:41:00 +0000

In that moment of panic, we forget to reflect on what type of gap this is and why it has been filled with fear. Leadership is a recognition of the gaps, that not all gaps are the same and how to prevent fear being the first response.

Image source: Susan David, Ph.D (love her work)

Fear and Gaps

Fear is an unpleasant emotion caused by the immediate or expected threat of danger, pain, or harm, but it is also so much more. We know fear sells in terms of marketing. We understand FOMO (fear of missing out) and the fear of failure (FOF) are significant drivers. We are aware that fear produces a unique reaction in the body driven from the gut ahead of the brain (Antonio Damasio research). Fear is a stimuli but is subjective and how fear is perceived is different for everyone. Different types of fear spread at different speeds. Brands and the media use fear and to create headlines and force change. COP27 and climate change agenda are not adverse to utilising this insight.

We should be aware that fear drives many decisions we make. Therefore, the interesting question becomes, “Why is it that fear fills the gaps between what we know/ believe and the unknown/ uncertain?” A further question on the link between fear and trust is worth exploring, but it is beyond this post.

Why is it that fear tends to be the feeling that fills the gaps between what we know/ believe and the unknown/ uncertain?

Peak Human Purpose

In the Peak Paradox framework, one of the peaks to optimise for is “Peak Human Purpose”. Each of the four purposes of the framework exists at the exclusion of anything else - purity at an extreme. At peak human purpose, we are here (humans on earth) to escape ultimate death by reproducing as much as possible with the broadest community we can. We also have to adapt as fast as possible. We have to meet our chemistry requirements to stay alive for as long as possible to adopt and reproduce at the expense of anything else. These form the most basic definitions of life with clarity and purity.

Whilst the purity of all the peak purposes might be controversial (even to myself), saying the purity of human purpose is chemistry/ biology does not go down very well; it is too simplistic. However, this is a model for framing thinking, so please go with it as it needs to be pure, and every other human purpose has conflicts with someone. The point here is that when we realise that fear and/or anxiety fills gaps, we understand that we are optimising for something deeply human - life, survival, and thriving.

The point here is that when we realise that fear/or anxiety fills gaps, we understand that we are optimising for something deeply human.

I am often questioned why I put “Human Purpose” as one of the peaks, and it is because of some deeply human traits of life that influence our decisions and create conflicts and tensions within us and our groups. Fear and anxiety are some of these feelings. I am neither an expert, counsellor or theorist in any human behaviour or psychology; however, that does not stop me from realising how much chemistry, biology and experience influence our decision-making, if we want to realise it or not. These disciplines are currently undervalued as is that fear is baked in to some systems from management, control and performance.

Different gaps have different fears

Different gaps have different fears sounds obvious, but it is not, as the only gap that fear is filling is the one in front of us right now. Fear steps in when there is a gap in our knowledge/ information. We hear a noise we cannot explain; someone is walking behind us or an imagined scenario. Fear is not limited to our personal lives and is an active component in the world of our daily commercial activities and actions. Geoffery Moores's Book “Crossing the Chasm” is about a book that sells by creating fear. The book is much more important than that and is a fantastic insight into adoption - however until you knew about the chasm, you did not fear it.

Without a doubt, life would be easier if only one gap and one fear existed. However, we have to be content with the fact that every moment we are dealing with different gaps (leadership, innovation, knowledge, information, experience) and different fears that come from the gaps we have right now and those we image in the future.

What do we image are the boundaries?

The image below illustrates two different gaps. The original thought was caught in an ESG session, so using this as an example. For some, ESG is a gap (think fear) between what is unknown and known and how we cross it (the gap on the left below.) For others, ESG is a gap (think fear) between what is known and the action they need to take (the gap on the right below.) At the recent Sibos conference*, where this thinking emerged, was a debate about the role data has in ESG and whether data can ever be useful because there are two gaps. A good question to ask is which area does your ESG data fall? This removes the ideas about for and against, and forces you to determine which camp your data represents!

The fear in each gap is real and, depending on the persona and team - determines how you will cross your fear fill gap. However, this model whilst “obvious” might not actually be a good representation of the issue..

Just Fix It

We (humans) tend to have an obsession with fixing things. The majority who will read this realise that we cannot fix wicked problems, usually because we cannot understand them. Even our systems thinking and explanation have limits because of the boundary interconnection problem. (the unknown consequences of your action on another system and vice-versa).

When you hear someone bark an order to “fix something”, we know it resembles the old order of control, dogma and hierarchy. There was a belief that in a more simple time, leadership should/could just fix everything. However, not everything is easy to fix (humans, climate, economy, inflation) and not all problems have solutions (my favourite is pure maths), and the majority of what we face every day requires us to walk past the ideal of a “quick fix” and wrestle with the complexity of wicked systems.

We should not ignore the power and pull of a “fix it” mental model. We all tend to do it as a first untrained response when faced with a fear, gap or problem. Because of the “fix-it” mental model, our gaps are mostly filled with fear because there is no immediate fix within our experience. Our early experience in education and business teaches us we can “fix it” by defining the problem and building a solution. To do this, we have to accept we must ignore critical facts that add complexity to the actual problem or lack experience to see such layers.

Management, leadership and MBA courses all spend a lot of time teaching us to ask, “what is the problem to be solved?” Usually, so we can determine if the pre-packed solution on offer aligns with the problem at hand. When we know the problem, we can write a plan. This fix-it provides a perception that we know how to cross the two big chasms filled with fears. This is not true because a “Fix it” mentality and language ignore struggles, dilemmas, compromises and paradoxes.
We, humans and our environment, are not a problem to be fixed but something to be crafted, shaped and moulded over time.

We, humans, and our environment are not a problem to be fixed but something to be crafted, shaped and moulded over time.

The purpose of the Peak Paradox framework is to embrace “fix it” thinking for simple things but then build a model that allows us to picture and imagine many of the complications of a dynamic interactive, interdependent system of systems. Wicked problems.

A single independent system can be modelled and might be fixable. A system of systems cannot be modelled or fixed as there are unknowns at the boundaries between the systems presenting unknown effects, dependencies and consequences. Not all humans have the same motivations, incentives or desires - a core identification in the peak paradox framework.

Moving on from the “fix-it” model

When we take out the “fix-it” thinking and redraw the two chasms, we observe that it is critical that executives are able to cope with leading in uncertainty and management who remain flexible so they can continually adapt the plan. I would argue this is why reporting and compliance boards fail and don’t work for any stakeholder, as they focus on the wrong model - “fix-it”

How does fear align with the Peak Paradox framework and thinking on sustainability?

