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The improbability of success

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Anyone who has tidied up after a toddler intuitively understands that making a mess is far easier than creating order. The fundamental reason for this is that the number of messy states in the universe (or a toddler’s room) far outnumbers the ordered ones.  As this point might not be obvious, I’ll demonstrate it via a simple thought experiment involving marbles:

Throw three marbles onto a flat surface.  When the marbles come to rest, you are most likely to end up with a random configuration  as in Figure 1.

Figure 1: A random configuration of 3 marbles

Indeed, you’d be extremely surprised if the three ended up being collinear as in Figure 2.   Note that Figure 2 is just one example of many collinear possibilities, but the point I’m making is that if the marbles are thrown randomly, they are more likely to end up in a random state than a lined-up one.

Figure 2: an unlikely (ordered) configuration

This raises a couple of questions:

Question: On what basis can one claim that the collinear configuration is tidier or more ordered than the non-collinear one?

Naive answer:  It looks more ordered. Yes, tidiness is in the eye of the beholder so it is necessarily subjective. However, I’ll wager that if one took a poll, an overwhelming number of people would say that the configuration in Figure 2 is more ordered than the one in Figure 1.

More sophisticated answer : The “state” of collinear marbles can be described using 2 parameters, the slope and intercept of the straight line that three marbles lie on (in any coordinate system) whereas the description of the nonlinear state requires 3 parameters. The first state is tidier because it requires fewer parameters.  Another way to think about is that the line can be described by two marbles; the third one is redundant as far as the description of the state is concerned.

Question: Why is a tidier configuration less likely than a messy one?

Answer:  May be you see this intuitively and need no proof, but here’s one just in case. Imagine rolling the three marbles one after the other. The first two, regardless of where they end up, will necessarily lie along a line (two points lie on the straight line joining them). Now, I think it is easy to see that if we throw the third marble randomly, it is highly unlikely end up on that line. Indeed, for the third marble to end up exactly on the same straight line requires a coincidence of near cosmic proportions.

I know, I know, this is not a proof, but I trust it makes the point.

Now, although it is near impossible to get to a collinear end state via random throws, it is possible to approximate it by changing the way we throw the marbles. Here’s how:

  1. Throw the marbles consecutively rather than in one go.
  2. When throwing the third marble, adjust its initial speed and direction in a way that takes into account the positions of the two marbles that are already on the surface. Remember these two already define a straight line.

The third throw is no longer random because it is designed to maximise the chance that the last marble will get as close as possible to the straight line defined by the first two. Done right, you’ll end up with something closer to the configuration in Figure 3 rather than the one in Figure 2.

Figure 3: an “approximately ordered” state

Now you’re probably wondering what this has to do with success. I’ll make the connection via an example that will be familiar to many readers of this blog: an organisation’s strategy. However, as I will reiterate later, the arguments I present are very general and can be applied to just about any initiative or situation.

Typically, a strategy sets out goals for an organisation and a plan to achieve them in a specified timeframe. The goals define a number of desirable outcomes, or states which, by design, are constrained to belong to a (very) small subset of all possible states the organisation can end up in.  In direct analogy with the simple model discussed above it is clear that, left to its own devices, the organisation is more likely to end up in one of the much overwhelmingly larger number of “failed states” than one of the successful ones.  Notwithstanding the popular quote about there being many roads to success, in reality there are a great many more roads to failure.

Of course, that’s precisely why organisations are never “left to their own devices.” Indeed, a strategic plan specifies actions that are intended to make a successful state more likely than an unsuccessful one. However, no plan can guarantee success; it can, at best, make it more likely. As in the marble game, success is ultimately a matter of chance, even when we take actions to make it more likely.

If we accept this, the key question becomes: how can one design a strategy that improves the odds of success?  The marble analogy suggests a way to do this is to:

  1. Define success in terms of an end state that is a natural extension of your current state.
  2. Devise a plan to (approximately) achieve that end state. Such a plan will necessarily build on the current state rather than change it wholesale. Successful change is an evolutionary process rather than a revolutionary one.

My contention is that these points are often ignored by management strategists. More often than not, they will define an end state based on a textbook idealisation, consulting model or (horror!) best practice. The marble analogy shows why copying others is unlikely to succeed.

Figure 4 shows a variant of the marble game in which we have two sets of marbles (or organisations!), one blue, as before, and the other red.


Figure 4: Two distinct configurations of marbles (or organisations)

Now, it is considerably harder to align an additional marble with both sets of marbles than the blue one alone. Here’s why…

To align with both sets, the new marble has to end up close to the point that lies at the intersection of the blue and red lines in Figure 5. In contrast, to align with the blue set alone, all that’s needed is for it to get close to any point on the blue line.

QED!

Figure 5: Why copying others is not a good idea (see text for explanation)

Finally, on a broader note, it should be clear that the arguments made above go beyond organisational strategies. They apply to pretty much any planned action, whether at work or in one’s personal life.

So, to sum up: when developing an organisational (or personal) strategy, the first step is to understand where you are and then identify the minimal actions you need to take in order to get to an “improved” state that is consistent with  your current one. Yes, this is akin to the incremental and evolutionary approach that Agilistas and Leaners have been banging on about for years. However, their prescriptions focus on specific areas: software development and process improvement.  My point is that the basic principles are way broader because they are a direct consequence of a fundamental fact regarding the relative likelihood of order and disorder in a toddler’s room, an organisation, or even the universe at large.

Written by K

April 4, 2017 at 9:16 pm

Uncertainty, ambiguity and the art of decision making

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A common myth about decision making in organisations is that it is, by and large, a rational process.   The term rational refers to decision-making methods that are based on the following broad steps:

  1. Identify available options.
  2. Develop criteria for rating options.
  3. Rate options according to criteria developed.
  4. Select the top-ranked option.

Although this appears to be a logical way to proceed it is often difficult to put into practice, primarily because of uncertainty about matters relating to the decision.

Uncertainty can manifest itself in a variety of ways: one could be uncertain about facts, the available options, decision criteria or even one’s own preferences for options.

In this post, I discuss the role of uncertainty in decision making and, more importantly, how one can make well-informed decisions in such situations.

A bit about uncertainty

It is ironic that the term uncertainty is itself vague when used in the context of decision making. There are at least five distinct senses in which it is used:

  1. Uncertainty about decision options.
  2. Uncertainty about one’s preferences for options.
  3. Uncertainty about what criteria are relevant to evaluating the options.
  4. Uncertainty about what data is needed (data relevance).
  5. Uncertainty about the data itself (data accuracy).

