Notions

Identity

2005-12-22T02:26:00.000Z

Is identity a thing?

Some people talk about identity as some special kind of object - a valuable possession that can be stolen by fraudsters (identity theft), appropriated by authority (e.g. government), and/or captured in some technological device (database, smartcard).

Some people say we have exactly one of these things, while others say we may have several different identities (corresponding perhaps to different social contexts). Some of us may have a cluster of overlapping but not-quite-consistent identities.

Some people say identity is a permanent fixture, while others say it can develop over time.

Identity may be fractured into technological bits. For example, Phil Windley describes identity in terms of "a collection of attributes, preferences, and traits stored in a computer record". He contrasts this (as he puts it) "dry technical definition of identity" with "the living language of identity" mooted by Tim Greyson. Perhaps the computer record is merely an impoverished representation of a living identity.

But perhaps it isn't a thing after all ...?

Is identity a function or process?

In my 1992 book on Information Modelling, I argued (following Frege) that identity was a special kind of rule, defining when something could be regarded as the same again. This notion of identity is invoked by Johann Ernst and Scott Lemon.

A company identifies me using a relatively small set of characteristics. If a fraudster manages to replicate these characteristics, then he can impersonate me for fraudulent ends. If the company is unable to detect the impersonation, then the fraudster and I are (at least temporarily) indistinguishable.

One way of making sense of this is to say that there are at least two different identity functions in play here. The bank's identity function answers YES when asked if the fraudster and I are the same; my own identity function answers NO. From my perspective, the bank's error counts as a false positive, caused by inadequate information.

In general, such identity functions are epistemological rather than ontological. They are about what a company knows (or chooses to know, or is permitted to know) about a data subject, rather than the intrinsic nature of the data subject himself.

And importantly, whereas ontological identity obeys all sorts of simple logic (excluded middle, transitivity), epistemological identity (indistinguishability) doesn't.

Is identity a policy?

This kind of identity is not stable, because it depends on the company's policy - what it chooses to know about me. It also depends on my own preferences - what I am willing to divulge to the company - for example whether I choose to participate in loyalty schemes or frequent flyer programmes. In some industries, there are also regulatory concerns - for example, banks have been forced to increase the amount they know about their customers, and this is apparently to counter money-laundering.

From this perspective, the question of biometric identity is not whether two people are theoretically indistinguishable, but whether anyone can be bothered to spend enough money to make the technology sufficiently accurate. (See discussion on the Ultimate Biometric by Neils A Bjergstrom (pdf), Stefan Brands and Kim Cameron.)

... more later

Life Cycle

2005-10-28T11:39:00.000+01:00

It might seem obvious, but the word "cycle" means going round in a loop. In biology, this means the cycle of birth, reproduction and death. In business, talking about product lifecycles or technology lifecycles carries the expectation that every instance of PRODUCT or TECHNOLOGY has a finite life expectancy, and will be replaced by something else.

But there are two common misuses of the word lifecycle. In the first misuse, people say "cycle" but mean something else. This is illustrated by Gartner's concept of the Hype Cycle, which is not even drawn as a cycle, but as a curved graph going from left to right. See discussion in my Software Industry Analysis blog.

In the second misuse, the concept of cycle is used inappropriately. This is illustrated by a Disaster Lifecycle found on the FEMA website. This appears to show each instance of DISASTER producing new instances of DISASTER.

(via Presentation Zen)

(Of course the ongoing purpose of FEMA assumes a continuous supply of fresh disasters, just as rat-catchers rely upon a continuous supply of rats, but it is really bad PR for FEMA to imply that they are helping to create the disasters they are supposed to be managing.)

The Presentation Zen blog suggests that "Perhaps FEMA would have been better advised to show the stages in a more linear way?" and refers to product adoption lifecycles being presented in left-to-right manner. But the problem (both here and elsewhere) is not just that a given concept has been inappropriately drawn, but that it was the wrong concept in the first place.

Attenuation

2005-10-11T13:29:00.000+01:00

A number of people have been talking about attenuation recently, and it links to some aspects of business intelligence I've been researching. When James Governor complained that the word was geeky, and asked why we couldn't just use the word filtering, I thought I should try to answer him.

