Cause and effect in management
Introduction
Management schools and gurus tell us that specific managerial actions will lead to desirable consequences – witness the prescriptions for success in books such as Good to Great or In Search of Excellence. But can one really attribute success (or failure) to specific actions? A cause-effect relationship is often assumed, but in reality the causal connection between strategic management actions and organisational outcomes is tenuous. This post, based on a paper by Glenn Shafer entitled Causality and Responsibility, is an exploration of the causal connection between managerial actions and their (assumed) consequences.
Note that the discussion below applies to strategic – or “big picture” – management decisions, not operational ones. In the latter, cause and effect is generally quite clear cut. For example, the decision to initiate a project sets in motion several processes that have fairly predictable outcomes. However, taking a big picture view, initiating a project (or even the successful completion of one) does not imply that the strategic aims of the project will be met. It is the latter point that is of interest here – the causal connection between a strategic decision and its assumed outcome.
Shafer’s paper deals with causality and responsibility in legal deliberations: specifically, the process by which judges and juries reach their verdict as to whether the accused (person or entity) is actually responsible (in a causal sense) for the outcome they are charged with. In short, did the actions of the accused cause the outcome? The arguments Shafer makes are quite general, and have applicability to any discipline. In the following paragraphs I’ll look at a couple of the key points he makes and outline their implications for cause and effect in management actions.
Deterministic cause-effect relationships
The first point that Shafer makes is that we should infer that a particular action causes a particular outcome only if it is improbable that the outcome could have happened without the action preceding it. In Shafer’s words:
…we are on safe ground in attributing responsibility if we do so based on our knowledge of impossibilities. It is not surprising, therefore, that the classical legal concept of cause – necessary and sufficient cause – is defined in terms of impossibility. According to this concept, an action causes an event if the event must happen (it is impossible for it not to happen) when the action is taken and cannot happen (it is impossible for it to happen) if the action is not taken.
This is, in fact, what legal arguments attempt to do: they attempt to prove, beyond reasonable doubt, that the crime occurred because of the defendants actions.
The reason that impossibilities are a better way of “proving” causal relationships is that such relationships cannot be invalidated as our knowledge of the situation increases providing the knowledge that we already have is valid. In other words, once something is deemed impossible (using valid knowledge) then it remains so even if we get to know more about the situation. In contrast, if something is deemed possible in the light of existing knowledge, it can be rendered false by a single contradictory fact.
The implication of the above for cause and effect in management is clear: a manager can (should!) claim responsibility for a particular outcome only if:
- The outcome must (almost always) happen if the managerial action occurs.
- It is highly unlikely that the outcome could have occurred without the action occurring prior to it.
Seen in this light, many of the prescriptions laid out in management bestsellers are little better than herpetological oleum.
Probabilistic cause-effect relationships
Of course, deterministic cause-effect relationships aren’t the norm in management – only the supremely confident (foolhardy?) would claim that a specific managerial action will always lead to a specific organisational outcome. This begs the question: what about probabilistic relationships? That is, what can we say about claims that a particular action results in a particular effect, but only in a fraction of the instances in which the action occurs?
To address this question, Shafer makes the important point that probabilities not close to zero or one have no meaning in isolation. They have meaning only in a system, and their meaning derives from the impossibility of a successful gambling strategy—the probability close to one that no one can make a substantial amount of money betting at the odds given by the probabilities. The last part of the previous statement is a consequence of how probabilities are validated empirically. In Shafer’s words:
We validate a system of probabilities empirically by performing statistical tests. Each such test checks whether observations have some overall property that the system says they are practically certain to have. It checks, in other words, on whether observations diverge from the probabilistic model in a way that the model says is practically (approximately) impossible. In Probability and Finance: It’s Only a Game, Vovk and I argue that both the applications of probability and the classical limit theorems (the law of large numbers, the central limit theorem, etc.) can be most clearly understood and most elegantly explained if we treat these asserted practical impossibilities as the basic meaning of a probabilistic or statistical model, from which all other mathematical and practical conclusions are to be derived. I cannot go further into the argument of the book here, but I do want to emphasize one of its consequences: because the empirical validity of a system of probabilities involves only the approximate impossibilities it implies, it is only these approximate impossibilities that we should expect to see preserved in a deeper causal structure. Other probabilities, those not close to zero or one, may not be preserved and hence cannot claim the causal status.