Each of these is qualitatively different: uncertainty about data accuracy (item 5 above) is very different from uncertainty regarding decision options (item 1). The former can potentially be dealt with using statistics whereas the latter entails learning more about the decision problem and its context, ideally from different perspectives. Put another way, the item 5 is essentially a technical matter whereas item 1 is a deeper issue that may have social, political and – as we shall see – even behavioural dimensions. It is therefore reasonable to expect that the two situations call for vastly different approaches.

Quantifiable uncertainty

A common problem in project management is the estimation of task durations. In this case, what’s requested is a “best guess” time (in hours or days) it will take to complete a task. Many project schedules represent task durations by point estimates, i.e.  by single numbers. The Gantt Chart shown in Figure 1 is a common example. In it, each task duration is represented by its expected duration. This is misleading because the single number conveys a sense of certainty that is unwarranted.  It is far more accurate, not to mention safer, to quote a range of possible durations.

Figure 1: Gantt Chart (courtesy Wikimedia)

Figure 1: Gantt Chart (courtesy Wikimedia)

In general, quantifiable uncertainties, such as those conveyed in estimates, should always be quoted as ranges – something along the following lines: task A may take anywhere between 2 and 8 days, with a most likely completion time of 4 days (Figure 2).

Figure 2: Task completion likelihood (3 point estimates)

Figure 2: Task completion likelihood (3 point estimates)

In this example, aside from stating that the task will finish sometime between 2 and 4 days, the estimator implicitly asserts that the likelihood of finishing before 2 days or after 8 days is zero.  Moreover, she also implies that some completion times are more likely than others. Although it may be difficult to quantify the likelihood exactly, one can begin by making simple (linear!) approximations as shown in Figure 3.

Figure 3: Simple probability distribution based on the estimates in Figure 2

Figure 3: Simple probability distribution based on the estimates in Fig 2

The key takeaway from the above is that quantifiable uncertainties are shapes rather than single numbers.  See this post and this one for details for how far this kind of reasoning can take you. That said, one should always be aware of the assumptions underlying the approximations. Failure to do so can be hazardous to the credibility of estimators!

Although I haven’t explicitly said so, estimation as described above has a subjective element. Among other things, the quality of an estimate depends on the judgement and experience of the estimator. As such, it is prone to being affected by errors of judgement and cognitive biases.  However, provided one keeps those caveats in mind, the probability-based approach described above is suited to situations in which uncertainties are quantifiable, at least in principle. That said, let’s move on to more complex situations in which uncertainties defy quantification.

Introducing ambiguity

The economist Frank Knight was possibly the first person to draw the distinction between quantifiable and unquantifiable uncertainties.  To make things really confusing, he called the former risk and the latter uncertainty. In his doctoral thesis, published in 1921, wrote:

…it will appear that a measurable uncertainty, or “risk” proper, as we shall call the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all. We shall accordingly restrict the term “uncertainty” to cases of the non-quantitative type (p.20)

Terminology has moved on since Knight’s time, the term uncertainty means lots of different things, depending on context. In this piece, we’ll use the term uncertainty to refer to quantifiable uncertainty (as in the task estimate of the previous section) and use ambiguity to refer to nonquantifiable uncertainty. In essence, then, we’ll use the term uncertainty for situations where we know what we’re measuring (i.e. the facts) but are uncertain about its numerical or categorical values whereas we’ll use the word ambiguity to refer to situations in which we are uncertain about what the facts  are or which facts are relevant.

As a test of understanding, you may want to classify each of the five points made in the second section of this post as either uncertain or ambiguous (Answers below)

Answer: 1 through 4 are ambiguous and 5 is uncertain.

How ambiguity manifests itself in decision problems

The distinction between uncertainty and ambiguity points to a problem with quantitative decision-making techniques such as cost-benefit analysis, multicriteria decision making methods or analytic hierarchy process. All these methods assume that decision makers are aware of all the available options, their preferences for them, the relevant evaluation criteria and the data needed. This is almost never the case for consequential decisions. To see why, let’s take a closer look at the different ways in which ambiguity can play out in the rational decision making process mentioned at the start of this article.

  1. The first step in the process is to identify available options. In the real world, however, options often cannot be enumerated or articulated fully. Furthermore, as options are articulated and explored, new options and sub-options tend to emerge. This is particularly true if the options depend on how future events unfold.
  2. The second step is to develop criteria for rating options. As anyone who has been involved in deciding on a contentious issue will confirm, it is extremely difficult to agree on a set of decision criteria for issues that affect different stakeholders in different ways.  Building a new road might improve commute times for one set of stakeholders but result in increased traffic in a residential area for others. The two criteria will be seen very differently by the two groups. In this case, it is very difficult for the two groups to agree on the relative importance of the criteria or even their legitimacy. Indeed, what constitutes a legitimate criterion is a matter of opinion.
  3. The third step is to rate options. The problem here is that real-world options often cannot be quantified or rated in a meaningful way. Many of life’s dilemmas fall into this category. For example, a decision to accept or decline a job offer is rarely made on the basis of material gain alone. Moreover, even where ratings are possible, they can be highly subjective. For example, when considering a job offer, one candidate may give more importance to financial matters whereas another might consider lifestyle-related matters (flexi-hours, commuting distance etc.) to be paramount. Another complication here is that there may not be enough information to settle the matter conclusively. As an example, investment decisions are often made on the basis of quantitative information that is based on questionable assumptions.

A key consequence of the above is that such ambiguous decision problems are socially complex – i.e. different stakeholders could have wildly different perspectives on the problem itself.   One could say the ambiguity experienced by an individual is compounded by the group.

Before going on I should point out that acute versions of such ambiguous decision problems go by many different names in the management literature. For example:

All these terms are more or less synonymous:  the root cause of the difficulty in every case is ambiguity (or unquantifiable uncertainty), which prevents a clear formulation of the problem.

Social complexity is hard enough to tackle as it is, but there’s another issue that makes things even harder: ambiguity invariably triggers negative emotions such as fear and anxiety in individuals who make up the group.  Studies in neuroscience have shown that in contrast to uncertainty, which evokes logical responses in people, ambiguity tends to stir up negative emotions while simultaneously suppressing the ability to think logically.  One can see this playing out in a group that is debating a contentious decision: stakeholders tend to get worked up over issues that touch on their values and identities, and this seems to limit their ability to look at the situation objectively.