“Fix-It” thinking defines problems and solves them or ends up with gaps filled with fears, the information gap. I see too many executive boards fixated on reporting, gaps and compliance, translating leadership into an instruction to fix it as there is a divergence between the plan and the actual. Leadership is surely about bringing vision, belief and skills to help bridge the gap, not by barking instructions to fix it but by providing the next base camp on an uncharted map. Stakeholder trust management to be flexible and adaptable so cope with change and the plan is there to change and not to manage to. The delta (gap in the plan to actual) is not to be feared but embraced and understood. Dashboards are a leadership killer

Dashboards are a leadership killer

Humans and the earth (terra firma, water and climate) need to find a sustainable compromise and are the same in this respect. We don’t need to be fixed, and we don’t need fixing. What we do need is a map.

Cop 27 “Fix-It” or map?

The obsession with 1.5 degrees to me is a problem. The earth will not end, but yes, it will definitely become far more difficult for humans on earth to thrive over just survive. The changes in temperature will affect some humans in some regions far more. Our favoured economic model is likely also to tested to a breaking point.

I am a massive supporter of SDG’s and change but my issue is that 1.5 degrees is a solution to a problem that we have not fully defined and depends on the “we can fix-it” mental model; The same with NetZero and ESG data. These are solutions to problems we don’t understand. These are wicked problems that should not be boiled down to a single number that no one can do anything about. 1.5 degrees is not a vision, a north star or a plan - it is a target. It should be the first camp on a long journey. However fear fills the gaps and drives a model that drives more fear into making the gaps bigger.

Perhaps we should step back to agree and determine what fears and gaps we are talking about.

Thank you.
* At Sibos 22 (the big banking, payments and finance conference), I had the joy of meeting a flock of old friends and meeting IRL some new ones I had only ever interacted with digitally. During one of the #Innotribe ESG sessions, it was good to interactively pen ideas based on the content as I sat with Yael Rozencwajg, which has become this post.

How to build a #team fit for #uncertainty

noreply@blogger.com (Tony Fish) — Thu, 20 Oct 2022 15:23:00 +0000

The pandemic changed us, our views, what we value and how we work. We might not recognise all the changes and hang on in the hope of a return to something we loved, but we must make the best of it now. We should be aware that the change has not only affected us but also our teams.

Whilst the Bruce Tuckman 1965 forming–storming–norming–performing model of group development is timeless. No one is likely to dissent that phases remain necessary and inevitable for a team to grow, face challenges, tackle problems, find solutions, plan work, and deliver results.

However, because we have changed, so has the utility of the tools we apply that move us along the journey from forming to performing. Tools learnt and built in stable and certain times, have less applicability when we are faced with volatility and uncertainty.

It is the usefulness of tools we utilise that move us on the journey from forming to performing that has changed.

More books and articles on “teams” and “leadership” exist than on almost all other management topics. However, forming teams today and how to get teams to perform is continually changing. Below is a new framework for the tool bag. Frameworks are just like a tradesperson supplementing their faithful and well-used wooden screwdriver with a sophisticated modern digital electronic driver. Both are needed, but the update can be faster and have more applications.

Because this is not a book on team building, an overly simplistic view of the Tuckman model is to recognise there are tensions and compromises in all new teams that have to be addressed (storming.) When addressed, align the team to the reason this team exists (norming.) Finally, focus on the tasks that are delegated to the team (performing.) If only it were that simple or that quick!!! Critically team leadership helps the team realise, faster than it would otherwise, that this team has an identity, purpose and unique capabilities.

The focus of the Peak-Paradox framework in this context is to aid in the unpacking of the storming part in the process. How to unpick and identify different tensions and compromises is essential, and there are many tools for this when the markets are stable and certain. The Peak Paradox framework has the most value in this part of a team's journey, especially when everything is changing. Digital interactions, Gen Z and remote working mean we need new tools to supplement the existing ones.

The Peak Paradox framing makes us realise that teams and communities don’t naturally exist in all places equally. The purer the purpose that drives an individual, the less likely they can find others who will make a team and walk someone else's path. Yes, there are certain exceptions, but those are not normal.

Teams and communities don’t exist in all places equally.

At Peak Paradox, where you try to optimise for everything, teams will not naturally exist as those in the team cannot agree on what they are optimising for. Debate, argument and hostility remain forever, with a team never escaping the forming stage. Indeed, forming a team with individuals who dwell at the two extremes (Peak Purpose and Peak Paradox) would appear to be futile. However, when humans' only mission is to survive, some of the best teams form. Always an exception.

Note: these comments should not be confused with applying the Peak Paradox framework to leadership or decision-making - the focus here is purely on team storming.

A team can start weak, messy or strong - the descriptions of the areas on the chart. They will all still follow the forming – storming – norming – performing model. These three areas give rise to where teams form and where teams need to move if they are to perform.

Weak teams. The reality, the individuals are not weak, the team is weak. These teams are made of very strong-minded individuals who know what they want, can lead themselves and know what to do but cannot work as a team at the outset. In this case, it is about unpacking what purpose they align to and how they would approach fulfilling the purpose this team has. This allows you to unpack what tensions and compromises they have to live with and how they will deal with them. The right question to ask each team member is, “Where do you naturally align on the four purposes?” Often these teams find they need to lose members or find a different leadership style to be able to move on.

Messy teams. This is because the individuals are messy, and we come with bias, history, experience and incentives. Messy teams are full of individuals who grasp compromise and tension and live with it every day but have been unable to find the right place for them. They are drawn to optimise for many things at the same time, they comprehend ambiguity, complexity, volatility and uncertainty. Messy teams can be easily guided by strong leadership, but often the cracks appear much later when an individual cannot live with the compromises that are now enforced. The right question to ask each team member is, “What is the one thing you will not compromise over because it creates tension you cannot live with?”

Strong teams. Teams both start here and should come here to perform, as there is a balance between clarity of purpose, tensions and compromises - sufficient diversity of thought and experience means they can work through problems that occur on the journey the team travels in delivering.

The team who starts here will still go on the same F-S-N-P path and, depending on the alignment the team has (if well selected), can get to performing fast. A misaligned team that was selected because of the wrong criteria can fall apart and never get anywhere - this is due to the fact that the individuals oppose the purpose and optimisation of others in the team. The division is divisive. Strong starting teams are not always the route to the best outcome. The trick here is to use the Peak Paradox model to select diverse team members who will be able to cope with the demands and requirements other team members place on the group. The right question to ask is, “What will you compromise on to make another team member more successful?”

The teams who come to this area from a different starting place, messy or weak, may take time however, on that journey, some team members may have to be lost, and others may be transformed, but they will come to a strong alignment and cohesion by the time they are performing. This is a thing of beauty. The right question to ask when you get to norming is, “what sacrosanct thing can you compromise on to be part of the team?”