I think the important difference is this. Attenuation is an outcome (black box), whereas filtering is a mechanism (white box). Filtering generally involves some device or subsystem (hardware, software, clerical or hybrid) that performs a filtering function - letting some items through and not others. Although it is possible in complex systems for filtering to happen by accident, and it is certainly possible for filtering devices to perform incorrectly, the filter is an architectural pattern that is normally implemented as a deliberate design decision.

In contrast, attenuation simply means that some data or information are just not getting through. This can occur as an emergent effect of the interactions within a large complex system, without being specifically located anywhere. It may be deliberate or accidental, it may be predictable or random. Filtering is certainly one possible mechanism for achieving attenuation, but there are many other possible causes of attenuation including distance or impedance mismatch. Simple aggregation also produces attenuation, and this has led some people (I think misleadingly) to bundle the two concepts. (See for example O'Reilly).

When I am looking at a complex system or organization, I can often start with the observation that attenuation is happening, but without knowing where or how. I infer attenuation when I see a system that is failing to respond to significant events in its environment, or when I see systems that cannot coordinate properly.

In some cases, of course, this inferred attenuation leads to the discovery of a specific filter - perhaps a communication channel has got blocked, or adapted for some local purpose that conflicts with the objectives of the whole system. But often the root cause is not the presence of a filtering mechanism but the absence or inadequacy of a communication mechanism. Or even a fundamental incompatibility between different systems or viewpoints.

Attenuation is often a desirable effect - particularly when dealing with information overload or complexity overload. Matt Webb praises maps, and points out that "the taking of a position in a landscape of information flow" produces attenuation. (Thus attenuation is a necessary consequence of perspective.) IT architects practise two forms of attenuation in particular - Modelling and SeparationOfConcerns.

Modelling is a form of conceptual attenuation - reducing a complex situation to an abstract model.
SeparationOfConcerns is a form of parallel attenuation - creating a series of simpler views of a complex situation.

However, there are many situations where attenuation needs to be overcome: I want more detail / context in the data than I'm being given. When attenuation occurs in my system, I may be able to get inside the system to detect and alter the causes of the attenuation. Matt Webb describes these as algorithms, and advocates "co-production of the algorithms with the people who sit in the information flows".

This is fine when it's available - but it usually isn't. Because sometimes the attenuation is happening in someone else's system. So I have to find a way to amplify the data I can get access to - using statistical inference to deconstruct aggregations and reconstruct detail and context - which help to connect and explain the attenuated fragments of data that are available. A lot of what happens under the heading of Business Intelligence can be understood as a form of archaeology - piecing together patterns of market behaviour from large quantities of extremely attenuated data.

Finally, I should acknowledge that James is not alone in equating attenuation with filtering. Stafford Beer uses the term attenuator as if it were equivalent to filter, and his Viable Systems Model (VSM) describes variety attenuators as if they were devices for filtering out complexity. And yet he says: "The lethal variety attenuator is sheer ignorance." and it is hard to see ignorance as a filter. [See this presentation on VSM by Trevor Hilder (pdf).]

My dear James, if you think that attenuation is geeky, you should try implicature. (Sources: Matt Webb, Lloyd Shepherd.) Perhaps someone could explain to me how this usefully differs from either framing or perspective. (See also Brian M Dennis.)

Bezzle

2005-05-17T01:10:00.000+01:00

The economist J.K Gailbraith used the term "bezzle" to denote the amount of money siphoned (or "embezzled") from the system. In good times, he remarked, the bezzle rises sharply, because everyone feels good and nobody notices. "In [economic] depression, all this is reversed. Money is watched with a narrow, suspicious eye. The man who handles it is assumed to be dishonest until he proves himself otherwise. Audits are penetrating and meticulous. Commercial morality is enormously improved. The bezzle shrinks." [Galbraith, The Great Crash 1929]

Bezzle can be interpreted to cover a range of ethical crimes and misdemenours - from outright corruption and fraud to self-interested self-deception and greed.

Bezzle Theory

Galbraith's idea that bezzle oscillates with the economic cycle can be elaborated into a prototype theory, which may do the following

explain some recent phenomena
illustrate some important behaviour patterns of complex systems
support some tentative predictions

Example - Split Cap Scandal

Few of the people who sold split capital investments as "low risk" were capable of exposing the dodgy mathematics that supposedly underpinned the sector - so they may have a reasonable claim to have been acting in good faith, based on prevailing knowledge.

