According to Cathy O’Neil in her book Weapons of Math Destruction [1] a mathematical model is nothing more than a simulation of the world that often models blind spots reflecting the judgement and priorities of its creators.

e.g. a product myopic organization [2] would not become anything else by applying algorithms, artificial intelligence or machine learning. It would only become more myopic.

It’s relevant to ask: why is the organization making the decisions it does? At the MIT System Dynamics Group they are saying:

We believe any individual is making the best possible decision based on the information they have available — James Paine, MIT, paraphrasing [3]

They are pointing to the information available as the key enabler of decisions.

With advanced analytics the organization could reach new information, new mental models, new types of sense-making. It could understand the world differently and make new hypotheses about what leads to progress. It could train models to test its assumptions in order to open up new worlds of untapped wealth — or close them before they do damage.

The motive of the data driven organization should not be to accelerate or make more efficient the existing biases and opinions of the organization (continuing in the same direction only faster and cheaper) ..

The promise is to help the organization make sense of the world in ways it never could before.

To better understand what the world looks like through other lenses — outside existing bubbles (e.g. through context, relationships, environment, culture). To broaden and diversify its field of view. To lower the cost of experimentation so that any wild assumption can be tested (if you are not experimenting to be surprised you are underutilizing your potential for learning). To be more humble, understand the company is not at the center of the customer’s consciousness, but sometimes only a tiny part of it. To help it have impact in a system where it has no control, but can hopefully assert some modest influence.

The goal of any organization should be to use the gift of the computer to reach somewhere they’ve never been, somewhere previously unreachable or even unknowable — not to accelerate in the direction it is already going (unless they are already perfect?).

Sources:

1. Weapons of Math Destruction, https://www.penguinrandomhouse.com/books/241363/weapons-of-math-destruction-by-cathy-oneil/
2. Marketing Myopia, Theodore Levitt, https://hbr.org/2004/07/marketing-myopia
3. System Dynamics: Systems Thinking and Modeling for a Complex World, James Paine, https://www.youtube.com/watch?v=o-Yp8A7BPE8

Are we trying to hard or not hard enough? In our quest to make the world data driven and quantifiable are we producing new problems? Are we so eager to make the world into a programmable sequence (algorithm) that we exclude the parts that make us sentient [able to perceive or feel things]? Meaning: if we want the computer to do all our work do we have to become computers?

In the book “Why the world needs anthropologists” (2) Dan Podjed, Meta Gorup, Pavel Borecky and Carla Guerrón Montero invite 11 anthropologists to share their stories about why now more than ever the world needs “cultural relativism, ethnography, comparison and context” (3).

All quotes below are from the introduction by Dan Podjed and Meta Gorup and the first article by Thomas Hylland Eriksen (the complete book is a gold mine).

“The world does not consist of straightforward facts and quantifiable models alone” — Thomas Hylland Eriksen, professor of social anthropology at the University of Oslo, Norway, p.9

“Embracing multiperspectivity, suspending judgement, acknowledging the fluidity of life and the importance of various inner and outer dimensions, answer big questions by studying very concrete phenomena [..] by listening to people’s stories.” — On Joana Breidenbach, serial entrepreneur, p.10

“Nolan is critical of the current interpretations of reality which are predominantly guided by numbers. To understand human diversity and complexity [..] we need to acknowledge the importance of context” — On Riall W. Nolan, Professor of anthropology at Purdue University, USA p.13

“It is impossible to address and resolve the pressing global issues merely by looking at numbers, statistics, figures and diagrams. Anthropology [.. enables] the collection of ‘thick data’ — in addition to ‘big data’ — and sheds a different light on a certain problem, helping us understand the world we live in more comprehensively” — On Christian Madsbjerg, ReD Associates p.13

“Anthropologists [..] are concerned with context, relationships and connections. The smallest unit that anthropologists study is not the isolated individual but the relationship between two people and their environment. Whereas the society is a web of relationships, culture , as activated between sentient bodies, not inside them, is what makes communication possible. To a great extent, we are constituted by our relationship with others, which produces us and gives us sustenance, and which confirms or challenges our values and opinions” — Thomas Hylland Eriksen, Ethnography in all the right places, why the world needs anthropologists

“Anthropologists resist simplistic accounts of human nature and accept that complex realities tend to have complex causes.” — Thomas Hylland Eriksen, Ethnography in all the right places, why the world needs anthropologists p.22

“He who speaks no foreign language knows nothing about his own” — Goethe p.24

“Make it as simple as possible, but not simpler” — Albert Einstein, page 22

Resources:

1. Kevin Slavin, https://youtu.be/9Goa1Y9OBHU
2. Why the world needs anthropologists, https://www.routledge.com/Why-the-World-Needs-Anthropologists/Podjed-Gorup-Borecky-Montero/p/book/9781350147133
3. Thomas Hylland Eriksen, Why the world needs anthropologists

Nobody knows the answer to any of these questions which are most likely multiple and changing all the time (1).