An implication of the above is that probabilities not close to zero or one are not fundamental properties of the system/situation; they are subject to change as our knowledge of the situation/system improves. A simple example may serve to explain this point. Consider the following hypothetical claim from a software vendor:
“80% of our customers experience an increase in sales after implementing our software system.”
Presumably, the marketing department responsible for this statement has the data to back it up. Despite that, the increase in sales for a particular customer cannot (should not!) be attributed to the software. Why? Well, for the following reasons:
- The particular customer may differ in important ways from those used in estimating the probability.This is a manifestation of the reference class problem.
- Most statistical studies of the kind used in marketing or management studies are enumerative, not analytical – i.e they can be used to classify data, but not to establish cause-effect relationships. See my post entitled Enumeration or Analysis for more onthe differences between enumerative and analytical studies.
There is an underlying reason for the above which I’ll discuss next.
The root of the problem – too many variables
The points made above – that outcomes cannot be attributed to actions unless the probabilities involved are close to zero or one – is a consequence of the fact that most organisational outcomes are results of several factors. Therefore it is incorrect to attribute the outcome to a single factor (such as farsighted managerial action). Nancy Cartwright makes this point in her paper entitled Causal Laws and Effective Strategies, where she states that a cause ought to increase the frequency of its purported outcome, but this increase can be masked by other causal factors that have not been taken into account. She uses the somewhat dated and therefore incorrect example of the relationship between smoking and heart disease. However, it serves to illustrate the point, so I’ll quote it below:
…a cause ought to increase the frequency of its effect. But this fact may not show up in the probabilities if other causes are at work. Background correlations between the purported cause and other causal factors may conceal the increase in probability which would otherwise appear. A simple example will illustrate. It is generally supposed that smoking causes heart disease. Thus, we may expect that the probability of heart disease on smoking is greater than otherwise (K’s note: i.e. the conditional probability of heart disease given that the person is a smoker, P(H/S), is greater than the probability of heart disease in the general population, P(H)). This expectation is mistaken, however. Even if it is true that smoking causes heart disease, the expected increase in probability will not appear if smoking is correlated with a sufficiently strong preventative, say exercising. To see why this is so, imagine that exercising is more effective at preventing heart disease than smoking at causing it. Then in any population where smoking and exercising are highly enough correlated, it can be true that P(H/S) = P(H), or even P(H/S) < P(H). For the population of smokers also contains a good many exercisers, and when the two are in combination, the exercising tends to dominate….
In the case of strategic outcomes, it is impossible to know all the factors involved. Moreover, the factors are often interdependent and subject to positive feedback (see my previous post for more on this). So the problem is even worse than implied by Cartwright’s example.
Conclusions
The implications of the above can be summarised as follows: the efficacy of most strategic managerial actions is questionable because the probabilities involved in such claims are rarely close to zero or one. This shouldn’t be a surprise: most organisational outcomes are consequences of several factors acting in concert, many of which combine in unpredictable ways. Given this is unreasonable to expect that managerial actions will result in predictable organisational outcomes. That said, it is only natural to claim responsibility for desirable outcomes and shift the blame for undesirable ones, as it is to seek simplistic solutions to difficult organisational problems. Hence the insatiable market for management snake oil.
On the origin of power laws in organizational phenomena
Introduction
Uncertainty is a fact of organizational life – managers often have to make decisions based on uncertain or incomplete information. Typically such decisions are based on a mix of intuition, experience and blind guesswork or “gut feel”. In recent years, probabilistic (or statistical) techniques have entered mainstream organizational practice. These have enabled managers to base their decisions and consequent actions on something more than mere subjective judgement – or so the theory goes.