We need to take a particular perspective in order to interpret such scams as bezzle. Bezzle depends on clear notions of legitimacy, which are lacking in many situations.

Chris Flitwick, who was at the centre of the split capital scam, has argued that the split caps were originally low risk, and that it was the investment practices of the fund managers that turned them into high risk. This raises some interesting risk management and trust issues - if events and changing management practices turn a low risk into a high risk, is there a duty of trust to notify all stakeholders that the risk profile has changed and give them an opportuity to reconsider their investment/involvement, or is there a duty of trust to mantain the original risk profile and bear the difference?

Meanwhile apparent wealth acts as an attractor - so gullible investors and intellectually lazy or cynical brokers rush towards get-rich-quick schemes. (This is perhaps an example of Gresham's law - bad money driving out good.)

Galbraith would surely argue that this phenomenon is itself dependent on the economic cycle - acting strongly at some times and very weakly at other times. Galbraith's theory is interesting from an epistemological perspective, because it suggests that bezzle is higher when it is unobserved (unobservable), and lower when it is observed. While this is intuitively plausible, it is scientifically problematic - because it cannot be tested through observation.

These theories provide ways of making sense of recent activity - especially the flurry of activity around corporate governance and "ethical" acccounting standards. Based on these theories, we can predict that the energy behind this activity will subside as economic conditions improve. Doubtless many stakeholders will be counting on this.

Corporate Governance

In the past few years, the level of public trust in accounts and accountants has been severely damaged. Some executives have evidently stolen from their shareholders for years, without any demur from the auditors. Other accounts have had to be restated, thanks to gross systemic error. Papers and reputations have been shredded, executives have been jailed or disgraced, large firms have collapsed, and stock markets around the world have taken a cold bath.

There are undoubtedly many accountants and auditors who perform a dedicated and thorough job, carefully checking the accounts of their clients, and investigating inconsistencies and anomalies; but it has become apparent that the traditional auditing system is no longer able to deliver adequate guarantees of reliability and honesty in corporate accounts.

Part of the problem is the sheer complexity of corporate accounting dataflows. Let's suppose your accounts are based on data output from one or more ERP packages, and exported into Excel for the final consolidation. Mix in some data from a few dozen legacy systems, sprinkle with currency conversion and actuarial calculations, and bake in a hot spreadsheet for a manic Year-End panic. Mistakes are inevitable, and not even the smartest auditor has much chance of spotting them. Cynical executives and conniving accountants may deliberately cook the books, but even honest executives cannot guarantee the results.

The US Sarbanes-Oxley Act of 2002 (SOX) mandates what is effectively a systems engineering solution to this problem. Reliability is achieved not by human oversight alone, but by a set of information and control systems that ensures information quality and management accountability. Executive officers are required to sign the accounts and are criminally liable for any inaccuracy. The act also mandates near-real-time disclosure of any material events.

In the past, reliability was equated with the moral character of the directors and auditors. Nowadays, reliability must be seen as an engineering problem.

Business Organization Management: Moral Bankruptcy
SOAPbox: Compliance and Control
POSIWID: Gas Bezzle
CBDI Report April 2004: Sarbanes-Oxley Drives Web Services Adoption

Reuse or Repurpose

2005-05-06T11:30:00.000+01:00

The software world has spent many years talking about reuse, especially in the context of Component-Based Software Engineering (CBSE). Reuse is linked to the economics of scale/scope, and is supposedly associated with a range of benefits including the productivity of development and maintenance.

But as the focus shifts from components to services, the word "reuse" doesn't quite reflect the opportunity. To my mind, the word never made quite as much sense for services as it did for components.

A number of commentators are now using the word repurpose instead of reuse. (PCMag, Zapthink)

A lot of discussion of repurposing seems to be largely about altering the format of information to suit different devices, channels or media. Such discussion is popular in the publication/syndication world, with reference to RSS and repurposing content for internet distribution. It is also relevant for transmitting content to a complex array of new devices such as mobile phones.

Dynamic Content Repurposing for Mobile Phones (Connection Software)
DeBabelizer for Repurposing Digital Assets (Equilibrium Technologies)

I don't deny the technical challenge of reformatting, but to my mind the more interesting aspects of repurposing is where there is a significant variation in the context of use. What is the (end-user) purpose that may be served by the content? For example, see this discussion Repurpose or Perish from 1998, which raises some of these issues:

the users' choice of how they want to get this information and how frequently they want it
users adopting different ways of reading/scanning material on-line (lean-forward versus lean-back)

Repurposing Data and Services

For a humorous definition of repurposing, see Buzzwords for Nerds.