Tackling ambiguity

Summarising the discussion thus far: rational decision making approaches are based on the assumption that stakeholders have a shared understanding of the decision problem as well as the facts and assumptions around it. These conditions are clearly violated in the case of ambiguous decision problems. Therefore, when confronted with a decision problem that has even a hint of ambiguity, the first order of the day is to help the group reach a shared understanding of the problem.  This is essentially an exercise in sensemaking, the art of collaborative problem formulation. However, this is far from straightforward because ambiguity tends to evoke negative emotions and attendant defensive behaviours.

The upshot of all this is that any approach to tackle ambiguity must begin by taking the concerns of individual stakeholders seriously.  Unless this is done, it will be impossible for the group to coalesce around a consensus decision. Indeed, ambiguity-laden decisions in organisations invariably fail when they overlook concerns of specific stakeholder groups.  The high failure rate of organisational change initiatives (60-70% according to this Deloitte report) is largely attributable to this point

There are a number of techniques that one can use to gather and synthesise diverse stakeholder viewpoints and thus reach a shared understanding of a complex or ambiguous problem. These techniques are often referred to as problem structuring methods (PSMs). I won’t go into these in detail here; for an example check out Paul Culmsee’s articles on dialogue mapping and Barry Johnson’s introduction to polarity management. There are many more techniques in the PSM stable. All of them are intended to help a group reconcile different viewpoints and thus reach a common basis from which one can proceed to the next step (i.e., make a decision on what should be done). In other words, these techniques help reduce ambiguity.

But there’s more to it than a bunch of techniques.  The main challenge is to create a holding environment that enables such techniques to work. I am sure readers have been involved in a meeting or situation where the outcome seems predetermined by management or has been undermined by self- interest. When stakeholders sense this, no amount of problem structuring is going to help.  In such situations one needs to first create the conditions for open dialogue to occur. This is precisely what a holding environment provides.

Creating such a holding environment is difficult in today’s corporate world, but not impossible. Note that this is not an idealist’s call for an organisational utopia. Rather, it involves the application of a practical set of tools that address the diverse, emotion-laden reactions that people often have when confronted with ambiguity.   It would take me too far afield to discuss PSMs and holding environments any further here. To find out more, check out my papers on holding environments and dialogue mapping in enterprise IT projects, and (for a lot more) the Heretic’s Guide series of books that I co-wrote with Paul Culmsee.

The point is simply this: in an ambiguous situation, a good decision – whatever it might be – is most likely to be reached by a consultative process that synthesises diverse viewpoints rather than by an individual or a clique.  However, genuine participation (the hallmark of a holding environment) in such a process will occur only after participants’ fears have been addressed.

Wrapping up

Standard approaches to decision making exhort managers and executives to begin with facts, and if none are available, to gather them diligently prior to making a decision. However, most real-life decisions are fraught with uncertainty so it may be best to begin with what one doesn’t know, and figure out how to make the possible decision under those “constraints of ignorance.” In this post I’ve attempted to outline what such an approach would entail. The key point is to figure out the kind uncertainty one is dealing with and choosing an approach that works for it. I’d argue that most decision making debacles stem from a failure to appreciate this point.

Of course, there’s a lot more to this approach than I can cover in the span of a post, but that’s a story for another time.

Note: This post is written as an introduction to the Data and Decision Making subject that is part of the core curriculum of the Master of Data Science and Innovation program, run by the Connected Intelligence Centre at UTS. I’m coordinating the subject this semester, and am honoured to be co-teaching it with my erstwhile colleague Sean Heffernan and my longtime collaborator Paul Culmsee.

Written by K

March 9, 2017 at 10:04 am

The Heretic’s Guide to Management – understanding ambiguity in the corporate world

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I am delighted to announce that my new business book, The Heretic’s Guide to Management: The Art of Harnessing Ambiguity, is now available in e-book and print formats. The book, co-written with Paul Culmsee, is a loose sequel to our previous tome, The Heretics Guide to Best Practices.

Many reviewers liked the writing style of our first book, which combined rigour with humour. This book continues in the same vein, so if you enjoyed the first one we hope you might like this one too. The new book is half the size of the first one and I considerably less idealistic too. In terms of subject matter, I could say “Ambiguity, Teddy Bears and Fetishes” and leave it at that…but that might leave you thinking that it’s not the kind of book you would want anyone to see on your desk!

Rest assured, The Heretic’s Guide to Management is not a corporate version of Fifty Shades of Grey. Instead, it aims to delve into the complex but fascinating ways in which ambiguity affects human behaviour. More importantly, it discusses how ambiguity can be harnessed in ways that achieve positive outcomes.  Most management techniques (ranging from strategic planning to operational budgeting) attempt to reduce ambiguity and thereby provide clarity. It is a profound irony of modern corporate life that they often end up doing the opposite: increasing ambiguity rather than reducing it.

On the surface, it is easy enough to understand why: organizations are complex entities so it is unreasonable to expect management models, such as those that fit neatly into a 2*2 matrix or a predetermined checklist, to work in the real world. In fact, expecting them to work as advertised is like colouring a paint-by-numbers Mona Lisa, expecting to recreate Da Vinci’s masterpiece. Ambiguity therefore invariably remains untamed, and reality reimposes itself no matter how alluring the model is.

It turns out that most of us have a deep aversion to situations that involve even a hint of ambiguity. Recent research in neuroscience has revealed the reason for this: ambiguity is processed in the parts of the brain which regulate our emotional responses. As a result, many people associate it with feelings of anxiety. When kids feel anxious, they turn to transitional objects such as teddy bears or security blankets. These objects provide them with a sense of stability when situations or events seem overwhelming. In this book, we show that as grown-ups we don’t stop using teddy bears – it is just that the teddies we use take a different, more corporate, form. Drawing on research, we discuss how management models, fads and frameworks are actually akin to teddy bears. They provide the same sense of comfort and certainty to corporate managers and minions as real teddies do to distressed kids.

A plain old Teddy

A Plain Teddy

Most children usually outgrow their need for teddies as they mature and learn to cope with their childhood fears. However, if development is disrupted or arrested in some way, the transitional object can become a fetish – an object that is held on to with a pathological intensity, simply for the comfort that it offers in the face of ambiguity. The corporate reliance on simplistic solutions for the complex challenges faced is akin to little Johnny believing that everything will be OK provided he clings on to Teddy.

When this happens, the trick is finding ways to help Johnny overcome his fear of ambiguity.