The value of the Peak Paradox framework to modern team building is it enables you to ask questions and plot where people are. This allows you to visualise gaps so you can work on how to bring a team together to perform. This is very different to culture and style analysis.

Why is this new? Because Gen-Z is much more opinionated and vocal on their purpose than previous generations, they are also far less likely to compromise to be in a team they don’t want to be in. Old tools still work, but new tools can help us get there faster.

The title is “How to build a #team fit for #uncertainty”

When there is stability and certainty, teams can perform with a far narrower, more holistic and aligned view, principally because decision-making has more data, and history is a good predictor. There is a greater demand for variance, tension and compromise in teams during instability and uncertainty. Building teams that are resilient when all is changing demands a deeper understanding of what drives individuals and how they cope with new tensions and compromises. To do that, we need new tools to help leadership and team builders visualise what they have and where they need to be.

My suggestion to start this, is that you

1. Plot where the team needs to be on the Peak Paradox map to deliver its objective.

2. Plot the individuals and determine if you have a team that can deliver or has too many tensions, which means compromise will not be sufficient to get them to perform.

3. Do it again before each review or every time a new member joins or leaves.

4. Question yourself if the current team is too narrow and aligned or too divergent and divisive.

Another reality - none of this is easy, and for anyone who entered work place post-1990, this is different to other significant but localised market disruptions in 2001 and 2008.

The Gap between #Purpose and #How is filled with #Paradox

noreply@blogger.com (Tony Fish) — Tue, 20 Sep 2022 10:00:00 +0000

Data would indicate that our global interest in purpose is growing. In truth, searching on Google for purpose is probably not the best place to start, and I write a lot about how to use data to frame an argument as this viewpoint highlights that the gap between purpose and how is filled with paradox.

Source: Google Trends

The Peak Paradox framework can be viewed from many different perspectives. In this 3-minute read, I want to focus on the gap between “Purpose” And “How.” For example, Robin Hood's (as in the legendary heroic outlaw originally depicted in English folklore and subsequently featured in literature and film - not the stock trading company) purpose was “The redistribution of wealth.” He and his band of merry fellows implemented the purpose by any means, mainly robbing the rich and giving to the poor (how they did it). The Purpose was not wrong, but How was an interesting take on roles in society. Google’s Purpose is to “Organise the world's information.” How it does this is by collection and ownership of data. The Purpose is not wrong, but How is an interesting take on data ownership. Facebook's Purpose is “To connect every person in the world.” It does this by using your data to manipulate you and your network. The Purpose is not wrong, but How Facebook does it is an interesting take on control and the distribution of value?

Reviewing the world's top businesses' mission/ purpose statement, we will conclude that “in general, “purpose is good.” When we question “How” the purpose is implemented, we shine a light on the incentives, motivations and methods.

“How” provides insights into the means; however, we should not be too quick to judge how. Consider The Suffragette mission, Climate Change movements or Anti-Apartheid. Sometimes “how” is left with fewer choices or options?

Apple’s Purpose is “To bring the best personal computing experience to students, educators, creative professionals, and consumers around the world through its innovative hardware, software, and internet offerings.” How Apple does this is to make you dependent on them, their products, and their services. Apple now positions their devices (iwatch), meaning you might not make it out alive without one. The “How” is to exploit via lock-in users without them realising (they are not alone.)

We should question what Principles “How” aligns to

In political systems we see structural tensions. Different sides of political systems don’t demand worse security, degrading healthcare, more poverty or less education. Fundamentally everyones similar purpose is a better society for all and that is broadly accepted, however #how individuals believe a policy can be delivered creates tension, fractions and division. Along with the allocation and priority of resources created by scarcity. #decisions

The Peak Paradox framework positions different ideological purposes to expose the conflicts that we all face as we cannot optimise for one thing at the exclusion of others, but we have to find our place where we feel at peace, and even better if we can find a team who also find rest within the same compromises. That does not mean we have to agree or not be challenged, as the world will throw enough of those.

Take Away

As you move towards making decisions, the decisions become about details to realise your balanced purpose. The HOW implementation decisions need to align with principles, and this is where we see the gaps. The gap is not in the purpose but in the misalignment of the implementation to principles that we believe in if we were asked to deliver the purpose.

If we were asked to deliver the purpose, a gap appears at the misalignment of the implementation to principles between what we believe in and what others align to.

How we value time frames our outcomes and incentives.

noreply@blogger.com (Tony Fish) — Thu, 15 Sep 2022 09:57:00 +0000

I am aware that a human limitation is our understanding of time. Time itself is something that humans have created to help us comprehend the rules that govern us. Whilst society is exceptionally good at managing short-time frames (next minute, hour, day and week), it is well established that humans are very bad at comprehending longer time frames (decades, centuries and millenniums). Humans are proficient at overestimating what we can do in the next year and wildly under-estimate what we can achieve in 10 years. (Gates Law)

Therefore, I know there is a problem when we consider how we should value the next 50,000 years. However, we are left with fewer short-terms options each year and are left to consider longer and bigger - the very thing we are less capable of.

Why 50,000 years

The orange circle below represents the 6.75 trillion people (UN figure) who will be born in the next 50,000 years. The small grey circle represents the 100 billion dead who have already lived on earth in the past 50,000 years. The living today is 7.7 billion, the small dot between the grey and orange.

The 100 billion dead lived on a small blue planet (below), which we have dug up, cut down, moved, built and created waste - in about equal measures. These activities have been the foundation of our economy and how we have created wealth thus far. We realise, in hindsight, that our activities have not always been done in a long-term sustainable way. Susutainble here should be interrupted as the avoidance of the depletion of natural resources in order to maintain an ecological balance.

Should we wish for future generations also to enjoy the small blue planet, a wealth or value calculation based on time will not shift the current economic model. We need to move the existing financial model based on exploiting "free" resources to new models focused on rewarding reuse and renovation; how we use discount rates as a primary function for justifying financial decisions works in the short term but increasingly looks broken because it does not support long-term sustainability thinking as part of any justification. Time breaks the simplicity of the decision.

Therefore, we appear to face a choice; that can be summarised as follows:

If we frame #esg and #climate in the language of money and finance, the obvious question is how do we value the next 50,000 years, as this would change how we calculate value - in the hope that it would move the dial in terms of investment. We need to upgrade the existing tools to keep them relevant.

If we frame #esg, #climate and our role in caring for our habitat as a circular economy (a wicked problem) and not a highly efficient/ effective finance-driven supply chain, we need a different way to calculate value over time economically.

Should we search for the obvious over wicked complexity?