Technorati Tags: repurpose reuse service-oriented XML

Off-Label

2005-03-16T13:58:00.000Z

In a pharmaceutical context, Off-Label refers to uses of drugs that are not approved by the regulators and cannot therefore be printed on the product label or officially promoted by the drug company. More generally, it refers to any unauthorized or emergent use of a product or service.

From the regulatory point of view, off-label is not merely unapproved but (at least to some extent) disapproved, and subject to secondary regulation.

But off-label usage is apparently increasing. This raises several questions which I shall raise in separate blog postings. [Update: links added]

Innovation	The technological leading edge is often/always off the label.
Knowledge and Uncertainty	Off-label usage is disseminated by informal knowledge mechanisms ("samizdat").
Trust	On-label and off-label usage rely on different trust mechanisms.
Service-Based Business	There is a critical asymmetry between on-label and off-label, which must be accommodated in the geometry of services.

Identity Theft

2005-01-10T09:21:00.000Z

Identity theft is usually defined in terms of the impersonation of individuals for criminal purposes.

See for example the recent report on Identity Theft published by the US Federal Deposit Insurance Corporation (December 14th, 2004).

However, phishing typically starts with a criminal attempt to impersonate a financial institution. Thus organizations can also suffer identity theft. See Paul Brown's blog posting, The Identity Problem is Symmetric.

However, financial institutions deal with the problem in a highly asymmetric way. Banks and other financial services companies don’t appreciate the customer’s need for security - they think security is about protecting them from us! Asymmetric Trust fits into a more general theory I have about Asymmetric Demand.

I got so fed up with “courtesy calls” that asked me to identify myself before they would even tell me what they were trying to sell me, that I blogged about this last year.

Finance Industry View of Security. See also further material on Identity and Security.

UPDATE: Technorati Tags: asymmetry identity-theft

Collaborative Composition

2005-01-01T18:45:00.001Z

There is a fundamental clash between two modes of software production. Based on the Boxer Model of Collaborative Composition, we characterize these modes as Clockwise and Anticlockwise.

The anticlockwise mode of software production starts with Domain Knowledge, and is dominated by the economies of scale/scope. Software engineering has traditionally been dominated by anticlockwise thinking.

The clockwise mode starts with Cases, and is dominated by providing a situated response to the specifics of the demand ecosystem. One version of this is known as Situated Software, which refers to software designed in and for a particular social situation or context.

Situated Software

2004-12-29T01:21:00.000Z

Software designed in and for a particular social situation or context. Clay Shirky explains how this works in practice, with some examples taken from his class at NYU. See discussion here, including sceptical comment by Lucas. See also comments by James Governor.

Situated software resists the traditional software engineering pressure towards generalization, and apparently disregards the economics of scale/scope. Instead it works solely within a collaborative socio-technical system (the "community"); the conditions for the success of the software (including meaning and trust) are co-created by the members of the community.

One of the earliest forms of situated software was the spreadsheet. Power users built themselves complicated structures using Visicalc or Lotus 123 or Excel. These were essentially non-transferable artefacts with many hidden assumptions, but they served a useful purpose within a given context.

This illustrates the fact that situated software is assisted by the existence of tools and platforms that provide generalized support for situated software. This is one interpretation of the software factory idea.

In the Boxer Model of Collaborative Composition, situated software appears to be a clockwise-dominant process, contrasting with the anticlockwise-dominant processes of traditional software engineering.

Related Concepts: Situated Action (Lucy Suchman). Situated Software Architecture (P Taylor).

Bearing Limit

2004-11-24T09:34:00.000Z

"Bearing limit" refers to the amount of cost or uncertainty a person or organization (or any other component of a distributed system) can contain or can be expected to bear. (Uncertainty here may include risk, surprise, instability or variability.)

Between 1994 and 1996, a stand-off emerged between two speculators. Yasuo Hamanaka, Sumitomo's chief copper trader, was long on copper. Julian Robertson, of the Tiger Fund, was short on copper.