Ambiguity is a primal force that drives much of our behaviour. It is typically viewed negatively, something to be avoided or to be controlled.

A Sith Teddy

A Sith Teddy

The truth, however, is that ambiguity is a force that can be used in positive ways too. The Force that gave the Dark Side their power in the Star Wars movies was harnessed by the Jedi in positive ways.

A Jedi Teddy

A Jedi Teddy

Our book shows you how ambiguity, so common in the corporate world, can be harnessed to achieve the results you want.

The e-book is available via popular online outlets. Here are links to some:

Amazon Kindle

Google Play

Kobo

For those who prefer paperbacks, the print version is available here.

Thanks for your support 🙂

Written by K

July 12, 2016 at 10:30 pm

From inactivism to interactivism – managerial attitudes to planning

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Introduction

Managers display a range of attitudes towards planning for the future.  In an essay entitled Systems, Messes and Interactive Planning, the management guru/philosopher Russell Ackoff classified attitudes to organizational planning into four distinct types which I describe in detail below. I suspect you may recognise examples of each of these in your organisation…indeed, you might even see shades of yourself 🙂

Inactivism

This attitude, as its name suggests, is characterized by a lack of meaningful action. Inactivism is often displayed by managers in organisations that favour the status quo.  These organisations are happy with the way things are, and therefore see no need to change. However, lack of meaningful action does not mean lack of action. On the contrary, it often takes a great deal of effort to fend off change and keep things the way they are. As Ackoff states:

Inactive organizations require a great deal of activity to keep changes from being made. They accomplish nothing in a variety of ways. First, they require that all important decisions be made “at the top.” The route to the top is deliberately designed like an obstacle course. This keeps most recommendations for change from ever getting there. Those that do are likely to have been delayed enough to make them irrelevant when they reach their destination. Those proposals that reach the top are likely to be farther delayed, often by being sent back down or out for modification or evaluation. The organization thus behaves like a sponge and is about as active…

The inactive manager spends a lot of time and effort in ensuring that things remain the way they are. Hence they act only when a stituation forces them to. Ackoff puts it in his inimitable way by stating that, “Inactivist  managers tend to want what they get rather than get what they want.”

Reactivism

Reactivist managers are a step worse than inactivists  because they believe that disaster is already upon them. This is the type of manager who hankers after the “golden days of yore when things were much better than they are today.” As a result of their deep unease of where they are now, they may try to undo the status quo.  As Ackoff points out, unlike inactivists, reactivists do not ride the tide but try to swim against it.

Typically reactivist managers are wary of technology and new concepts. Moreover, they tend to give more importance to seniority and experience rather than proven competence. They also tend to be fans of simplistic solutions to complex problems…like “solving” the problem of a behind-schedule software project by throwing more people at it.

Preactivism

Preactivists are the opposite of reactivists in that they believe the future is going to be better than the past. Consequently, their efforts are geared towards understanding what the future will look like and how they can prepare for it.  Typically, preactive managers are concerned with facts, figures and forecasts; they are firm believers in scientific planning methods that they have learnt in management schools. As such, one might say that this is the most common species of manager in present  day organisations. Those who are not natural preactivists will fly the preactivist flag when they’re asked for their opinions by their managers because it’s the expected answer.

A key characteristic of preactivist managers is that they tend to revel in creating plans rather than implementing them. As Ackoff puts it, “Preactivists see planning as a sequence of discrete steps which terminate with acceptance or rejection of their plans. What happens to their plans is the responsibility of others.

Interactivism

Interactivists planners are not satisfied with the present, but unlike reactivists or preactivists, they do not hanker for the past, nor do they believe the future is automatically going to be better. They do want to make things better than they were or currently are, but they are continually adjusting their plans for the future by learning from and responding to events.  In short, they believe they can shape the future by their actions.

Experimentation is the hallmark of interactivists.  They are willing to try different approaches and learn from them. Although they believe in learning by experience, they do not want to wait for experiences to happen; they would rather induce them by (often small-scale) experimentation.

Ackoff labels interactivists as idealisers – people who pursue ideals they know cannot be achieved, but can be approximated or even reformulated in the light of new knowledge. As he puts it:

They treat ideals as relative absolutes: ultimate objectives whose formulation depends on our current knowledge and understanding of ourselves and our environment. Therefore, they require continuous reformulation in light of what we learn from approaching them.

To use a now fashionable term, interactivists are intrapreneurs.

Discussion

Although Ackoff shows a clear bias towards  interactivists in his article, he does mention that specific situations may call for other types of planners. As he puts it:

Despite my obvious bias in my characterization of these four postures, there are circumstances in which each is most appropriate. Put simply, if the internal and external dynamics of a system (the tide) are taking one where one wants to go and are doing so quickly enough, inactivism is appropriate. If the direction of change is right but the movement is too slow, preactivism is appropriate. If the change is taking one where one does not want to go and one prefers to stay where one is or was, reactivism is appropriate. However, if one is not willing to settle for the past, the present or the future that appears likely now, interactivism is appropriate.

The key point he makes is that inactivists and preactivists treat planning as a ritual because they see the future as something they cannot change. They can only plan for it (and hope for the best). Interactivists, on the other hand, look for opportunities to influence events and thus potentially change the future. Although both preactivists and interactivists are forward-looking, interactivists tend to be long-term thinkers as compared to preactivists who are more concerned about the short to medium term future.

Conclusion

Ackoff’s classification of planners in organisations is interesting because it highlights the kind of future-focused attitude that managers ought to take.  The sad fact, though, is that a significant number of managers are myopic preactivists, focused on this year’s performance targets rather than what their organisations might look like five or even ten years down the line. This is not the fault of individuals, though. The blame for the undue prevalence of myopic preactivism can be laid squarely on the deep-seated management dogma that rewards short-termism.

Written by K

August 20, 2015 at 9:30 pm

The façade of expertise

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Introduction

Since the 1980s, intangible assets, such as knowledge, have come to represent an ever-increasing proportion of an organisation’s net worth.  One of the problems associated with treating knowledge as an asset is that it is difficult to codify in its entirety. This is largely because knowledge is context and skill dependent, and these are hard to convey by any means other than experience. This is the well-known tacit versus explicit knowledge problem that I have written about at length elsewhere (see this post and this one, for example).  Although a recent development in knowledge management technology goes some way towards addressing the problem of context, it still looms large and is likely to for a while.