Much of the statistical analysis in organisational theory and research is based on the assumption that the variables of interest have a Normal (aka Gaussian) distribution. That is, the probability of a variable taking on a particular value can be reckoned from the familiar bell-shaped curve. In a paper entitled Beyond Gaussian averages: redirecting organizational science towards extreme events and power laws, Bill McKelvey and Pierpaolo Andriani, suggest that many (if not most) organizational variables aren’t normally distributed, but are better described by power law or fat-tailed (aka long-tailed or heavy-tailed) distributions. If correct, this has major consequences for quantitative analysis in many areas of organizational theory and practice. To quote from their paper:
Quantitative management researchers tend to presume Gaussian (normal) distributions with matching statistics – for evidence, study any random sample of their current research. Suppose this premise is mostly wrong. It follows that (1) publication decisions based on Gaussian statistics could be mistaken, and (2) advice to managers could be misguided.
Managers generally assume that their actions will not have extreme outcomes. However, if organisational phenomena exhibit power law behaviour, it is possible that seemingly minor actions could have disproportionate results. It is therefore important to understand how such extreme outcomes can come about. This post, based on the aforementioned paper and some of the references therein discusses a couple of general mechanisms via which power laws can arise in organizational phenomena.
I’ll begin by outlining the main differences between normal and power law distributions, and then present a few social phenomena that display power law behaviour. Following that, I get to my main point – a discussion of general mechanisms that underlie power-law type behaviour in organisational phenomena. I conclude by outlining the implication of power-law phenomena for managerial actions and their (intended) outcomes.
Power laws vs. the Normal distribution
Probabilistic variables that are described by the normal distributions tend to take on values that cluster around the average, with the probability dropping off to zero rapidly on either side of the average. In contrast, for long –tailed distributions, there is a small but significant probability that the variable will take on a value that is very far from the average (what is sometimes called a black swan event). Long-tailed distributions are often described by power laws. In such cases, the probability of variable taking a value 
Power laws in social phenomena
In their paper Mckelvey and Andriani mention a number of examples of power laws in natural and social phenomena. Examples of the latter include:
- The sizes of US firms : the probability that a firm is greater than size N (where N is the number of employees), is inversely proportional to N .
- The number of criminal acts committed by individuals: the frequency of conviction is a power law function of the ranked number of convictions.
- Information access on the Web: The access rate of new content on the web decays with time according to a power law.
- Frequency of family names: Frequency of family names has a power law dependence on family size (number of people with the same family name).
Given the ubiquity of power laws in social phenomena, Mckelvey and Adriani suggest that they may be common in organizational phenomena as well. If this is so, managerial decisions based on the assumption of normality could be wildly incorrect. In effect, such an assumption treats extreme events as aberrations and ignores them. But extreme events have extreme business implications and hence must be factored in to any sensible analysis.
If power laws are indeed as common as claimed, there must be some common underlying mechanism(s) that give rise to them. We look at a couple of these in the following sections.
Positive feedback
In a classic paper entitled, The Second Cybernetics: Deviation-Amplifying Mutual Causal Processes, published in 1963, Magoroh Maruyama pointed out that small causes can have disproportionate effects if they are amplified through positive feedback. Audio feedback is a well known example of this process. What is, perhaps, less well appreciated is that mutually dependent deviation-amplifying processes can cause qualitative changes in the phenomenon of interest. A classic example is the phenomenon of a run on a bank : as people withdraw money in bulk, the likelihood of bank insolvency increases thus causing more people to make withdrawals. The qualitative change at the end of this positive feedback cycle is, of course, the bank going bust.
Maruyama also draws attention to the fact that the law of causality – that similar causes lead to similar effects – needs to be revised in light of positive feedback effects. To quote from his paper:
A sacred law of causality in the classical philosophy stated that similar conditions produce similar effects. Consequently, dissimilar results were attributed to dissimilar conditions. Many scientific researches were dictated by this philosophy. For example, when a scientist tried to find out why two persons under study were different, he looked for a difference in their environment or in their heredity. It did not occur to him that neither environment nor heredity may be responsible for the difference – He overlooked the possibility that some deviation-amplifying interactional process in their personality and in their environment may have produced the difference.
In the light of the deviation-amplifying mutual causal process, the law of causality is now revised to state that similar conditions may result in dissimilar products. It is important to note that this revision is made without the introduction of indeterminism and probabilism. Deviation-amplifying mutual causal processes are possible even within the deterministic universe, and make the revision of the law of causality even within the determinism. Furthermore, when the deviation-amplifying mutual causal process is combined with indeterminism, here again a revision of a basic law becomes necessary. The revision states:
A small initial deviation, which is within the range of high probability, may develop into a deviation of very low probability or more precisely, into a deviation which is very improbable within the framework of probabilistic unidirectional causality.