By mid 1995, Robertson un-owned about $1bn-worth of copper. Robertson was convinced copper was over-priced, but the price was still rising. Other speculators (notably Soros Fund Management) bailed out and took their losses. Robertson held on.

By spring 1994, Hamanaka probably owned about $10bn-worth of copper. When this was discovered, the price of copper fell 30%. Tiger made $300m in one day. Sumitomo lost billions. History refers to this incident as the Sumitomo copper scandal (and not the Tiger copper coup).

Alistair Blair reviews the story in his weekly column. "Mr Hamanaka ... couldn't squeeze any more copper trade tickets into the bottom right hand drawer of his desk, where he had been accumulating them for two years in an attempt to recover losses ... think of Nick Leeson times three". In contrast, "Mr Robertson ... was not betting his bank. He had conviction and self-belief, but he also had discipline. ... He could remain solvent for as long as it took." (Investor's Chronicle No Free Lunch, 19 November 2004)

Rogue traders such as Hamanaka and Leeson exceed their bearing limits, and may damage or destroy their respective organizations. Meanwhile, Robertson remained well inside his bearing limit.

Of course markets are irrational. Sometimes rogue traders get away with it; sometimes disciplined speculators lose out. But distributed risk management (not just in financial trading but in a wide range of domain) always demands attention to bearing limits.

We introduced the term "bearing limit" into our risk management practice following the Nick Leeson scandal and the fall of Barings Bank. (The pun is deliberate.) More recently, the term "risk-bearing limit" was used in a Sept 2001 paper Reflections on New Financial System in Japan (pdf). We have also started to apply the term to questions of knowledge and intelligence. (See weblog post on Bearing Limit and WMD).

Any given party has a bearing limit, which defines how much cost and risk it can bear. Above this limit, the party cannot be expected to contain the costs and risks allocated to it, and these may spill over the contractual boundaries to its partners. In the worst case, a party unable to bear its costs and risks goes into liquidation, and the remaining costs and risks then have to be picked up by another party. (Think about PFI and the possible demise of Jarvis.)

In some cases, the bearing limit can be determined fairly precisely. This is particularly true in cases that are covered by various forms of indemnity insurance, since the bearing limit can be taken to be equal to the level of insurance cover. In other cases, the bearing limit is itself a matter for negotiation.

Within a hierarchical organization, there is a bearing limit at each level of the management hierarchy. In other words, there is a maximum level of responsibility that can be delegated downwards. Above this limit, the responsibility remains with upper management. (For example, if a trading bank loses half a billion dollars, this cannot be blamed solely on a rogue trader with an authorization limit of 50 million dollars. To pretend otherwise is either foolish or corrupt.)

Design by Contract

2004-09-01T13:30:00.000+01:00

Design by Contract was pioneered by Bertrand Meyer, who refined the assertion-based approach into the Design by Contract method and the Eiffel language. The basic idea is that a component and its clients have a contract with each other. The client guarantees certain preconditions before calling a method, the component guarantees certain postconditions after the call. If the pre- and postconditions are included in a form that the compiler can check, then any violation of the contract between caller and component can be detected immediately. The prime focus of the approach is to deliver reliable software.

Design by Contract has wide theoretical acceptance. It is an intrinsic component of the Catalysis Approach, perhaps the most influential of all component methodologies. However its usage has to date been relatively limited, the most prevalent use being in the Eiffel language.

CBDI Report Eiffel in the .NET Environment October 2002 (restricted access)

In business terms, the basis for collaboration between autonomous business entities is a service contract. This suggests a design process in which contracts are paramount - such as Design by Contract.

For distributed collaborations, a contract between provider and consumer needs to have three parts: logical, quality and commercial.

The logical contract specifies the function of the Service, typically using a series of logical assertions such as preconditions and postconditions. This includes both syntactic elements (signature) and semantic elements (vocabulary, meaning).

The quality contract specifies the quality of service - often given the rather dismissive label of non-functional characteristics.

The commercial contract specifies the commercial arrangements, including charging for normal operation and compensation for abnormal operation.

Design by Contract allows services to be defined and used without knowing anything about the implementation. It therefore seems ideally suited to the design of web collaborations. Design by Contract has traditionally concentrated on the logical contract, but the same principles and related design techniques can be extended to the quality contract and the commercial contract.

The term "web service contract" is sometimes used in the very narrow sense of the syntax/signature of the service call, as expressed in WSDL/XML. Much of the recent discussion on Contract-First Development seems to be focused on these aspects of the contract.