Although the problem mentioned above is well-known, it hasn’t stopped legions of consultants and professional organisations from attempting to codify and sell expertise: management consultancies and enterprise IT vendors being prime examples. This has given rise to the notion of a knowledge-intensive firm, an organization in which most work is said to be of an intellectual nature and where well-educated, qualified employees form the major part of the work force.   However, the slipperiness of knowledge mentioned in the previous paragraph suggests that the notion of a knowledge intensive firm (and, by implication, expertise) is problematic. Basically, if it is true that knowledge itself is elusive, and hard-to-codify, it raises the question as to what exactly such firms (and their employees) sell.

In this post, I shed some light on this question by drawing on an interesting paper by Mats Alvesson entitled, Knowledge Work: Ambiguity, Image and Identity (abstract only), as well as my experiences in dealing with IT services and consulting firms.

Background: the notion of a knowledge-intensive firm

The first point to note is that the notion of a knowledge-intensive firm is not particularly precise. Based on the definition offered above, it is clear that a wide variety of organisations may be classified as knowledge intensive firms. For example, management consultancies and enterprise software companies would fall into this category, as would law, accounting and research & development firms.  The same is true of the term knowledge work(er).

One of the implications of the vagueness of the term is that any claim to being a knowledge-intensive firm or knowledge worker can be contested. As Alvesson states:

It is difficult to substantiate knowledge-intensive companies and knowledge workers as distinct, uniform categories. The distinction between these and non- (or less) knowledge-intensive organization/non-knowledge   workers is not self-evident, as all organizations and work  involve “knowledge” and any evaluation of “intensiveness” is likely to be contestable. Nevertheless,  there are, in many crucial respects, differences  between many professional service and high-tech companies on the one hand, and more routinized service and industry companies on the other, e.g. in terms of broadly socially shared ideas about the significance of a long theoretical education and intellectual capacities for the work. It makes sense to refer to knowledge-intensive companies as a vague but meaningful category, with sufficient heuristic value to be useful. The category does not lend itself to precise definition or delimitation and it includes organizations which are neither unitary nor unique. Perhaps the claim to knowledge-intensiveness is one of the most distinguishing features…

The last line in the excerpt is particularly interesting to me because it resonates with my experience: having been through countless IT vendor and management consulting briefings on assorted products and services, it is clear that a large part of their pitch is aimed at establishing their credibility as experts in the field, even though they may not actually be so.

The ambiguity of knowledge work

Expertise in skill-based professions is generally unambiguous – an incompetent pilot will be exposed soon enough. In knowledge work, however, genuine expertise is often not so easily discernable. Alvesson highlights a number of factors that make this so.

Firstly, much of the day-to-day work of knowledge workers such as management consultants and IT experts involves routine matters – meetings, documentation etc. – that do not make great demands on their skills. Moreover, even when involved in one-off tasks such as projects, these workers are generally assigned tasks that they are familiar with. In general, therefore, the nature of their work requires them to follow already instituted processes and procedures.  A somewhat unexpected consequence of this is that incompetence can remain hidden for a long time.

A second issue is that the quality of so-called knowledge work is often hard to evaluate – indeed evaluations may require the engagement of independent experts! This is true even of relatively mundane expertise-based work. As Alvesson states:

Comparisons of the decisions of expert and novice auditors indicate no relationship  between the degree of expertise  (as indicated by experience)  and consensus; in high-risk and less standard situations, the experts’ consensus level was lower than that of novices. [An expert remarked that] “judging the quality of an audit is an extremely problematic exercise” and says that consumers of the audit service “have only a very limited insight into the quality of work undertaken by an audit firm”.

This is true of many different kinds of knowledge work.  As Alvesson tells us:

How can anyone tell whether a headhunting firm has found and recruited the best possible candidates or not…or if an audit has been carried out in a high-quality way?  Or  if  the  proposal by  strategic management consultants is optimal or even helpful, or not. Of course, sometimes one may observe whether something works or not (e.g. after the intervention of a plumber), but normally the issues concerned are not that simple in the context in which the concept of knowledge-intensiveness is frequently used. Here we are mainly dealing with complex and intangible phenomena.  Even if something seems to work, it might have worked even better or the cost of the intervention been much lower if another professional or organization had carried out the task.

In view of the above, it is unlikely that market mechanisms would be effective in sorting out the competent from the incompetent.  Indeed, my experience of dealing with major consulting firms (in IT) leads me believe that market mechanisms tend to make them clones of each other, at least in terms of their offerings and approach. This may be part of the reason why client firms tend to base their contracting decisions on the basis of cost or existing relationships – it makes sense to stick with the known, particularly when the alternatives offer choices akin to Pepsi vs Coke.

But that is not the whole story, experts are often hired for ulterior motives. On the one hand, they  might be hired because they confer legitimacy – “no one ever got fired for hiring McKinsey” is a quote I’ve heard more than a few times in many workplaces. On the other hand, they also make convenient scapegoats when the proverbial stuff hits the fan.

Image cultivation

One of the consequences of the ambiguity of knowledge-intensive work is that employees in such firms are forced to cultivate and maintain the image of being experts, and hence the stereotype of the suited, impeccably-groomed Big 4 consultant. As Alvesson points out, though, image cultivation goes beyond the individual employee:

This image must be  managed on different levels: professional-industrial, corporate and individual. Image may be targeted in specific acts and arrangements,  in visible symbols for public consumption but also in everyday behavior, within the organization and in interaction  with others. Thus image is not just of importance in marketing  and for attracting personnel but also in and after production.  Size and a big name  are  therefore important for  many knowledge-intensive companies – and here we perhaps have a major explanation  for all the mergers and acquisitions  in accounting, management consultancy and  other  professional service companies. A large size is reassuring. A well-known brand name substitutes for difficulties in establishing quality.

Another aspect of image cultivation is the use of rhetoric. Here are some examples taken from the websites of Big 4 consulting firms:

No matter the challenge, we focus on delivering practical and enduring results, and equipping our clients to grow and lead.” —McKinsey

We continue to redefine ourselves and set the bar higher to continually deliver quality for clients, our people, and the society in which we operate.” – Deloitte

Cutting through complexity” – KPMG

Creating value for our clients, people and communities in a changing world” – PWC

Some clients are savvy enough not to be taken in by the platitudinous statements listed above.  However, the fact that knowledge-intensive firms continue to use second-rate rhetoric to attract custom suggests that there are many customers who are easily taken in by marketing slogans.  These slogans are sometimes given an aura of plausibility via case-studies intended to back the claims made. However, more often than not the case studies are based on a selective presentation of facts that depict the firm in the best possible light.