The effect of positive feedback can be further amplified if the variable of interest is made up of several interdependent (rather than independent) effects. We’ll look at what this means next.
Interdependence, not independence
Typically we invoke probabilities when we are uncertain about outcomes. As an example from project management, the uncertainty in the duration of a project task can be modeled using a probability distribution. In this case the probability distribution is a characterization of our uncertainty regarding how long it is going to take to complete the task. Now, the accuracy of one’s predictions depends on whether the probability distribution is a good representation of (the yet to materialize) reality. Where does the distribution come from? Generally one fits the data to an assumed distribution. This is an important point: the fit is an assumption – one can fit historical data to any reasonable distribution, but one can never be sure that it is the right one. To get the form of the distribution from first principles one has to understand the mechanism behind the quantity of interest. To do that one has to first figure out what the quantity depends on . It is hard to do this for organisational phenomena because they depend on several factors.
I’ll explain using an example: what does a project task duration depend on? There are several possibilities – developer productivity, technology used, working environment or even the quality of the coffee! Quite possibly it depends on all of the above and many more factors. Further still, the variables that affect task duration can depend on each other – i.e. they can be correlated. An example of correlation is the link between productivity and working environment. Such dependencies are a key difference between Normal and power law distributions. To quote from the paper:
The difference lies in assumptions about the correlations among events. In a Gaussian distribution the data points are assumed to be independent and additive. Independent events generate normal distributions, which sit at the heart of modern statistics. When causal elements are independent-multiplicative they produce a lognormal distribution (see this paper for several examples drawn from science), which turns into a Pareto distribution as the causal complexity increases. When events are interdependent, normality in distributions is not the norm. Instead Paretian distributions dominate because positive feedback processes leading to extreme events occur more frequently than ‘normal’, bell-shaped Gaussian-based statistics lead us to expect. Further, as tension imposed on the data points increases to the limit, they can shift from independent to interdependent.
So, variables that are made up of many independent causes will be normally distributed whereas those that are made up of many interdependent (or correlated) variables will have a power law distribution, particularly if the variables display a positive feedback effect. See my posts entitled, Monte Carlo simulation of multiple project tasks and the effect of task duration correlations on project schedules for illustrations of the effects of interdependence and correlations on variables.
Wrapping up
We’ve looked at a couple of general mechanisms which can give rise to power laws in organisations. In particular, we’ve seen that power laws may lurk in phenomena that are subject to positive feedback and correlation effects. It is important to note that these effects are quite general, so they can apply to diverse organizational phenomena. For such phenomena, any analysis based on the assumption of Normal statistics will be flawed.
Most management theories assume simple cause-effect relationships between managerial actions and macro-level outcomes. This assumption is flawed because positive feedback effects can cause qualitative changes in the phenomena studied. Moreover, it is often difficult to know with certainty all the factors that affect a macro-level quantity becasues such quantities are typically composed of several interdependent factors. In view of this it’s no surprise that managerial actions sometimes lead to unexpected extreme consequences.
Interdependence, not independence
Typically we invoke probabilities when we are uncertain about outcomes. As an example from project management, the uncertainty in the duration of a project task can be modeled using a probability distribution. In this case the probability distribution is a characterization of our uncertainty regarding how long it is going to take to complete the task. Now, the accuracy of one’s predictions depends on whether the probability distribution is a good representation of (the yet to materialize) reality. But where does the distribution itself come from? Generally one fits the data to an assumed distribution. This is an important point: the fit is an assumption – one can fit historical data to any reasonable distribution, but one can never be sure that it is the right one. To get the form of the distribution from first principles one has to understand the mechanism behind the quantity of interest. To do that one has to first figure out what the quantity depends on . It is hard to do this for organisational phenomena, which generally cannot be studied in controlled conditions.