For example, Simon Guest regards Contract-First Development as an alternative to Data-First Development (which he prefers).
See also Aaron Skonnard blog on Contract-First Development (August 2004) with many comments
Eric Newcomer (Description First, September 2004) points out that for Web services, the purpose is to share data over the network. Therefore the Schema is more correctly viewed as the contract, not the WSDL.

Design by Contract has a broader concept of contract, which explicitly includes the semantics of the service call in terms of pre/postconditions and invariants, but against a single semantic vocabulary.

Web services will be implemented in a range of formal languages and protocols. These will not only specify the syntax of the service (e.g. using WSDL/XML) but also the semantic vocabulary (e.g. using RDF or DAML-S) and the pragmatics (e.g. using BPEL). However, these languages do not yet cover the full ground of quality contracts and commercial contracts. In the short term, these aspects of the contract are likely to be covered by legal contracts and SLAs between service providers and consumers. Some vendors refer to this broader notion of contract as the Relationship Contract. Some service management tools include such characteristics within the service repository as metadata.

CBDI Newswire 22nd May 2003 and 28th May 2003 (free access).
CBDI Reports From Web Services to Web Collaborations (Nov 2002) and Modelling for SOA (Feb 2003) (restricted access).
See my blog entry on BPEL (September 2004)

Leaky Abstraction

2004-08-31T12:00:00.000+01:00

Joel Spolsky's Law of Leaky Abstraction:

All non-trivial abstractions, to some degree, are leaky.

Technologies (Joel talks specifically about code generation tools) are generally supposed to abstract out something. They create a separation (decoupling) between some abstract service at one level, and some technical code or mechanism at another level.

But all abstractions leak, and the only way to deal with the leaks competently is to learn about how the abstractions work and what they are abstracting. So the abstractions save us time working, but they don't save us time learning.

See note on Automation and Skill

So decoupling is never as clean as it should be, and we should always expect hidden coupling and feature interaction.

See note on Simplicity and Complexity

The Law of Leaky Abstraction is related to the belief that symbolization (standardization or formalization) is necessarily imperfect, always leaves holes (something to be desired, the invasion of the Real). Complexity, often seen as part of the solution, merely adds to the problem.

Asymmetry

2004-08-09T22:28:00.000+01:00

Many enterprises are managed on a false assumption of symmetry.

War and Peace
Traditional armies assumed that their principal enemies were also traditional armies. This assumption was shaken by insurgency and guerilla and is completely irrelevant to the war against terror. Hence the modern interest in asymmetric warfare.

Traditional diplomacy focused on the relationships between nation states, represented by the political establishment within each state. These states has peer-to-peer relationships, and also participated in various international bodies.

Enterprise
Traditional enterprises assumed symmetry between supply and demand. But this symmetry typically suppresses the real demands of the support economy.

General Notes on Asymmetry, Asymmetric Trust, ...

Information Asymmetry: Labelling as Service
Asymmetry of Demand: Business Geometry

asymmetry@del.icio.us
asymmetry@technorati

Power to the Edge

2004-08-07T16:07:00.001+01:00

cross-posted to AsymmetricDesign blog

Power to the edge is about changing the way individuals, organizations, and systems relate to one another and work.

empowerment of individuals at the edge of an organization
adoption of an edge organization, with greatly enhanced peer-to-peer interactions.
moving senior personnel into roles that place them at the edge

Power to the edge is being presented in the military domain as the correct response to increased uncertainty, volatility, and complexity. Clearly these factors also apply to civilian enterprises, both commercial and public sector.

Carole Eigen and Philip Boxer presented on this topic at the ISPSO Symposium in Baltimore in June 2005 (paper).

Military use of the term comes from a book by David S. Alberts and Richard E. Hayes, Power to the Edge: Command … Control … in the Information Age. June 2003. Published by CCRP. PDF version available online (1.7 MB).

See John Stenbit statement. See also presentation material by Dr Margaret Myers. Power to the Edge Through Net Centricity - Transformation of the Global Information Grid Text (html) Slides (pdf).

Groove (acquired by Microsoft in March 2005 - see my commentary) always liked this concept (for reasons that should be obvious) - see blogs by Ray Ozzie (now offline) and Michael Helfrich. See also blogs by Doug Simpson and Nathan Wallace.