Many deeply intellectual and highly skilled disciplines instinctively favour complex explanations that make their voice sound more valuable and clever. (Accounting, AI, Quantum Physics, Data Analysts, Statisticians, human behaviours). A better solution may lie in something seemingly obvious or trivial, which is therefore perceived to have less value in the eyes of the experts. We can make #ESG and ecosystem thinking very complex, very quickly, but should we rather be asking better questions?

We know that better science and more data will not resolve the debate. When we use data and science in our arguments and explain the problem, individuals will selectively credit and discredit information in patterns that reflect their commitment to certain values.

Many of the best insights and ideas are obvious, but only in retrospect as they have been pointed out, like the apocryphal story of "The Egg of Columbus". Once revealed, they seem self-evident or absurdly simplistic, but that does not prevent their significance from being widely overlooked for years.

Can data lead to better humanity?

We are (currently) fixated on data, but "data'' has morphed from "useful information" to refer to that unrepresentative informational lake which happens to have a numerical expression for everything and hence capable of aggregation and manipulation into a model that predicts whatever outcome you want. It is very clever, as are the people who manage and propagate it.

ESG, climate and the valuation of nature has become "data" - hoping it will improve decision-making and outcomes. Using data, we have already been able to put a value on most of our available natural resources, including human life (life insurance). Whilst we can value risk and price in uncertainty, we have not found or agreed on how to measure or value "the quality of life".

Right now, businesses can only decide based on their data and financial skills. This makes leadership look cleaver and capable in the eyes of an economist, but we are at risk of acting dumb in the eyes of an ecologist, anthropologist and biologist. Reliance on data can make you blind to the obvious. Jeff Bezos commented, "When the anecdotes and the data disagree, the anecdotes are usually right". Our climate challenge might not be about data but reframing to make the obvious - well, obvious. Perhaps we should stop asking leadership to decide everything based on data or value and instead demand they care for our natural world if it was their only job!

Perhaps we should stop asking leadership to decide everything based on data or value and instead demand they care for our natural world if it was their only job!

Imagine two models; in the first, you have one pen for life, and in the second, you have a new pen for every event. One model supports "growth", and the other a more sustainable ecology. One helps support secondary markets such as a gift economy and can make an individual feel valued. The other is a utility, where the pen has no instinct economic value beyond function but has an unmeasurable sentimental value.

If the framing is growth and profitability, then the former model appeals to investors as there is a growing demand for more pens. This also drives innovation and differentiation, and so emerges an entire pen industry. (telegraph road - dire straits) Employment and opportunity are abundant, but so is the consumption of the earth's resources, and no one cares if a pen is lost or thrown away. Related industries benefit from gifts to delivery - a thriving, interconnected economy.

If the framing is for a sustainable ecology, pens are just a means for an entire ecosystem to develop. One pen for life means it is maintained, treasured and repaired. There is no growth in the market, and innovation is hard; there are few suppliers with cartel-type controls. Transparency and costs might not be a priority. However, if those who made the pens could also benefit from the content/ value/ wealth created by the pen, such that the pen is no longer stand-alone but tiny incremental payments over life - everything changes. Value is created by what people do with the pen, not the pen itself. Pick axes in the wild west railways is a well-documented example, what would have happened if they were given a percentage of train ticket prices?

Where does this shine a light?

It appears that decision-making and the tools we need for a "sustainable" age are different from what we have today. First, we need to ask questions to realise the tools we have are broken; however, all our biases prevent us from asking questions we don't want the answer to.

Below are five typical questions we often utilise as aids to improve decision-making. What the commentary after each question suggests if that our framing means we don't ask the right questions, even though we are taught these are the right questions.

Have I considered all of the options or choices? Too often, we assume that there are no additional alternatives and, therefore, the decision has to be made from the choices you have right now. We also discount alternatives that appear more difficult. If the choice we want is available, we ignore others.

Do I have evidence from the past that could help me make an informed decision? We will never change if we depend on history because we reinforce past experiences as conformational guidance and reassurance.

Will I align with this decision in the future? To answer this, you need to have imagined and articulated your future and then tested it to check that it is still valid with how others see a future. It is far too easy to make wild assumptions and live a fantasy. How you see the future might be wildly different from those, you need support from to be able to deliver the future.

What does this decision require from me right now? This is a defence question to try and find the route of least resistance and lowest energy. We use this as a way to justify efficiency and effectiveness over efficacy.

Is this a decision or a judgement? We find some facts and data are preferable to a route we find too hard, so we ignore them and say it is a judgement call or a gut feeling. When data shows us a path we don't like, we tend to find reasons to take the path we want. (re-read that Jeff Bezos quote above)

These simple questions highlight that we have significant built-in path dependency, which makes asking new questions and seeing the limitation of our existing tools hard. A wicked problem emerges because our existing tools and questions largely frame outcomes to remain the same.

It follows that purpose should bound strategy, and both should frame structure. Without purpose, strategy is just a list of tasks and activities; determining what you do leads to a better outcome is somewhat impossible. We obviously value time, as it frames our strategy, outcomes and incentives.

Therefore the question to comment on is, "how should we measure the quality of life today, and how will our measures change over the next 100 years?"

Can frameworks help us understand and communicate?

noreply@blogger.com (Tony Fish) — Wed, 27 Jul 2022 15:50:00 +0000

I have the deepest respect and high regard for Wardley Maps and the Cynefin framework. They share much of the same background and evolution. Both are extremely helpful and modern frameworks for understanding, much like Porter’s five forces model was back in the 1980s.

I adopted the same terminology (novel, emergent, good and best) when writing about the development of governance for 2050. In the article Revising the S-Curve in an age of emergence, I used the S-curve as it has helped us on several previous journeys. It supported our understanding of adoption and growth; it can now be critical in helping us understand the development and evolution of governance towards a sustainable future. An evolutionary S-curve is more applicable than ever as we enter a new phase of emergence. Our actions and behaviours emerge when we grasp that all parts of our ecosystem interact as a more comprehensive whole.

A governance S-curve can help us unpack new risks in this dependent ecosystem so that we can make better judgments that lead to better outcomes. What is evident is that we need far more than proof, lineage and provenance of data from a wide ecosystem if we are going to create better judgement environments, we need a new platform.

The image below takes the same terminology again but moves the Cynefin framework from the four quadrant domains to consider what happens when you have to optimise for more things - as in the Peak Paradox model.

The yellow outer disc is about optimising for single outcomes and purposes. In so many ways, this is simple as there is only one driving force, incentive or purpose, which means the relationship between cause and effect is obvious.

The first inner purple ring recognises that some decision-making has a limited number of dependent variables. System thinking is required to unpick, but it is possible to come up with an optimal outcome.