One way to set strategy is open, broad statements that can fit a lot of change in them, another is experimentation.

With experimentation the strategy becomes active. It’s not a stone tablet the company chisels out once a year and has to commit to no matter how inaccurate or unimportant it might become.

Active means that it wants to learn and it pushes the organization to need to learn.

As an example: by combining the lean startup method (2) with riskiest assumptions testing (3) and business experimentation (4) the strategy can become living and inspiring (read more here (5) and here (6)). Not something to be measured against at the end of journey, but something to keep teams at speed, direction and engaged.

A strategy is not only there to make us goal oriented and focused, it’s there to energize and inspire new opportunities and ideas.

An active strategy that wants to learn never has to be 100% perfect. Because the immediate outcome of learning is change (if we don’t commit to what we learn we will only feel misguided). And so the mindset shifts from thinking you have to commit to the strategy for a year and spending 110% effort to build over-confidence (only to see the world change the next Monday), to an active learning strategy where your goal is to stay curious. To create a good enough springboard (decreasing the startup cost of strategy), leap into the learning journey and keep discovering.

Who said strategy had to be stale, broad and fixed? Why do we have to make strategy into a ceremony, an event? Why can’t strategy be a way-of-working? And why can’t continuous learning and experimentation fuel our strategy and keep the team energized and led by a strategy that is always as fresh as newly baked bread?

Resources:

(1) https://youtu.be/Miwb92eZaJg

(2) https://www.slideshare.net/tafkin/lean-startup-customer-development-with-javelin-board

(3) https://medium.com/hackernoon/the-mvp-is-dead-long-live-the-rat-233d5d16ab02

(4) https://hbr.org/2020/03/building-a-culture-of-experimentation

(5) https://medium.com/everything-new-is-dangerous/business-experimentation-f5620919f209

(6) https://bootcamp.uxdesign.cc/what-is-business-experimentation-2f96d573b0b0

the language that you speak shapes the way that you think. And that gives you the opportunity to ask, “Why do I think the way that I do?” “How could I think differently?” And also, “What thoughts do I wish to create?” — Lea Boroditsky (1)

We choose labels to describe the world and these labels shape the lenses through which we understand and act on the world. Boroditsky uses an example: if an accident where to happen an English speaker would focus on the perpetrator (who did it?) while a Spanish speaker on the intentions leading to the incident (why did it happen?).

This relates to how organizations choose to describe the world and particularly the common label customers. Are there really any customers?

If I am in the mattress making business labelling someone as a customer will describe their moment of purchase not their years of usage. What would be the best language to improve my products, innovate or direct my marketing? Why are people engaging with me and buying from me in the first place? Is it because they want to buy a mattress or because they want to use a mattress? What do they need from their sleep, cuddles, cozyness, mornings, rest that motivates them?

Our language and labels should help us access and take part in the main motivators and drivers through which people are using and enjoying (delighting in) our products. We need to see our products through the lens of their lives not see their lives through the lens of our products.

e.g. a physician might describe to a patient a disease through the lens of the illness. “..these are the effects of the illness on smell, breathing or joints …” While a patient will try to understand the illness through the lens of his life: “What will my future look like, will I be able to go on runs with my wife, meet my colleagues at the office, hug my kids, sleep etc.”

Very few companies should have customers. As it reflects the moment of purchase. It reflects a wallet with a body attached to it. And the intention of any product is not to be sold, it’s to be used and enable desired outcomes.