A related point is that such firms often flaunt their current client list in order to attract new clientele. Lines like, “our client list includes 8 of top ten auto manufacturers in the world,” are not uncommon, the unstated implication being that if you are an auto manufacturer, you cannot afford not to engage us. The image cultivation process continues well after the consulting engagement is underway. Indeed, much of a consultant’s effort is directed at ensuring that the engagement will be extended.

Finally, it is important to point out the need to maintain an aura of specialness. Consultants and knowledge workers are valued for what they know. It is therefore in their interest to maintain a certain degree of exclusivity of knowledge. Guilds (such as the Project Management Institute) act as gatekeepers by endorsing the capabilities of knowledge workers through membership criteria based on experience and / or professional certification programs.

Maintaining the façade

Because knowledge workers deal with intangibles, they have to work harder to maintain their identities than those who have more practical skills. They are therefore more susceptible to the vagaries and arbitrariness of organisational life.  As Alvesson notes,

Given the high level of ambiguity and the fluidity of organizational  life and interactions with external actors, involving a strong dependence on somewhat arbitrary evaluations  and opinions of others, many knowledge-intensive workers must struggle more for the accomplishment,  maintenance and gradual change of self-identity, compared to workers whose competence and results are more materially grounded…Compared with people who invest less self- esteem in their work and who have lower expectations,  people in knowledge-intensive  companies are thus vulnerable to frustrations  contingent upon ambiguity of performance  and confirmation.

Knowledge workers are also more dependent on managerial confirmation of their competence and value. Indeed, unlike the case of the machinist or designer, a knowledge worker’s product rarely speaks for itself. It has to be “sold”, first  to management and then (possibly) to the client and the wider world.

The previous paragraphs of this section dealt with individual identity. However, this is not the whole story because organisations also play a key role in regulating the identities of their employees. Indeed, this is how they develop their brand. Alvesson notes four ways in which organisations do this:

  1. Corporate identity – large consulting firms are good examples of this. They regulate the identities of their employees through comprehensive training and acculturation programs. As a board member remarked to me recently, “I like working with McKinsey people, because I was once one myself and I know their approach and thinking processes.”
  2. Cultural programs – these are the near-mandatory organisational culture initiatives in large organisations. Such programs are usually based on a set of “guiding principles” which are intended to inform employees on how they should conduct themselves as employees and representatives of the organisation. As Alvesson notes, these are often more effective than formal structures.
  3. Normalisation – these are the disciplinary mechanisms that are triggered when an employee violates an organisational norm. Examples of this include formal performance management or official reprimands. Typically, though, the underlying issue is rarely addressed. For example, a failed project might result in a reprimand or poor performance review for the project manager, but the underlying systemic causes of failure are unlikely to be addressed…or even acknowledged.
  4. Subjectification – This is where employees mould themselves to fit their roles or job descriptions. A good example of this is when job applicants project themselves as having certain skills and qualities in their resumes and in interviews. If selected, they may spend the first few months in learning and internalizing what is acceptable and what is not. In time, the new behaviours are internalized and become a part of their personalities.

It is clear from the above that maintaining the façade of expertise in knowledge work involves considerable effort and manipulation, and has little to do with genuine knowledge. Indeed, it is perhaps because genuine expertise is so hard to identify that people and organisations strive to maintain appearances.

Conclusion

The ambiguous nature of knowledge requires (and enables!) consultants and technology vendors to maintain a façade of expertise. This is done through a careful cultivation of image via the rhetoric of marketing, branding and impression management.The onus is therefore on buyers to figure out if there’s anything of substance behind words and appearances. The volume of business enjoyed by big consulting firms suggests that this does not happen as often as it should, leading us to the inescapable conclusion that decision-makers in organisations are all too easily deceived by the facade of expertise.

Written by K

July 8, 2015 at 8:47 pm

Catch-22 and the paradoxes of organisational life

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“You mean there’s a catch?”

“Sure there’s a catch”, Doc Daneeka replied. “Catch-22. Anyone who wants to get out of combat duty isn’t really crazy.”

There was only one catch and that was Catch-22, which specified that a concern for one’s own safety in the face of dangers that were real and immediate was the process of a rational mind. Orr was crazy and could be grounded. All he had to do was ask; and as soon as he did, he would no longer be crazy and would have to fly more missions…”   Joseph Heller, Catch-22

Introduction

The term Catch-22 was coined by Joseph Heller in the eponymous satirical novel written in 1961. As the quote above illustrates,  the term refers to a paradoxical situation caused by the application of  contradictory rules.  Catch-22 situations are common in large organisations of all kinds, not just the military (which was the setting of the novel). So much so that it is a theme that has attracted some scholarly attention over the half century since the novel was first published  – see this paper or this one for example.

Although Heller uses Catch-22 situations to highlight the absurdities of bureaucracies in a humorous way, in real-life such situations can be deeply troubling for people who are caught up in them. In a paper published in 1956, the polymath Gregory Bateson and his colleagues  suggested that these situations can cause people to behave in ways that are symptomatic of schizophrenia .  The paper introduces the notion of a  double-bind, which is  a dilemma arising from an individual receiving two or more messages that contradict each other .   In simple terms, then,  a double-bind is a Catch-22.

In this post, I draw on Bateson’s  double bind theory to get some insights into Catch-22 situations in organisations.

Double bind theory

The basic elements of a double bind situation are as follows:

  1. Two or more individuals, one of whom is a victim – i.e. the individual who experiences the dilemma described below.
  2. A primary rule which keeps the victim fearful of the consequences of doing (or not doing) something.  This rule typically takes the form , “If you do x then you will be punished” or “If you do not do x then you will be punished. “
  3. A secondary rule that is in conflict with the primary rule, but at more abstract level. This rule, which is usually implicit, typically takes the form, “Do not question the rationale behind x.”
  4. A tertiary rule that prevents the victim from escaping from the situation.
  5. Repeated experiences of (1) and (2)

A simple example (quoted from this article) serves to illustrate the above in a real- life situation:

One example of double bind communication is a mother giving her child the message: “Be spontaneous” If the child acts spontaneously, he is not acting spontaneously because he is following his mother’s direction. It’s a no-win situation for the child. If a child is subjected to this kind of communication over a long period of time, it’s easy to see how he could become confused.