The pink inner ring is the first level where the relationship between cause and effect requires analysis or some form of investigation and/ or the application of expert knowledge. This is difficult and requires assumptions, often leading to tension and conflict. Optimising is not easy, if at all possible.

The inner black circle - where peak paradox exists. Complexity thrives as the relationship between cause and effect can only be perceived in hindsight. Models can post-justify outcomes but are unlikely to scale or be repeatable. There is a paradox because the same information can have two (or more) meaning and outcomes.

The joy of any good framework is that it can always give new understanding and insight. What a Wardley Map then adds is movement, changing of position from where you are to where you will be.

Why does this matter?

Because what we choose to optimise for is different from what a team of humans or a company will optimise for. Note I use “optimise”, but equality could be “maximise”. These are the yin/yan of effectiveness and efficiency, a continual movement. The purpose ideals are like efficacy - are you doing the right thing?

What we choose to optimise for is different from what a team of humans or a company will optimise for.

We know that it is far easier to make a decision when there is clarity of purpose. However, when we have to optimise for different interests that are both dependent and independent - decision-making enters zones that are hard and difficult. It requires judgement. In complexity is where leadership can shine as they can move from simple and obvious decision-making in the outer circle to utilising collective intelligence of the wider team as the decisions become more complex. Asking “what is going on here” and understanding it is outside a single person's reach. High functions and diverse teams are critical for decisions where paradoxes may exist.

When it gets towards the difficult areas, leadership will first determine if they are being asked to optimise for a policy or to align to an incentive; this shines the first spotlight on a zone where they need to be.

Why do we lack leadership?

noreply@blogger.com (Tony Fish) — Thu, 21 Jul 2022 07:13:00 +0000

Because when there is a leader, we look to them to lead, and they want us to follow their ideas. If you challenge the leader, you challenge leadership, and suddenly, you are not in or on the team. If you don’t support the leader, you are seen as a problem and are not a welcome member of the inner circle. If you bring your ideas, you are seen to be competitive to the system and not aligned. If you don’t bring innovation, you are seen to lack leadership potential.

The leader sets the rules unless and until the leader loses authority or it is evident that their ideas don’t add up when a challenge to leadership and a demonstration of leadership skills becomes valid.

We know this leadership model is broken and based on old command and control thinking inherited from models of war. We have lots of new leadership models, but leaders who depend on others for ideas, skills and talent, are they really the inspiration we are seeking?

Leadership is one of the biggest written-about topics, but it focuses on the skills/ talents you need to be a leader and the characteristics you need as a leader.

So I am stuck thinking …..

in a world where war was not a foundation, what would have been a natural or dominant model for leadership?
do we lack leaders because we have leaders - because of our history?
do we love the idea of leaders more than we love leaders?
do we have leaders because of a broken model for accountability and responsibility?
do we like leadership because it is not us leading?
do we find it easier to be critical than be criticised?
is leadership sustainable?
if care for our natural world was our only job, what would leadership look like?

A problem of definitions in ecomimcs that create conflicts

noreply@blogger.com (Tony Fish) — Tue, 19 Jul 2022 10:00:00 +0000

A problem of definitions

As we are all reminded of inflation and its various manifestations, perhaps we also need to rethink some of them. The reason is that in economics, inflation is all about a linear scale. Sustainable development does not really map very well to this scale. In eco-systems, it is about balance. Because of the way we define growth - we aim for inflation and need to control it. However, this scale thinking then frames how we would perceive sustainability as the framing sets these boundaries. What happens if we change it round?

What we have today in terms of the definition that creates conflicts and therefore has to ask, is this useful for a sustainable future as we are trying to fit a square peg in a round hole.

Economics	Definition	Perceptions from the Sustainability community and long term impact
Hyperinflation	Hyperinflation is a period of fast-rising inflation; an Increase in prices drives for more efficiency to control pricing. Use of scale to create damp effects. Use global supply to counter effects.	Rapid and irreparable damage
Inflation	Inflation is the rate at which the overall level of prices for various goods and services in an economy rises over a period of time. Drives growth which is an increase in the amount of goods and services produced per head of the population over a period of time.	Significant damage and changes to eco-systems and habitat
Stagnation	Stagflation is characterised by slow economic growth and relatively high unemployment—or economic stagnation—which is at the same time accompanied by rising prices (i.e., inflation). Stagflation can be alternatively defined as a period of inflation combined with a decline in the gross domestic product (GDP).	Unstable balance but repairable damage possible
Recession/ deflation	Deflation is when prices drop significantly due to too large a money supply or a slump in consumer spending; lower costs mean companies earn less and may institute layoffs.	Stable and sustainable
Contraction	Contraction is a phase of the business cycle in which the economy is in decline. A contraction generally occurs after the business cycle peaks before it becomes a trough.	Expansion of the ecosystem and improving habitats

Perhaps what we need/ want if we want to remove the tensions from the ideals of growth and have a sustainable future.

Sustainable development		Economics
Unstable balance and damage creates change		Rapid growth
Out of balance, but repairable damage possible		Unco-ordinated growth
Stable and sustainable	Requires a lot of work and investment into projects to maintain stability and sustainability. Projects are long-term and vast. Requires global accord and loss of intra-Varlas protections. No sovereign states are needed as must hold everyone accountable.	Growth but without intervention would not be sustainable
Expansion of ecosystem and improving habitats	Goldilocks zone - improving quality of life and lifestyles but not at the expense of reducing the habitual area on the earth.	Slow growth in terms of purity of economics and GDP measurements.
Stable and sustainable	Requires a lot of work and investment into projects to maintain stability and sustainability. Projects are long-term and vast. Requires global accord and loss of intra-Varlas protections. No sovereign states are needed as must hold everyone accountable.	Shrinking and without intervention would not be sustainable
Out of balance, but repairable damage possible		Unco-ordinated decline
Unstable balance and damage creates change		Rapid decline

Mind the Gap - between short and long term strategy

noreply@blogger.com (Tony Fish) — Thu, 07 Jul 2022 11:31:00 +0000

Mind the Gap

This article addresses a question that ESG commentators struggle with: “Is ESG a model, a science, a framework, or a reporting tool? Co-authored @yaelrozencwajg and @tonyfish

An analogy. Our universe is governed by two fundamental models, small and big. The gap between Quantum Physics (small) and The Theory of Relativity (big) is similar to the issues between how we frame and deliver short and long-term business planning. We can model and master the small (short) and the big (long), but there is a chasm between them which means we fail to understand why the modelling and outcomes of one theory; don’t enlighten us about the other. The mismatch or gaps between our models create uncertainty and ambiguity, leading to general confusion and questionable incentives.