I found a weblog rant here to the effect that Power to the Edge is all about speeding up information flow, just another name for Reengineering. In my view, this is a fundamental misunderstanding. Obviously Power to the Edge may call for improved flow of information: quality and complexity as well as quantity and speed. But Power to the Edge is not the improved flow itself but what it enables - which is a fundamental transformation in the geometry of the organization away from a hierarchical command-and-control structure. And such structures are still as common in civilian/commercial organizations as in the military, if not more so.

Further comment: Demise of the Super Star, Governance at the Edge.

Tethering

2004-08-02T01:32:00.000+01:00

Tethering is the creation of a dependence (tight coupling, binding) by a supplier, in a situation where a consumer may have a reasonable expectation of independence (loose coupling, zero coupling).

Example 1. RealNetworks has recently launched a service to download music onto Apple iPods. Apple regards this as an invasion of its tethering. The blogs I read are generally supportive of RealNetworks.

Siva Vaidhyanathan The Trouble with Tethering
Ernie the Attorney Reverse Engineering

Example 2. It is alleged that some brands of printer automatically reduce print quality when they detect third-party ink cartridges.

Example 3. Off-shore software developers may put in unauthorized coupling between software modules/components, in order to increase subsequent maintenance revenues.

Tethering represents a clash between the supplier's view of the world and the consumers' view. (We call this Asymmetric Demand.) Sometimes it stems from a deliberate plan to exploit a commercial position or from bloodymindedness. But sometimes the supplier feels that the position is morally defensible and in the best interests of consumers (if they but knew it.) Surely iTunes provides all the flexibility and functionality anyone could want??

Clinical Validation

2004-07-02T00:52:00.000+01:00

crossposted to TrustBlog

Hypotheses are checked not against impersonal trials of their adequacy but against testimonials, case studies and assessments of success made by parties with a stake in their outcome.

Frederick C. Crews, Out, Damned Blot! New York Review July 15 2004

Drug companies only publish the results of favourable trials. Some people argue they should be forced to publish all results, whether favourable or otherwise. However, this could simply cause the drug companies to engineer the trials more carefully in advance, to reduce the risk that the trials might reveal anything inconvenient to their commercial agenda.

Marcia Angell, The Truth About the Drug Companies, New York Review July 15 2004

Transference

2004-06-18T23:48:00.000+01:00

cross-posted to Leadership and Change blog

Within psychoanalytic theory, there has been a great deal written about the phenomenon of transference, where the client uses the relationship with the therapist to replace something else, and becomes as it were addicted to the therapy/therapist. A related phenomenon also occurs with management consultancy.

Psychoanalytic Definition

Trust and Transference

Transference Among People Online

Metaphor as Transference

Fractal Loading

2004-06-18T14:30:00.000+01:00

Fractal loading means that each high-level exchange also carries with it simultaneous exchanges on many smaller levels, and implies the coexistence of different but related things at different levels of scale.

The opposite case of monofunctional planning forces many separate and competing exchanges of the same type into a single communications channel, thus maximizing the capacity of uniform communications channels dedicated to a single type of exchange. An example of this is a choked highway, or the overloading of subway cars at rush hour. Not only is this inefficient, but it excludes other types of exchange.

[source: Information Architecture of Cities, Coward & Salingaros]
See also Phil Jones wiki

Customer relationship management illustrates the alternative between fractal loading and monofunctional planning. A call centre or other customer-facing operation may aspire to identify additional products and services to sell to customers. But this conflicts with a series of aspirations related to the efficiency and speed of a single transaction type – e.g. maximum throughput, minimum transaction times, and minimum queueing time.

Management-by-walking-around (MBWA) is an appeal to fractal loading. Knowledge management and trust benefit from fractal loading.

Fractal loading represents a major challenge to traditional bureaucratic assumptions about information processing and management. It helps us understand why traditional approach can never deliver adequate levels of adaptability.

Stress

2004-06-14T06:12:00.001+01:00

Stress affects all sorts of outcomes, including biological fertility and workplace productivity.

There are many observable symptoms of stress - both in individuals and in organizations.

Stress is itself often a symptom of some underlying problem. Sometimes one of the most destructive things we can do is alleviate or suppress the symptoms of individual stress, while ignoring the organizational or social context that generates this stress.

More discussion on my website.