A few of my own guides to identify a better language:

1. How would they describe the situation they are in?
2. What are they trying to achieve, what are their desired outcomes?
3. What label would a person use to describe themselves given 1 and 2

“It would be an act of mere reductionism to think of these people as mere users — as operators that need to be taken care of” — Anthropologist Rikke Ulk (2)

Sources:

 (1) How language shapes the way we think, TED, https://www.ted.com/talks/lera_boroditsky_how_language_shapes_the_way_we_think

(2) Why the World Needs Anthropologists, https://www.appliedanthro.org/publications/news/november-2020/why-world-needs-anthropologists

According to Christian Madsbjerg & Sarah Heatherington what thin or “big” data “lacks is one simple thing: a connection to our subjective experience or the way that we, as people, actually understand the world. Without this — the subjective frame of individual and cultural experience — the big data approach can only deliver “thin data”, or numbers stripped of any richer contextual meaning. If business leaders really want to understand the complexity of the world, they need to pair their use of big data with “thick data” or data that richly captures the human experience.” (1).

We can measure a channel or a website using thin data. Because it is just a piece of technology, functionality, code. It doesn’t think about a daughter’s wedding, SAT scores or a business opportunity. In fact, it doesn’t think at all. That is why we can reduce measuring it down into something as simple as number, a performance metric. So we can understand it in comparison to the context-less job it has?

But when we are reducing human beings into mere operators in our engagements we are erasing their complexity — we are taking away their individual and cultural experience which is their motivation for making decisions in the first place.

To quote anthropologist Rikke Ulk: “It would be an act of utter reductionism to think of these people as mere ‘users’ — as actors that need to be taken care of” (2).

I believe any organization can measure their ability to produce value for their customers which leads to a customer response that can be measured against value for the business. But it’s a. most likely not a number like 32% or 14,8. OR it might be a number if it is built on the basis of qualitative research or experimentation identifying what is valuable to the complex human being — if that insights can be translated into a measurable quantity (3).

Sources:

(1) https://www.dukece.com/insights/thin-data-new-framework-understanding-world/

(2) https://www.appliedanthro.org/publications/news/november-2020/why-world-needs-anthropologists

(3) https://hbr.org/2020/04/the-most-important-metrics-youre-not-tracking-yet

You can do this by taking a step back and asking “what leads this to happen?”. E.g. If you are trying to understand the design of a car engine, then the cylinder head, piston or crankshaft might be less important. These are elements of the engine, they are the result of the engine having to solve something that is pushing at it from the outside. And you might find yourself looking more at things like the thermo dynamics of fuel, different demands based on if it’s a race car or a family car or local government regulations.

When trying to design a system to represent something like why you are selling more or less of your products. If you find the way you are organized, your revenue model, products or features as central components in your system you might be designing an echo-system of yourself rather than trying to understand the bigger ecosystem you are a part of.

You are usually not the center of the system, you are only one part of it (and sometimes you are not even a part of it). But, if your systems map is to narrow you might find it describes you more than the bigger picture (and I would advise to take a step back).
 
 Powers of ten, Eames, https://youtu.be/0fKBhvDjuy0

A big part of systems thinking is drawing out peoples’ mental models to connect different ways of seeing the world in the same structure. This allows us to test and learn from simulation and feedback how the bigger system works, uncover behaviors and outcomes one person or a few might have missed.

Paine suggest that to draw out another persons mental model is like walking up to them and saying:

“I know the decisions you are making are the best decisions to make based on the information you have right now. I want to know why. I want to build a model of your mental process that when we run it and I look at it it makes complete sense. And then take that model and pop it into the context of a larger system to study how those decisions are coming back and affecting the outcome.”

At MIT’s System Thinking group this mindset is so fundamental that on a board in their group room the following is written:

“We believe that everyone in this community is intelligent and capable, cares about doing their best, acts with integrity, and wants to learn.”

(The lecture in the video below starts at 11min)

1. Stay humble. We can’t control the environment we are in, but we can try to understand it, keep up with it and hopefully be able to influence some of it. A customer way-of-thinking trains you on understanding the influence the environment and culture has on the organization and the influence the organization has back — as one of many forces of influence (a simple system map can easily identify 30-50 forces of influence on any environment). It keeps you humble to what you can achieve — and because of this also get better at finding where to operate, what to prioritize and how to influence.

2. It’s the outcomes. A customer way-of-thinking doesn’t see the world through the lens of what the company outputs, but the influence and impact it creates. This doesn’t mean it only sees outcomes. It sees the whole organization as an organism optimized for better outcomes. It can even be enabler agnostic taking a broad perspective in exploring and suggesting how to reach the desired outcomes, even as these keep changing.