To take a concrete example: what does a project task duration depend on? Developer competence? Technology used? Autonomy? Quality of the coffee?? Quite possibly it depends on all of the above. But even further, the variables that make up the quantity of interest can depend on each other – i.e. the can be correlated. This is a key difference between Normal and power law distributions. To quote from the paper:
The difference lies in assumptions about the correlations among events. In a Gaussian distribution the data points are assumed to be independent and additive. Independent events generate normal distributions, which sit at the heart of modern statistics. When causal elements are independent-multiplicative they produce a lognormal distribution (see this paper for examples drawn from science), which turns into a Pareto distribution as the causal complexity increases. When events are interdependent, normality in distributions is not the norm. Instead Paretian distributions dominate because positive feedback processes leading to extreme events occur more frequently than ‘normal’, bell-shaped Gaussian-based statistics lead us to expect. Further, as tension imposed on the data points increases to the limit, they can shift from independent to interdependent.
So, variables that are made up of many independent causes will be normally distributed whereas those that are made up of many interdependent (or correlated) variables will have a power law distribution, particularly if the variables display a positive feedback effect. See my posts entitled, Monte Carlo simulation of multiple project tasks and the effect of task duration correlations on project schedules for illustrations of the effects of interdependence and correlations on variables.
Scientific management theories assume a simple cause-effect relationship between managerial actions and macro-level outcomes. In reality however , it is difficult to know with certainty all the factors that affect a macro-level quantity; it is typically influenced by several interdependent factors. In view of this it’s no surprise that simplistic prescriptions hawked by management gurus and bestsellers seldom help in fixing organisational problems.
On the relationship between projects and project managers
Introduction
Those who run projects often spend a large part of their waking hours working or thinking about work. It is therefore no surprise that the self images and identities of such individuals are affected (if not defined) by their work roles. In a sense, their identities are colonized (in the sense of “taken over” or “largely defined”) by the project and the larger, permanent organization which hosts the project. A paper entitled, Who is colonizing whom? Intertwined identities in product development projects, by Thomas Andersson and Mikael Wickelgren explores this issue via a longitudinal case study that was carried out within new product development teams at Volvo. This post is a summary and review of the paper.
From the title of the paper it is evident that the identity issue is more than just a simple “the project leader (or team’s) identity is defined by project work” argument . Indeed, those who lead product development projects are themselves involved in creating at least three identities: those of the product, project and organization. Further, as I have pointed out in my post on project management in post-bureaucratic organizations, there are contradictions in the way in which project management operates. On the one hand it is seen as a means to direct innovative efforts (such as product development initiatives); on the other it is an essentially top-down, bureaucratic means of control. Project teams often operate in such contradictory, tension-filled environments. Although, most project leaders believe they work on projects by choice, it could be that the not-so-subtle pressures of expectation and social/ professional norms force the choice upon them.
However, as the authors point out, identity construction isn’t enough to explain why folks are willing to work insane hours; there’s something more going on. Indeed there is research that supports the notion that employees identities are moulded by organizations to suit organizational ends – in other words, employees identities are colonized by organisations. Andersson and Wickelgren suggest that the process of colonization isn’t as straightforward as it seems because employees often actively seek demanding roles. So, who is colonizing whom? Both parties are complicit in the colonization process. The main aim of the authors is to describe identity construction processes in project work with a focus on how, via the process proving their competence in project work, project leaders form their own self identities.
My review follows the format of the paper: I’ll begin with an overview of the relevant conceptual and theoretical background and then get into the case study.
Identity construction in project management
Individual identities are defined by how people relate to (professional and social) situations. The process of identity construction is an ongoing process of making sense of situations from a personal perspective. An individual is typically subject to many different identities at an aggregate level – for example the professional identity of a project manager, the identity of a parent etc. These can be thought of as certain norms or ways in which people are expected to behave. Individuals identify with aspects of these roles and act them out, thus integrating them into their own (self) identities. The point is that one’s professional identity is a part of one’s self identity.
