March 2023 – Collective IQ

Daniel Kahneman and Richard Thaler are both Nobel Prize winners in Economic Sciences¹ and they want you to change the way you manage. This is because there are two things afflicting your organisation that you don’t realise are costing you dearly – in their words these are ‘Noise’ and ‘Sludge’.

‘Noise’ is Kahneman’s term, and it refers to all those extraneous things that can affect human judgement but have no logical bearing on the issue at hand. As he puts it, “The problem is that humans are unreliable decision makers; their judgments are strongly influenced by irrelevant factors, such as their current mood, the time since their last meal, and the weather. We call the chance variability of judgments ‘noise’. It is an invisible tax on the bottom line of many companies.”²

He explains that noise is distinct from bias, which exists more as a permanent filter on judgements rather than a random factor. The way noise taxes the bottom line is that it causes significant variations in decisions. Imagine that you are a customer and you inadvertently request estimates from two employees in the same company for the same thing. They then reply with substantially different estimates. This actually happened according to Kahneman, and of course the horrified customer decided that the best alternative was a competitor.

‘Sludge’, on other hand, is a somewhat different but equally pernicious hidden influence. Sludge is Thaler’s word for any aspect of your organisational environment that hinders a person from taking the better course of action, or it may even actively steer them into a poor choice.

The overall circumstance in which a person makes a choice is called the “decision architecture”, and it is something that can be shaped for good, or for bad, by design or default. Sludge is any part of the architecture that fails to help with good choices or actively steers people toward bad ones. In Thaler’s words, “Sludge … is nasty stuff that makes it more difficult to make wise choices”³.

The solution, of course, is to remove both sludge and noise from decision making. But how? In the case of sludge, the answer is to replace it with ‘nudge’. A nudge is a change to the decision architecture that helps a person to act in the best way and make better choices. Nudges often involve rethinking processes to simplify them, personalise them, or make them easier and more efficient, or all of these things. And nudging happens automatically when decision makers are provided with better knowledge and understanding of the intricacies and implications of the tasks they face.

Reducing noise requires a similar approach, with the main aim being to achieve accurate and consistent professional judgements. Kahneman states that research shows that noise typically causes variations in professional assessments of up to 50% (with instances as high as 70%). Removing noise reduces this to a much more tolerable, and less damaging, 5-10%. Part of his solution is to “adopt procedures that promote consistency by ensuring that employees in the same role use similar methods to seek information, integrate it into a view of the case, and translate that view into a decision.”

So, for any given task or issue, the way forward is for those involved to:

Rethink it in nudge terms
Agree consistent methods, so as to eliminate noise
Subscribe and commit to those methods, and share the associated knowledge
Jointly monitor outcomes and variability
Based on outcomes, go back to 1 and repeat

This five-step approach builds consistency and capability. It also lays solid groundwork for developing effective algorithms for automated methods, which are Kahneman’s preferred ultimate solutions. He states, “Replacing human decisions with an algorithm should be considered whenever professional judgments are noisy, but in most cases this solution will be too radical or simply impractical.” In support of this he argues that “People have competed against algorithms in several hundred contests of accuracy over the past 60 years, in tasks ranging from predicting the life expectancy of cancer patients to predicting the success of graduate students. Algorithms were more accurate than human professionals in about half the studies, and approximately tied with the humans in the others. The ties should also count as victories for the algorithms, which are more cost effective.”

But the caveats on automated algorithms are serious. They must be developed and implemented with extreme care, and never without close human oversight and gatekeeping. Inaccurate assumptions, flawed methods, inadequate input data, and general haste to jump to a “silver bullet” solution, (especially when highly paid external consultants are involved) can be absolutely disastrous – the most egregious examples being Australia’s Robodebt debacle⁴ and The Netherland’s welfare fraud and child benefits scandals⁵ (the latter brought down the government).