Here the injunction to “Be spontaneous” is contradicted by the more implicit rule that “one cannot be spontaneous on demand.”  It is important to note that the primary and secondary (implicit) rules are at different logical levels  –  the first is about an action, whereas the second is about the nature of all such actions. This is typical of a double bind situation.

The paradoxical aspects of double binds can sometimes be useful as they can lead to creative solutions arising from the victim “stepping outside the situation”. The following example from Bateson’s paper illustrates the point:

The Zen Master attempts to bring about enlightenment in his pupil in various ways. One of the things he does is to hold a stick over the pupil’s head and say fiercely, “If you say this stick is real, I will strike you with it. If you say this stick is not real, I will strike you with it. If you don’t say anything, I will strike you with it.”… The Zen pupil might reach up and take the stick away from the Master–who might accept this response.

This is an important point which we’ll return to towards the end of  this piece.

Double binds in organisations

Double bind situations are ubiquitous in organisations.   I’ll illustrate this by drawing on a couple of examples I have written about earlier on this blog.

The paradox of learning organisations

This section draws on a post I wrote while ago. In the introduction to that post I stated that:

The term learning organisation refers to an organisation that continually modifies its processes  based on observation and experience, thus adapting to changes in its internal and external environment.   Ever since Peter Senge coined the term in his book, The Fifth Discipline, assorted consultants and academics have been telling us that although a  learning  organisation is an utopian ideal, it is one worth striving for.  The reality, however,  is that most organisations that undertake the journey actually end up in a place far removed  from this ideal. Among other things, the journey may expose managerial hypocrisies that contradict the very notion of a learning organisation.

Starkly put, the problem arises from the fact that in a true learning organisation, employees will  inevitably start to question things that management would rather they didn’t.  Consider the following story, drawn from this paper on which the post is based:

…a multinational company intending to develop itself as a learning organization ran programmes to encourage managers to challenge received wisdom and to take an inquiring approach. Later, one participant attended an awayday, where the managing director of his division circulated among staff over dinner. The participant raised a question about the approach the MD had taken on a particular project; with hindsight, had that been the best strategy? `That was the way I did it’, said the MD. `But do you think there was a better way?’, asked the participant. `I don’t think you heard me’, replied the MD. `That was the way I did it’. `That I heard’, continued the participant, `but might there have been a better way?’. The MD fixed his gaze on the participants’ lapel badge, then looked him in the eye, saying coldly, `I will remember your name’, before walking away.

Of course,  a certain kind of learning  occurred here:  the employee learnt that certain questions were taboo, in stark contrast to the openness that was being preached from the organisational pulpit.  The double bind here is evident:  feel free to question and challenge everything…except what management deems to be out of bounds.  The takeaway for employees is that, despite all the rhetoric of organisational learning, certain things should not  be challenged. I think it is safe to say that this was probably not the kind of learning that was intended by those who initiated the program.

The paradoxes of change

In a post on the  paradoxes of organizational change, I wrote that:

An underappreciated facet of organizational change is that it is inherently paradoxical. For example, although it is well known that such changes inevitably have unintended consequences that are harmful, most organisations continue to implement change initiatives in a manner that assumes  complete controllability with the certainty of achieving solely beneficial outcomes.

As pointed out in this paper, there are three types of paradoxes that can arise when an organisation is restructured. The first is that during the transition, people are caught between the demands of their old and new roles. This is exacerbated by the fact that transition periods are often much longer expected. This paradox of performing in turn leads to a paradox of belonging – people become uncertain about where their loyalties (ought to) lie.

Finally, there is a paradox of organising, which refers to the gap between the rhetoric and reality of change. The paper mentioned above has a couple of nice examples. One study described how,

friendly banter in meetings and formal documentation [promoted] front-stage harmony, while more intimate conversations and unit meetings [intensified] backstage conflict.”  Another spoke of a situation in which, “…change efforts aimed at increasing employee participation [can highlight] conflicting practices of empowerment and control. In particular, the rhetoric of participation may contradict engrained organizational practices such as limited access to information and hierarchical authority for decision making…

Indeed, the gap between the intent and actuality of change initiatives make double binds inevitable.

Discussion

I suspect the situations described above will be familiar to people working in a corporate environment. The question is what can one do if one is on the receiving end of such a Catch 22?

The main thing is to realise that a double-bind arises because one perceives the situation to be so. That is, the person experiencing the situation has chosen to interpret it  as a double bind. To be sure, there are usually factors that influence the choice – things such as job security, for example – but the fact is that it is a choice that can be changed if one sees things in a different light. Escaping the double bind is then a “simple” matter of reframing the situation.

Here is where the notion of mindfulness is particularly relevant. In brief, mindfulness is “the intentional, accepting and non-judgemental focus of one’s attention on the emotions, thoughts and sensations occurring in the present moment.”  As the Zen pupil who takes the stick away from the Master, a calm non-judgemental appraisal of a double-bind situation might reveal possible courses of action that had been obscured because of one’s fears. Indeed, the realization that one has more choices than one thinks is in itself a liberating discovery.

It is important to emphasise that the actual course of action that one selects in the end matters less than the realisation that one’s reactions to such situations is largely under one’s own control.

In closing – reframe it!

Organisational life is rife with Catch 22s. Most of us cannot avoid being caught up in them, but we can choose how we react to them. This is largely a matter of reframing them in ways that open up new avenues for action, a point that brings to mind this paragraph from Catch-22 (the book):

“Why don’t you use some sense and try to be more like me? You might live to be a hundred and seven, too.”

“Because it’s better to die on one’s feet than live on one’s knees,” Nately retorted with triumphant and lofty conviction. “I guess you’ve heard that saying before.”

“Yes, I certainly have,” mused the treacherous old man, smiling again. “But I’m afraid you have it backward. It is better to live on one’s feet than die on one’s knees. That is the way the saying goes.”

“Are you sure?” Nately asked with sober confusion. “It seems to make more sense my way.”

“No, it makes more sense my way. Ask your friends.”

And that, I reckon, is as brilliant an example of reframing as I have ever come across.

Written by K

June 22, 2015 at 9:54 pm

From the coalface: an essay on the early history of sociotechnical systems

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The story of sociotechnical systems began a little over half a century ago, in a somewhat unlikely setting: the coalfields of Yorkshire.

The British coal industry had just been nationalised and new mechanised mining methods were being introduced in the mines. It was thought that nationalisation would sort out the chronic labour-management issues and mechanisation would address the issue of falling productivity.