The process of identity construction is a discursive one: i.e. it depends on how the situations in which the individual finds himself or herself unfold. In this connection the authors mention two important concepts, identity work and identity regulation. The first is the ongoing process of identity formation (and reformation) through interaction with the situation at hand (which could be a project, say). The second refers to the norms and rules, or the ways in which people are expected to behave in situations (the explicit norms and rules of project management, for instance). It is clear that identity regulation – by laying down appropriate behaviours – can have a “colonizing effect” on people’s identities. The authors make the point that even identity work can have an implicit colonizing effect – an example would be where project leaders identify with their work to such an extent that they go above and beyond the call of duty.
The increasing projectisation of organisations means that many individuals spend a large part of their work hours in a project environment. As such it is inevitable that this will affect their self-identity. In a fascinating paper, Lindgren and Packendorff pointed out that there are certain commonly accepted ways of relating to and making sense of project situations. For example – a project is seen as demanding higher levels of professionalism and loyalty than “normal” organizational work. Such norms constrain choices of those involved in projects. Once signed up, one has to behave in certain accepted ways. The authors make the point that there are very few empirical studies that look into how people handle such a “projectified reality.”
Several researchers have recognized the paradoxical nature of project work. Project-based management is touted as a means to loosen the hold of bureaucratic management structures. However, project management in practice tends to be riddled with (pointless?) bureaucratic procedures. As another example, projects are seen as a means to accelerate organizational learning – by doing new things under controlled, time-bound conditions. Yet, the reality is that when projects are in progress, organisations are loathe to spend time on capturing knowledge. The focus is always on the immediate deliverables rather than longer term learning. Given this, it is no surprise that individuals too, would rather focus on their next project than reflect on what happened on the previous one. As the authors put it:
…project managers seem ambivalent about their ‘professional identity’; they both aspire to it and resist it. Because of the lack of opportunities for reflection and learning, project workers often seek higher positions in future projects as their reward, with the result that their careers become a series of endless projects requiring increased responsibility and commitment. Emergency situations and problems that arise owing to these time and resource constraints are resolved by heroic actions that gradually become taken-for granted solutions.
It’s a sad commentary on the profession, but I reckon that we, as practitioners, are at least partly to blame.
Project work-life balance
Projects usually operate under tight budgetary and time constraints. Even if one can find more money to throw at a project, it is often impossible to buy more time. As a result those who work on projects often end up working overtime – “doing whatever it takes” to finish the work. But as the authors point out:
‘Doing whatever it takes’ is a very abstract commitment that is hardly measurable since basically it is a social construction dependent on the project leaders’ sense of duty and the external pressures for heroic actions. The dark side of this commitment means long working hours with the inevitable risk of burnout, stress and work/life balance difficulties, all of which may lead to problems with health, general well-being, and family life. The potential damage is as real for the project workers as it is for their organizations.
But it’s even worse because this destructive type of “heroic behaviour” is generally seen as distinguishing committed workers from less committed ones. The authors claim that this goes beyond specific organisations; it is a consequence of projectisation of society in general.
The case study
The qualitative data presented in the case study was gathered by the authors over two periods: 1998-2001 and 2007. In the intervening period, the authors stayed in touch with those in the organisation (Volvo Car Company), but did not actively gather data. Such a longitudinal study (over a long period) enables researchers to study how attitudes evolve over time. The methodology of the study is best described in their own words:
We studied projects managers who were jointly running new car projects at Volvo Car Corporation (VCC). In addition to direct observations, we video-taped 100 hours of project management meetings and audio-taped individual interviews with all participating project leaders. Our combination of observations and interviews allowed us to observe the practice and everyday lives of the project leaders and to discuss the observations with the interviewees. Thus we were able to observe the project practice closely. In 2007, we interviewed some people from the initial round of interviews who still worked in new car projects. Using this wealth of empirical material, our focus here is on the multi-layered aspects of identity regulation and identity work, especially in terms of colonization, in the studied setting.
The project leaders enjoyed a high status within the company and were often seen as “company heroes, but only as long as their projects succeeded. This created a tremendous pressure to succeed thus making the heroic approach to project management almost inevitable.
Long hours come with the territory
Working long hours is often seen as a hallmark of a dedicated project manager. Further, in many organisations (such as the one studied by the authors) there was the expectation that project managers would sacrifice their own time for the good of the project. As one project leader explained to the authors:
I work all the time! Weekends, evenings…Before Christmas I picked up my husband at a Christmas party in the evening, and then I went back to work and stayed there until midnight. Still, I met a colleague on Saturday morning and was able to do some more work before we left for Christmas. That is typical in my work. I haven’t time for the simplest things in my private life.