3. Be curios. In a complex environment there is always more than one answer and it keeps changing all the time. Keep learning and don’t fall in love with an idea if that means you won’t be able to keep challenging and changing it.

So, how do we measure our ability to do and improve this? It might be easier than you think..

In his 2020 article “The most important Metrics you are not tracking (yet)”Gene Cornfield, suggests to use Customer Performance Indicators (CPIs). These are compared to KPIs measures on our ability to produce value for the customer, compared to KPIs which measure our ability to get the customers to produce value for us.

But, how do you find the right CPIs?

There might be two approaches (there are most likely many):

1. Is our engagement producing value?

Using Outcome Driven Innovation (ODI) by Strategyn can help break down the customers’ jobs (what they are trying to do) into smaller desirable outcomes, finding which of these are aligned to your business and also could be set up as a quantitative real-time measures (e.g. in Cornfield’s article he references an insurance company using reduction in ‘time-through-sales-funnel’ as a quantitative measure for customer value which their qualitative research confirmed).

Measuring customer value down to the engagement level can give your team a direct line-of-sight between what they are doing and the customers. It also helps us make sure we can improve whats important to our customer in our engagements.

2. Are we helping the customer’s own progress?

According to jobs-to-be-done theory every customer hires products or services from because they have a need for progress to solve. Customers aren’t buying products just because someone is selling them. There is almost always an underlying unsatisfied need that the company is consciously or unconsciously tapping into. The question is: how good are your products or services at helping the customers do their job and and how can you improve?

Jobs-to-be-done helps organizations take a step back from it’s technology and functionality and look at their ability to produce progress for the customer from a broader perspective — it’s agnostic to what vehicle you are using to enable the customer to produce value. With technologies and customer demands changing every so often it can be important for the company to measure itself against something more stable and long term: the customers’ needs .. and have a measure that even incentives pivots if needed.

These are just two examples, of course. But hopefully it can be inspiring to find your own.

Sources:

.. on the other hand ..

“The Chinese believe in constant change. They pay attention to a wide range of events; they search for relationships between things; and they think you can’t understand the part without understanding the whole”.

Both these quotes are from Richard Nisbett’s book The Geography of Thought, exploring the the culture of thinking from East to West, the gulf between us and a blueprint to build a bridge. 

It’s a book to helps us better understand other cultures and to explore and understand our own. Thinking isn’t only thinking, you think the way you do because of your culture, upbringing, education and more…

Two more quotes from the book:

“.. Where the Greek saw a collection of persons with attributes that were independent of any connections with others. Complexity and interrelation meant for the Chinese that an attempt to understand the object without appreciation of its context was doomed. Under the best of circumstances control of outcomes was difficult.”

“The Chinese where right about the importance of the field to an understanding of the behavior of the object and they were right about complexity, but their lack of interest in categories prevented them from discovering laws that really are capable of explaining classes of events. And for all that the greeks tended to oversimplify and to be satisfied by pseudo-explanations involving non-existent properties of objects, they correctly understood that it was necessary to categorize objects in order to be able to apply rules to them”.

As the mid- and/or post-pandemic pressure ramps up on organizations it might become clear which organizations have been using their customer focus as a “slogan exercise” (Philip Gerskovich, Zebra Technologies (2)), where they have been “forced to care as other means of differentiation has been eroded” and which have a customer culture at their core (Ed Thompson, Gartner (3))

Corporate Rebels (4) published this short video on Haier the Chinese multinational home appliances and consumer electronics company, presenting one version of what it means to have the customer at the core (and not just as slogan).

From the video:

Under two main principles Haier, set out to reinvent itself in order to bring back motivation, entrepreneurship and speediness:

1. Zero distance to the customer – The aim to connect people directly to the customer

2. Everyone is an entrepreneur – Creating and acting a culture where every employee feels and acts as if they were entrepreneurs

This lead to a change in their organizational structure from one big bureaucratic hierarchical organization to a network of 4000 micro-enterprises centered around different types of customer demands. 

The micro enterprises fall into two categories:

A. The customer facing enterprises with direct contact with the customers (e.g. repair teams and web-shops)

B. The supporting teams selling their services to the customer facing teams indirectly supporting the customer (e.g. purchasing, manufacturing and marketing)

These enterprises form micro-communities or networks that share profit adapt or dissolve. 

This structure allows the organization to be constantly changing in response to customer requirements (= zero distance to the customer).