In physics, quantum mechanics is about understanding the small nuclear forces. However, based on our understanding of the interactions and balances between fundamental elements that express small nuclear forces, we cannot predict the movement of planets in the solar system. Vice versa, our model of gravity allows us to understand and predict motion in space and time, enabling us to model and know the exact position of Voyager 1 since 1977, which does not help in any way to understand fundamental particle interactions. There remains a gap between the two models, which is marketed as “The Theory of Everything” it is a hypothetical, singular, all-encompassing, coherent theoretical framework of physics that thoroughly explains and links together all physical aspects of the universe - it closes the gaps as we want it to all be explainable.

In business, we worked out that based on experience, probability, and confidence, using the past makes a reasonable predictive model in the short term (say the next three years), especially if the assumptions are based on a stable system (maintaining one sigma variance). If a change occurs, we will see it as a delta between the plan and reality as the future does not play out as the short-term model predicted.

We have improved our capabilities in predicting the future by developing frameworks, scenario planning and game theory. We can reduce risks and model scenarios by understanding the current context. The higher level of detail and understanding we have about the present, the better we are able to model the next short period of time. However, whilst we have learnt that our short-term models can be representative and provide a sound basis, there is always a delta to understand and manage. No matter how big and complex our model is, it doesn't fare well in with a longer time horizon as short-term models are not helpful for long-term strategic planning.

Long-term planning is not based on a model but instead on a narrative about how the active players' agency, influence and power will change. We are better able to think about global power shifts in the next 50 to 100 years than we can perceive what anything will look like in 10 years. We bounded by Gates Law “Most people overestimate what they can achieve in a year and underestimate what they can achieve in ten years.”

For every view of the long-term future, there is a supporting opinion. There is an alternative view of the future for every opinion, and neither follows the short-term model trajectory.

There is a gap between the two models; (small and big)/ (short and long). The gap is a fog-covered chasm that we have so far failed to address how to cross using models, theories or concepts from either the short- or long-term position. In this gap, where the fog-filled chasm exists, this zone demands critical thinking, judgement and leadership. The most critical aspects of modern humanity's ability to thrive sit in this zone: climate, eco-systems, geopolitics, global supply chains, digital identity, privacy, poverty, energy and water.

ESG has become the latest victim stuck in the foggy chasm.

ESG will be lost if we couldn’t agree now to position it as both a short-term model and a long-term value framework. ESG has to have an equal foot in each camp and requires a simple linear narrative which connects the two, avoiding getting lost in the foggy chasm that sucks the life out of progress that sites between them.

ESG as a short-term model must have data with a level of accuracy for reporting transparently. However, no matter how good this data is or the reporting frameworks, it will not predict or build a sustainable future.

ESG demands a long-term framework for a sustainable future, but we need globally agreed policies, perhaps starting from many UN SDG ideals. How can we realistically create standards, policies and regulations when we cannot agree on what we want the future to look like because of our geographical biases. We know that a long-term vision does not easily translate into practical short-term actions and will not help deliver immediate impact, but without a purpose, north star and governance, we are likely to get more of the same.

If the entire ESG eco-system had only focussed on one (short or long), it would have alienated the other, but right now, I fear that ESG has ended up being unable to talk about or deliver either. The media has firmly put ESG in the foggy gap because it is the best for its advertising-driven model. As a community, we appear unable to use our language or models to show how to criss-cross the chasm. Indeed our best ideas and technologies are being used to create division and separation. For example, climate technologies such as “carbon capture and storage models” had long-term thinking in the justification. Still, it has become a short-term profit centre and tax escape for the oil and gas extraction industries. "The Great Carbon Capture Scam" by Greenpeace does a deep dive on the topic.

As humans, we desperately need ESG to deliver a long-term sustainable future, but this is easy to ignore as anyone and everyone can have an opinion. Suppose ESG becomes only a short-term deliverable, and reporting tool, it is likely to fail as the data quality is poor and there is a lack of transparency. Whilst the level of narrative interruption is one that marketing demands, we will likely destroy our habitat before we acknowledge it and end up in the next global threat.

Repeating the opening question. “Is ESG a model, a science, a framework, or a reporting tool?” On reflection, it is a fair question as ESG has to be all. However, we appear to lack the ability to provide clarity on each element or a holistic vision for unity. Just in ESG science alone, there is the science that can be used to defend any climate point of view you want. Therefore, maybe, a better question is, “Does ESG have a Social Identity Crisis?” If so, what can we do to solve it?

Since:

there is no transparency about why a party supports a specific outcome, deliverable, standard or position;
the intrinsic value of ESG is unique by context and even to the level of a distinct part of an organisation;
we cannot agree if ESG investors are legit;
we cannot agree on standards or timeframes;
practitioners do not declare how or by whom they are paid or incentivised;
And bottom line, we have not agreed on what we are optimising for!

Whilst we know that we cannot please everyone all of the time, how would you approach this thorny debate as a thought leader?

Predator-prey models to model users

noreply@blogger.com (Tony Fish) — Thu, 09 Jun 2022 09:11:00 +0000

Predator-prey models are helpful and are often used in environmental science because they allow researchers to both observe the dynamics of animal populations and make predictions as to how they will develop/ change over time.

I have been quiet as we have been unpacking an idea that with a specific data set, we can model user behaviour based on a dynamic competitive market. This Predator-prey method, when applied to understand why users are behaving in a certain way, opens up a lot of questions we don’t have answers to.

As a #CDO, we have to remain curious, and this is curious.

Using the example of the rabbit and the fox. We know that there is a lag between growth in a rabbit population and the increase in a fox population. The lag varies on each cycle, as does the peak and minimum of each animal. We know that there is a lag between minimal rabbits and minimal foxes, as foxes can find other food sources and rabbits die of other causes.

Some key observations.

The cycles, whilst they look similar, are very different because of externalities - and even over many time cycles where we end up with the same starting conditions, we get different outcomes. Starting at any point and using the data from a different cycle creates different results; it is not a perfect science even with the application, say Euler's method, or bayesian network models. Indeed we appear to have divergence and not convergence - between what we expect and what we see, even with the actual reality showing that over a long time, the numbers remain within certain boundaries.

Each case begins with a set of initial conditions at a certain point in the cycle that will produce different outcomes for the function of the population of rabbits and foxes over a long period (100 years) - or user behaviours.

This creates a problem, as the data and models look good in slide form, as we can fix one model into a box that makes everyone feel warm and fuzzy. With the same model and different starting parameters - the outcome does not marry the plan. Decision-making is not always easier with data!

As a CEO

How do you test that the model that is being presented flexes and provides sensitivity to changes and not wildly different outcomes? It is easy to frame a model to give the outcome we want.