The authors make the point that even if a project leader could finish his/her work within a normal 40 hour work week, others would still question their commitment if they did not work overtime. Further, if the project did fail, the failure would almost certainly be attributed to the lack of commitment. Project leaders are thus under pressure to work overtime, whether it is needed or not. This is reflected in another comment by a project leader, about what happens between projects:
The period between projects is tough. It takes time to come down. In the beginning it is hard to accept that working 40 hours a week is not the same as having a half-time job, but that is the feeling. […] I have accepted that there are no interesting jobs where you work 40 hours a week, but I think it might be possible to stop at 60 hours a week…
We see that although unreasonable demands are being made on project leaders, they accede to the demands – or even welcome them. So, who is colonizing whom?
Parallel identity construction
The answer to the question in the previous paragraph is complicated by the fact that the project managers who participated in the study wielded considerable influence over the product they were creating. Indeed, this was the intent of the company. That this is so is illustrated by the remarks of an HR director who was involved in the selection of a project leader:
[the candidate] was, along with his competence regarding car development, chosen because he was an almost perfect customer targeted for the V70….Putting him on the management team of the new car project gave him an opportunity to develop the perfect car that satisfied his lifestyle, and the company got the intended car developed. We also used him as an example of our projected customer in a part of our marketing campaign for the V70.
So, selection for prized positions within the company depended on the technical competence and lifestyles of the candidates. In turn, the chosen ones had an opportunity to stamp their personality (identity?) on the product they created. Identities of people, projects and products were indeed entwined.
Discussion
The authors note that, once selected, project leaders were given considerable autonomy in running their projects. This included the freedom to make choices that influenced the product. Seen in this light, project leaders could stamp their identity on the products they were involved in creating. However, there were limits to their independence. After all, project leaders depended on the organisation for their livelihoods. Furthermore, their independence was constrained by organizational rules and norms.
Taking another view, one could view the behaviour of the project leaders as being self imposed in the sense that the long hours they put in could be seen as some kind of an addiction to work. Workaholism is an apt term here, I suppose. At first, the desire to become project leaders spurred them to work hard and once the position was attained they felt the desire to work harder still, possibly to prove that they were worthy of the trust reposed in them by the organisation.
Taking yet another view, one could say that the project leaders had limited choices in both their private and professional lives. On the one hand, there are professional expectations from the company and on the other, expectations from family and friends. Once the individual chose to become a project leader, the choices on offer in both spheres were limited by the choice they made and their personal priorities. All the project leaders interviewed gave their projects priority over all other aspects of their lives. This isn’t surprising because the selection process ensured it. Nevertheless, it does imply that the project leaders accepted that the organisation formed a major part of their self-identities.
It has to be acknowledged that because of their interest in cars, the project leaders were happy to work insane hours. However, equally, the company consciously exploited this interest to the extent that the project leaders believed the project to be the most important aspect of their lives.
Conclusions
Several researchers have suggested that organisations regulate individual identities in a manner that aligns them with organizational objectives (see this paper by Alvesson and Wilmott, for example). At first sight, the foregoing discussion is a case in point. Yet, to some extent, the project leaders in the study believed they had free will – that they made the choices they did because they wanted to. But in the end, the project (and organisation) “wins”. As the authors put it:
To some extent, the project leaders knew they were subjects of control, colonization, and regulation, and yet they chose this career path with full recognition of the consequences for their work/life balance. Their choice meant accepting long workdays and potential emotional and psychological damage in exchange for professional status, job fulfilment, and high compensation. The colonization had consequently moved beyond organizational controland corporate influence. The project leaders were colonized by the projectified society,a situation which made them aspire to the core constructions of the project management..
I suspect that many project managers – particularly those working on high profile projects within their organisations – will find themselves agreeing with the authors. Most of us choose to work on ever more challenging projects to further our professional experience, “make a difference” or even “influence the product”. Regardless of our motives, we generally believe that we make the choice voluntarily. The question is: is this true?
Eight to Late 