In short, noise and sludge are real, and nudges and noise reduction are proven paths to improved performance. But achieving this is not easy. Fundamentally, it requires commitment, knowledge sharing, and cooperation. And algorithms will be most effective, and least likely to be harmful, when they are an extension of these things and always kept transparently within their control.

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¹ Kahneman in 2002 and Thaler in 2017

² “Noise: How to Overcome the High, Hidden Cost of Inconsistent Decision Making”, by Daniel Kahneman, Andrew M. Rosenfield, Linnea Gandhi, and Tom Blaser, Harvard Business Review, October 2016

³ ”Nudge: The Final Edition”, by Richard H Thaler and Cass R Sunstein, Penguin Books, 2021

⁴ “The Robodebt fiasco has been laid bare at royal commission hearings”, ABC News, 4 March 2023

⁵ “This algorithm could ruin your life”, by Matt Burgess, Evaline Schot, And Gabriel Geiger, WIRED Magazine, 6 March 2023

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Onno van Ewyk is a Knowledge Management Consultant and author of the book Raising an Organisation’s Collective IQ.

Have you ever heard of DITA? Outside a small community of specialist technical communicators, most people have never heard of this acronym. Which is a shame because, when applied in the right way, it can save an organisation millions of dollars. How? By significantly improving the way organisational knowledge is captured and communicated. It makes knowledge capture faster and easier, and it produces an end result that is both easier and quicker for people to assimilate and apply. Employees work more effectively, and new appointments get up to speed much faster.

DITA stands for Darwin Information Typing Architecture, which is not exactly self-explanatory, but its cleverness becomes obvious when you consider its output – called a ‘topic’. A topic is “a title and content short enough to be specific to a single subject or answer a single question, but long enough to make sense on its own and be authored as a unit”ⁱ. In other words, a compact packet of useful information.

So how will this save millions? The simple answer is by replacing policy, procedure, and instruction documents. These classically rigid and bureaucratic documents, often written more with an eye to lawyers and regulators than employees, can hinder more than they help. Their orientation often tangles the business up unnecessarily in red tape and complicates issues in ways that are counterproductive to their intent. Policies end up as just words on a page with little impact on behaviours and culture, and useful instructions are lost in overblown paragraphs of passive prose.

Topics, on the other hand, orientate policies, procedures, and instructions to the employee’s needs. Short, sharp, and to the point (single subject, answer to a single question), they are not only far more effective but also easier to maintain and keep up to date.

Moreover, topics are created and maintained within an ecosystem called a DITA Map. This is a nested hierarchy of categories that are aligned with the business. They ensure that topics are relevant, comprehensive (i.e., covering all important processes), and easily located. The DITA Map provides an overall framework in which topics are related to each other. It creates a knowledge map that employees can use to explore knowledge resources productively, rather than having to blunder through the usual ad-hoc folksonomies found on file servers and Intranets.

The DITA approach is Darwinian in that units of information (topics) live and die within their use-environment according to their practical value. Topics are also adapted to a particular overall context (your business) and are potentially each related to one another (implemented via contextual hyperlinks).

‘Information Typing’ means that DITA topics can come in various flavours, the key ones being ‘Concept’, ‘Task’, and ‘Reference’. You can think of policies as being ‘concepts’, procedures and instructions as ‘tasks’, and everything else as ‘references’, but there is no need to get too hung up on these distinctions. Being this fine-grained is only useful when working with detailed technical information that is published in multiple formats from a single source. In a general business context, the greatest utility comes from restricting topics to a single subject or answer to a single question.

The A for Architecture in DITA, however, is critical. Architecture means not only a clear structure in which policy, procedure, and instructional information makes sense and supports your value chains, but also a commitment to quickly changing that structure as business needs change. In fact, the A in DITA could quite comfortably stand for Adaptation – and what could be more Darwinian than that.

Onno van Ewyk is a Knowledge Management Consultant and the author of the book Raising an Organisation’s Collective IQ

Month: March 2023

Noise, Nudge, and Sludge – These Nobel prize winners want you to change how you manage

CEOs! An acronym you have never heard of could save you millions