Great leadership is about knowing what to optimise for & when.

noreply@blogger.com (Tony Fish) — Fri, 20 May 2022 05:43:00 +0000

I participated in a fantastic talk in May 2022 on “Ideological Polarization and Extremism in the 21st Century” led by Jonathan Leader Maynard who is a Lecturer in International Politics at King's College London. The purpose here focuses on a though I took from Jonathan's talk and his new book, “Ideology and Mass Killing: The Radicalized Security Politics of Genocides and Deadly Atrocities,” published by Oxford University Press.

When I started thinking about writing about Peak Paradox, it was driven by a desire to answer a core question I asked myself, individuals, boards and teams; “what are we/ you optimising for?” . It has become my go-to question when I want to explore the complexity of decision making and team dynamics as the timeframe (tactical vs strategic) is determined by the person answering the question. Ultimately individuals in a team, which give the team its capabilities, are driven by different purposes and ideals, which means incentives work differently as each person optimises for different things in different ways in different time frames.

Nathalie Oestmann put up this post with the diagram below, talking about communication and all having the same message. My comment was that if you want stability this is good thinking, if you need change it will be less so as it will build resistance. If you want everyone to have the same message then again this is helpful thinking, but, if you need innovation alignment is less useful. When we all optimise for one thing and do the same thing - what do we become? A simple view is that 91 lines in the final idea becomes one as we will perpetuate the same, building higher walls with confimative incentives, feedback loops and echo chambers to ensure that the same is defensible.

What we become, when we optimise for one thing was also set out by Jonathan in his talk. He effectively said (to me) that if you optimise for one thing, you are an extremist. You have opted that this one thing is (or very few things are) more important than anything else. We might *not* like to think of ourselves as extremists but it is in fact what we are when we optimise for a single goal. Natalie’s post confirms that if you have enough people optimizing, for one thing, you have a tribe, movement, power, and voice. The very action of limiting optimisation from many to single creates bias and framing.

Extremism can be seen as a single optimisation when using Peak Paradox

Bill George wrote supporting the 24-hour rule from this INC article, essentially, whatever happens, is good or bad, you have 24 hours to celebrate or stew. Tomorrow, it’s a new day. It’s a good way to stay focused on the present. The problem is that this optimising appears good at one level but to improve leadership decision making and judgement skills, moving on without much stewing or celebrating removes critical learning. Knowing when to use the 24-hour is perfect, to blanket apply is probably a less useful rule. Leadership needs to focus on tomorrow's issues based on yesterday's learning whilst ensuring surviving today, to get to tomorrow.

So much about what we love (embrase/ take one/ follow) boils ideas down to a single optimisation. Diets, games, books, movies, etc.. Is it that we find living with complexity and optimising for more than one thing difficult or exhausting, or that one thing is so easy that we given our energy retention preference there is a natural bias to simplification? Religion and faith, politics, science, maths, friends family and life in general however requires us to optimise for opposing ideas all the same time, creating tensions and compromises.

Implication to boards, leadership and management

For way-to-long, the mantra for the purpose of a business was to “maximise the wealth for the shareholders.” This was the singular objective and optimisation of the board and instruction to management “maximise profits.” We have come a little way since then, but as I have written before, the single purity of Jenson and Mecking's work in 1976 left a legacy of incentives and education to optimise for one thing ignoring other thinking such as Peter Drucker’s 1973 insight that the only valid purpose of a firm is to create a customer, which itself has problems.

We have shifted to “optimsing for stakeholders” but is that really a shift on the peak paradox framework or a dumbing down of one purpose, one idea, one vision? A movement from the simple and singular to a nuanced paradoxical mess? Yes it is a move from the purity of “shareholder primacy” but does it really engage in optimising for the other peaks on the map? What does become evident is that when we move from the purity of maximising shareholder value is that decision making becomes more complex. I am not convinced that optimising for all stakeholders really embraces the requirement for the optimising for sustainability, it is a washed out north star where we are likely to deliver neither.

Here is the issue for the leadership.

Optimising for one thing is about being extreme. When we realise we are being extreme it is not a comfortable place to be and it naturally drives out creativity, innovation and change.

The pandemic made us focus on one issue, and it showed us that when we, irrespective of industry, geography and resources had to focus on just one thing we can make the amazing happen. Often sited is the 10 years of progress in 10 months, especially in digital and changing work patterns. However, we did not consider the tensions, compromises or unintended consequences, we just acted. Doing one thing, and being able to do just one thing is extreme.

Extreme is at edges of the peak paradox model. When we move from optimising for one thing to a few things we struggle to determine which is the priority. This is the journey from the the edges to the centre of the peak paradox model. When we have to optimise for many things we are at Peak Paradox. We know that optimising for many trends is tiring and the volume of data/ information we need for decision making increases by the square of the number of factors you want to optimise for. It is here that we find complexity but also realise that we cannot optimise or drive for anything. Whilst living with complexity is a critical skill for senior teams, it is here that we find that we cannot optimise and we appear to a ship adrift in a storm being pulled everywhere, with no direction or clarity of purpose. A true skill of great leadership is about knowing what to optimise for & when. Given the ebbs and flows of a market, there is a time to dwell and live with complexity optimising for many but knowing when to draw out, provide clarity, and optimise for one thing is critical.

The questions we are left to reflect on are:

how far from a single optimisation do your skills enable you to move?
how far from a single optimisation do your team's collective skills enable you to collectively move?
when optimising for conflicting purposes, how do you make decisions?
when optimising for conflicting purposes, how does the team make collective decisions?

When we finally master finding clarity to optimise for one thing and equally living with the tensions, conflicts and compromises of optimising for many things; we move from average to outperforming in terms of delivery and from decision making to judgment.

Great leaders and teams appear to be able to exist equally in the optimisation for both singular and complex purposes at the same time.

This viewpoint suggests that when the optimisation is for a singular focus, such as a three-word mission and purpose statement that provides a perfect clarity of purpose, is actually only half the capability that modern leadership needs to demonstrate.

Will decision making improve if we understand the bias in the decision making unit?

noreply@blogger.com (Tony Fish) — Wed, 23 Mar 2022 20:09:00 +0000

As a human I know we all have biases, and we all have different biases. We expose certain biases based on context, time, and people. We know that bias forms because of experience, and we are sure that social context reinforces perceived inconstancy. Bias is like a mirror and can show our good and bad sides.

As a director, you have to have experience before taking on the role, even as a founder director. This thought-piece asks if we know where our business biases start from and what direction of travel they create. Business bias is the bias you have right now that affects your choice, judgment and decision making. Business bais is something that our data cannot tell us. Data can tell me if your incentive removes choice or aligns with an outcome.