Sources:

(1) https://www.computerweekly.com/feature/How-companies-are-rethinking-digital-customer-experience-in-wake-of-pandemic

(2) https://hbr.org/sponsored/2016/04/advancing-the-customer-experience

(3) Computerweekly.com/feature/customer-experience-management-figures-as-way-to-stand-out [link no longer works]

(4) https://www.youtube.com/channel/UC7q3K7B7reV3lCz4N2xIDiQ

I have tested this, asking people in internal roles like e.g. administration and finance how they were offering value directly to their customers, and they were easily able to identify how their work was contributing valuable outcomes to their customers.

So what is a customer DNA?

Back in 2016 Aaron Dignan and The Ready published the OS Canvas it was a way to describe and understand the organization as an operating system.

The OS Canvas is “something that could take a complex system and make it a practical playground for imagining and implementing a new way of working.”

An updated version includes the following forces of influence on the organization:

Purpose — How we orient and steer

Authority — How we share power and make decisions

Structure — How we organize and team

Strategy — How we plan and prioritize

Resources — How we invest our time and money

Innovation — How we learn and evolve

Workflow — How we divide and do the work

Meetings — How we convene and coordinate

Information — How we share and use data

Membership — How we define and cultivate relationships

Mastery — How we grow and mature

Compensation — How we pay and provide

I immediately took a liking to the canvas because it makes clear the forces of influence on the organization and helps us decide which, why and how different forces need to be aligned with our customers to provide a healthy organization (healthy in terms of its outcomes and responsibility in the ecosystem).

To me the customer is not a marketing gimmick or a data point. It is a force of influence on the organization which used correctly can inspire, inform and shape several parts of a healthy company. Enabling it to keep up with the changing ecosystem and consistently provide the best possible outcomes at the right time.

A customer aligned organization could be said to have a customer DNA.

Demographics aren’t customers they are proxies. They expose us to biased assumptions about who (affluent, woman, 50-60yrs) wants what. But they don’t help us understand why they want it (or how). 

People aren’t motivated by who they are they are motivated by what they need. Customers don’t care about the artefacts companies are selling. What they want are the outcomes the objects help them achieve: people hire products and services from companies to enable behaviors that unlock their need for progress or help them overcome a struggle.

Knowing that Sarah is 56 years old is as irrelevant as knowing that her weight is 67kg. More helpful is knowing what she needs. How she makes decisions and how she measures her own success? This is jobs-to-be-done.

In her book Weapons of math destruction Cathy O’Neil talks about how we use mathematical models and proxies to simulate the world and make decisions.

A mathematical model is nothing more than a simulation of the world, it is a simplifications (they have to be), and often they are modeling a context based on data they don’t have .. so they use proxies.

Proxies are statistical correlations that make assumptions about what has a causal effect on something else (if A happens B will happen), but often we use proxies that are spurious at best — we don’t know that A has an effect on B. “A model’s blind spots reflects the judgements and priorities of it’s creators”

“Whether a model works or not is also a matter of opinion”, “models, despite their reputation for impartiality, reflect goals and ideology”.

But we need models, so how do we make them work for us? O’Neil suggests a few factors relevant for a model of any size or purpose:

• Transparency. Since every model is a reflection of someones values and ideas and many models uses proxies, the best way to make them work is to make them transparent so that everyone can participate in the evaluation and discussion of the assumptions the models make
• Dynamic. “That is how trustworthy models operate. They maintain a constant back-and-forth with whatever in the world they are trying to understand or predict. Conditions change and so must the model.”
• Clarity. [This is my own experience] A model must be very clear on what it is modeling and what it is not modeling. Don’t over-market it.

https://www.penguinrandomhouse.com/books/241363/weapons-of-math-destruction-by-cathy-oneil/

With learning comes demands. So do you really want to learn?

Here are a few things I’ve experienced the learning organization needs to want:

1. To commit to what you are learning whatever it is? What are you not prepared to commit to?

2. To be surprised? Learning is about breaking with your preconceived ideas. Do you want to spend time and resources testing something where you have no idea of the outcome?

3. To admit you don’t have all the answers? Are you willing to move forward without certainty?

4. To admit there is probably a better answer, you just haven’t found it yet?

5. To keep changing all the time? Or do you want to stay the course no matter what? What is your tipping point?

Learning includes feedback loops, openness and commitment. And these are hard. The most important question for a learning organization might be:

Do you really want to learn?

Because you really need to want to…