But things weren’t going as planned. In the words of Eric Trist, one of the founders of the Tavistock Institute:

…the newly nationalized industry was not doing well. Productivity failed to increase in step with increases in mechanization. Men were leaving the mines in large numbers for more attractive opportunities in the factory world. Among those who remained, absenteeism averaged 20%. Labour disputes were frequent despite improved conditions of employment.   – excerpted from, The evolution of Socio-technical systems – a conceptual framework and an action research program, E. Trist (1980)

Trist and his colleagues were asked by the National Coal Board to come in and help. To this end, they did a comparative study of two mines that were similar except that one had high productivity and morale whereas the other suffered from low performance and had major labour issues.

Their job was far from easy: they were not welcome at the coalface because workers associated them with management and the Board.

Trist recounts that around the time the study started, there were a number of postgraduate fellows at the Tavistock Institute. One of them, Ken Bamforth, knew the coal industry well as he had been a miner himself.  Postgraduate fellows who had worked in the mines were encouraged to visit their old workplaces after  a year and  write up their impressions, focusing on things that had changed since they had worked there.   After one such visit, Bamforth reported back with news of a workplace innovation that had occurred at a newly opened seam at Haighmoor. Among other things, morale and productivity at this particular seam was high compared to other similar ones.  The team’s way of working was entirely novel, a world away from the hierarchically organised set up that was standard in most mechanised mines at the time. In Trist’s words:

The work organization of the new seam was, to us, a novel phenomenon consisting of a set of relatively autonomous groups interchanging roles and shifts and regulating their affairs with a minimum of supervision. Cooperation between task groups was everywhere in evidence; personal commitment was obvious, absenteeism low, accidents infrequent, productivity high. The contrast was large between the atmosphere and arrangements on these faces and those in the conventional areas of the pit, where the negative features characteristic of the industry were glaringly apparent. Excerpted from the paper referenced above.

To appreciate the radical nature of practices at this seam, one needs to understand the backdrop against which they occurred. To this end, it is helpful to compare the  mechanised work practices introduced in the post-war years with the older ones from the pre-mechanised era of mining.

In the days before mines were mechanised, miners would typically organise themselves into workgroups of six miners, who would cover three work shifts in teams of two. Each miner was able to do pretty much any job at the seam and so could pick up where his work-mates from the previous shift had left off. This was necessary in order to ensure continuity of work between shifts. The group negotiated the price of their mined coal directly with management and the amount received was shared equally amongst all members of the group.

This mode of working required strong cooperation and trust within the group, of course.  However, as workgroups were reorganised from time to time due to attrition or other reasons, individual miners understood the importance of maintaining their individual reputations as reliable and trustworthy workmates. It was important to get into a good workgroup because such groups were more likely to get more productive seams to work on. Seams were assigned by bargaining, which was typically the job of the senior miner on the group. There was considerable competition for the best seams, but this was generally kept within bounds of civility via informal rules and rituals.

This traditional way of working could not survive mechanisation. For one, mechanised mines encouraged specialisation because they were organised like assembly lines, with clearly defined job roles each with different responsibilities and pay scales. Moreover, workers in a shift would perform only part of the extraction process leaving those from subsequent shifts to continue where work was left off.

As miners were paid by the job they did rather than the amount of coal they produced, no single group had end-to-end responsibility for the product.   Delays due to unexpected events tended to get compounded as no one felt the need to make up time. As a result, it would often happen that work that was planned for a shift would not be completed. This meant that the next shift (which could well be composed of a group with completely different skills) could not or would not start their work because they did not see it as their job to finish the work of the earlier shift. Unsurprisingly, blame shifting and scapegoating was rife.

From a supervisor’s point of view, it was difficult to maintain the same level of oversight and control in underground mining work as was possible in an assembly line. The environment underground is simply not conducive to close supervision and is also more uncertain in that it is prone to unexpected events.  Bureaucratic organisational structures are completely unsuited to dealing with these because decision-makers are too far removed from the coalface (literally!).  This is perhaps the most important insight to come out of the Tavistock coal mining studies.

As Claudio Ciborra  puts it in his classic book on teams:

Since the production process at any seam was much more prone to disorganisation than due to uncertainty and complexity of underground conditions, any ‘bureaucratic’ allocation of jobs could be easily disrupted. Coping with emergencies and coping with coping became part of worker’s and supervisors’ everyday activities. These activities would lead to stress, conflict and low productivity because they continually clashed with the technological arrangements and the way they were planned and subdivided around them.

Thus we see that the new assembly-line bureaucracy inspired work organisation was totally unsuited to the work environment because there was no end-to-end responsibility, and decision making was far removed from the action. In contrast, the traditional workgroup of six was able to deal with uncertainties and complexities of underground work because team members had a strong sense of responsibility for the performance of the team as a whole. Moreover, teams were uniquely placed to deal with unexpected events because they were actually living them as they occurred and could therefore decide on the best way to deal with them.

What Bamforth found at the Haighmoor seam was that it was possible to recapture the spirit of the old ways of working by adapting these to the larger specialised groups that were necessary in the mechanised mines. As Ciborra describes it in his book:

The new form of work organisation features forty one men who allocate themselves to tasks and shifts. Although tasks and shifts those of the conventional mechanised system, management and supervisors do not monitor, enforce and reward single task executions. The composite group takes over some of the managerial tasks, as it had in the pre-mechanised marrow group, such as the selection of group members and the informal monitoring of work…Cycle completion, not task execution becomes a common goal that allows for mutual learning and support…There is basic wage and a bonus linked to the overall productivity of the group throughout the whole cycle rather than a shift.  The competition between shifts that plagued the conventional mechanised method is effectively eliminated…

Bamforth and Trist’s studies on Haighmoor convinced them that there were viable (and better!) alternatives to those that were typical of mid to late 20th century work places.  Their work led them to the insight that the best work arrangements come out of seeking a match between technical and social elements of the modern day workplace, and thus was born the notion of sociotechnical systems.

Ever since the assembly-line management philosophies of Taylor and Ford, there has been an increasing trend towards division of labour, bureaucratisation and mechanisation / automation of work processes.  Despite the early work of the Tavistock school and others who followed, this trend continues to dominate management practice, arguably even more so in recent years. The Haighmoor innovation described above was one of the earliest demonstrations that there is a better way.   This message has since been echoed by many academics and thinkers,  but remains largely under-appreciated or ignored by professional managers who have little idea – or have completely forgotten – what it is like to work at the coalface.

Written by K

April 7, 2015 at 10:30 pm

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