At the most superficial level, we know that the expectations of board members drive decisions. The decisions we take link to incentives, rewards and motivations and our shared values.

If we unpack this simple model, we can follow (the blue arrows in the diagram below) that says your expectation builds shared values that focus/highlight the rewards and motivations (as a group) we want. These, in turn, drives new expectations.

However, equally, we could follow (the orange arrows) and observe that expectations search and align with rewards and motivations we are given; this exposes our shared values that create new expectations for us.

Whilst Individual bias is complex; board or group bias adds an element of continuous dynamic change. We have observed and been taught this based on the “forming storming norming performing” model of group development first proposed by Bruce Tuckman in 1965, who said that these phases are all necessary and inevitable for a team to grow face up to challenges, tackle problems, find solutions, plan work, and deliver results.

The observation here is that whilst we might all follow the Tuckman ideals of “time”; in terms of the process to get to perfroming, of which there is lots of data to support, his model ignores the process of self-discovery we pass through during each phase, assuming that we align during the storming (conflicts and tensions) phase but ignore that we fundamentally have different approaches. Do you follow the blue of orange route and from where did you start.

This is non-more evident than when you get a “board with mixed experience”, in this case, the diversity of experience is a founder, family business and promoted leader. The reason is that if you add their starting positions to the map, we tend to find they start from different biased positions and may be travelling in different directions. Thank you to Claudia Heimer for stimulating this thought. The storming phase may align the majority round the team but will not change the underlying ideals and biases in the individuals, which means we don’t explose the paradoxes in decision making.

What does this all mean? As a CDO, we are tasked with finding data to support decisions? Often leadership will not follow the data, and we are left with questions. Equally, some leaders blindly follow the data without questioning it. Maybe it is time to collect smaller data at the board to uncover how we work and expose a bias in our decision making.

Ethics, maturity and incentives: plotting on Peak Paradox.

noreply@blogger.com (Tony Fish) — Wed, 23 Feb 2022 16:18:00 +0000

Ethics, maturity and incentives may not appear obvious or natural bedfellows. However, if someone else’s incentives drive you, you are likely on a journey from immaturity to Peak Paradox. A road from Peak Paradox towards a purpose looks like maturity as your own incentives drive you. Of note, ethics change depending on the direction of travel.

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In psychology, maturity can be operationally defined as the level of psychological functioning one can attain, after which the level of psychological functioning no longer increases with age. Maturity is the state, fact, or period of being mature.

Whilst immature is not fully developed or has an emotional or intellectual development appropriate to someone younger, I want to use the state of immaturity, which is the state where one is not fully mature.

Incentives are a thing that motivates or encourages someone to do something.

Peak Paradox is where you try to optimise for everything but cannot achieve anything as you do not know what drives you and are constantly conflicted.

Ethics is a branch of philosophy that "involves systematising, defending, and recommending concepts of right and wrong behaviour". Ethical and moral principles govern a person's behaviour.

The Peak Paradox framework is below.

When we start our life journey, we travel from being immature to mature. Depending on your context, e.g. location, economics, social, political and legal, you will naturally be associated with one of the four Peak Purposes. It might not be extreme, but you will be framed towards one of them (bias). This is the context you are in before determining your own purpose, mission or vision. Being born in a place with little food and water, there is a natural affinity to survival. Being born in a community that values everyone and everything, you will naturally align to a big society. Born to the family of a senior leader in a global industry, you will be framed to a particular model. Being a child of Murdoch, Musk, Zuckerberg, Trump, Putin, Rothschild, Gates, etc. - requires assimilation to a set of beliefs.

Children of celebrities break from what the parents thinking, as have we and as do our children. Politics and religious chats with teenagers are always enlightening. As children, we travel from the contextual purpose we are born into and typically head towards reaching Peak Paradox - on this journey, we are immature. (note, it is possible to go the other way and become more extreme in purpose than your parents.) Later in life and with the benefits of maturity, we observe this journey from the simplicity of binary choices (black and white ethics) towards a more nuanced mess at Peak Paradox. At Peak Paradox, we sense a struggle to make sense of the different optimisations, drivers, purposes, incentives, rewards that others have. This creates anxiety, tension and conflict within us. During this journey from a given purpose to Peak Paradox, the incentives given to you are designed to maintain the original purpose, to keep you following that ideal. Incentive frame and keep us in a model which is sometimes hard to break.

It is only when we live with complexity and are able to appreciate others' purposes, optimisations, and drivers that we will also gain clarity on our own passion, purpose or mission. By living with Peak Paradox, we change from being driven by others' incentives to uncovering our own affinity; this is where we start to align to what we naturally believe in and find what fits our skin.

I have written before that we have to move from Peak Paradox towards a purpose if we want to have clarity of purpose and achieve something.

Enter Ethics

Suppose maturity is the transition from our actions being determined by others and following their ethical or moral code to determining what type of world or society we want to be part of. In that case, we need to think about the two journeys.

On the route from birth to Peak Paradox, I have framed this as a route from immaturity to living with complexity. On the route in, we live by others' moral and ethical codes and are driven by their incentives. As we leave Peak Paradox and head to a place where we find less tension, conflicts and anxiety, which has a natural affinity to what we believe, and we create our own moral and ethical compass/ code and become driven by our own motivations.

We should take a fresh perspective on ethics and first determine which direction someone is heading before we make a judgement. This is increasingly important in #cyberethics and #digitalethics as we only see the point and have no ability to create a bearing or direction.

The purpose of Peak Paradox

As maturity heads towards being mature, we move in and out of living at Peak Paradox from different “Purposes” I am sure this is an iterative process. The purpose of Peak Paradox is to be in a place where you are comfortable with complexity, but it is not a place to stay. It is like a holiday home, good to go there now and again, but it does not represent life. The question we have is how do we know when we are at Peak Paradox, probably because our north star has become a black hole! The key message here is that some never escape the Peak Paradox black hole, finding they live in turmoil driven by others' incentives that are designed to keep you there) and never finding their own passion, incentive or motivation. The complexity death vortex is where you endlessly search for a never reachable explanation of everything as it is all too interconnected and interdependent to unravel. Leaders come out from Peak Paradox knowing why they have a purpose and a direction.

The Journey

Imagine you are born into a celebrity household, over time you see the world is more complicated, you work for a company believing that money bonuses and incentives matter. Over time you come to understand the tensions such a narrow view brings. You search for something better, committing to living a simpler life, changing your ethics and moral code. This still creates tension, and you search for peace and harmony, where you find less tension and more alignment; when you arrive there, you have a unique code because you live with complexity and understand different optimisations. It does not scale, and few can grasp your message.

Where are you on the journey?