Archive for the ‘Project Management’ Category
Do project managers learn from experience?
Do project managers learn from their experiences? One might think the answer is a pretty obvious, “Yes.” However in a Harvard Business Review article entitled, The Experience Trap, Kishore Sengupta, Tarek Abdel-Hamid and Luk Van Wassenhove suggest the answer may be a negative, especially on complex projects. I found this claim surprising, as I’m sure many project managers would. It is therefore worth reviewing the article and the arguments made therein.
The article is based on a study in which several hundred experienced project managers were asked to manage a simulated software project with specified goals and constraints. Most participants failed miserably: their deliverables were late , over-budget and defect ridden. This despite the fact that most of them acknowledged that the problems encountered on the simulations were reflective of those they had previously seen on real projects. The authors suggest this indicates problems with the way project managers learn from experience. Specifically:
- When making decisions, project managers do not take into account consequences of prior actions.
- Project managers don’t change their approach, even when it is evident that it doesn’t work.
The authors identify three causes for this breakdown in learning:
- Time lags between cause and effect: In complex projects, the link between causes and effects are not immediately apparent. The main reason for this, the authors contend, is that there can be significant delays between the two – e.g. something done today might affect the project only after a month. The authors studied this effect through another simulated project in which requirements increased during implementation. The participants were asked to make hiring decisions at specified intervals in the project, based on their anticipated staffing requirements. The results showed that the ability of the participants to make good hiring decisions deteriorated as the arrival lag (time between hiring and arrival) or assimilation lag (time between arrival and assimilation) increased. This, the authors claim, shows that project managers find it hard to make causal connections when delays between causes and effects are large.
- Incorrect estimates: It is well established that software projects are notoriously hard to estimate (see my article on complexity of IT projects for more on why this is so). The authors studied how project managers handle incorrect estimates. This, again, was done through a simulation. What they found was participants tended to be overly conservative when providing estimates even when things were actually going quite well. The authors suggest this is an indication that project managers attempt to game the system to get more resources (or time), regardless of what the project data tells them.
- Initial goal bias: Through yet another another simulation, the authors studied what happens as project goals change with time. The simulation started out with a well-defined initial scope which was then changed some time after the project started. Participants were not required to reevaluate goals as scope changed, but that avenue was open to them. The researchers found that none of the participants readjusted their goals in response to the change, thus indicating that unless explicitly required to reevaluate objectives, project managers tend to stick to their original targets.
After discussing the above barriers to learning, the authors provide the following suggestions reduce these:
- Provide cognitive feedback: A good way to understand causal relationships in complex processes is to provide cognitive feedback – i.e feedback that clarifies the connection between important variables. In the simulation exercise involving arrival / assimilation delays, participants who were provided with such feedback (basically graphical displays of number of defects detected vs time) were able to make better (i.e. more timely) staffing decisions.
- Use calibrated model-based tools and guidelines: The authors suggest using decision support and forecasting tools to guide project decision-making. They warn that these tools should be calibrated to the specific industry and environment.
- Set goals based on behaviours rather than performance: Most project managers are assessed on their performance – i.e. the success of their projects. Instead, the authors suggest setting goals that promote specific behaviours. An example of such a goal might be the reduction of team attrition. Such a goal would ensure that project managers focus on things such as promoting learning within the team, protecting their team from schedule pressure etc. This, the logic goes, will lead to better team cohesion and morale, ultimately resulting in better project outcomes.
- Use project simulators: Project simulations provide a safe environment for project managers to hone their skills and learn new ones. The authors cite a case where introduction of project simulation games significantly improved the performance of managers on projects, and also lead to a better understanding of dynamic relationships in complex environments.
Although many of the problems (e.g. inaccurate estimates) and solutions (e.g. use of simulation and decision support software) discussed in the article aren’t new, the authors present an interesting and thought-provoking study on the apparently widespread failure of project managers to learn from experience. However, for reasons which now I outline, I believe their case may somewhat overstated.
Regarding the research methodology, I believe their reliance on simulations limits the strength, if not the validity, of their claims. More on this below:
- Having participated in project simulations before, I can say that simulators cannot simulate (!)important people-related factors which are always present in a real project environment. These include factors such as personal relationships and ill-defined but important notions such as organisational culture. In my experience, project managers always have to take these into account when making project decisions.
- Typically many of the important factors on real projects are “fuzzy” and have complex dependencies that are hard to disentangle. Simulations are only as good as the models they use, and these factors are hard to model.
On the solutions recommended by the authors:
- I’m somewhat sceptical about the use of software tools to supports decision making. In my experience, decision support tools require a fair bit of calibration, practice and (good) data to be of any real use. By the time one gets them working, one usually has a good handle on the problem any way. They’re also singularly useless when extrapolated to new situations – and projects (almost by definition) often involve new situations.
- Setting behavioural goals is nice in theory, but I’m not sure how it would work in practice. Essentially I have a problem with how a project manager’s performance will be measured against such goals. The causal connection between a behavioural goal such as “reduce team attrition” and improved project performance is indirect at best.
- Regarding simulators as training tools, I have used them and have been less than impressed. It is very easy to make a “wrong” decision on a simulator because information has been hidden from you. In a real life situation, a canny project manager would find ways to gather the information he or she needs to make an informed decision, even if this is hard to do. Typically, this involves using informal communication modes and generally keeping ear to the ground. The best project managers excel at this.
So, in closing, I think the authors have a point about the disconnect between project management practice and learning at the level of an individual project manager. However, I believe their thesis is somewhat diluted because it is based on the results of simulated project games which are limited in their ability to replicate complex, people-related issues that are encountered on real projects.
The Dunning-Kruger effect and its relevance to project management
I’ll start with a story that may sound familiar to some of you.
A project team member – let’s call him Ernest – appears to be a major asset to the team. He is enthusiastic, volunteers to do stuff others don’t want to do and is always (seemingly) on the ball. The problem is most of his work is shoddy, riddled with errors and has to be redone. Worse, this is starting to have a negative knock-on effect on other deliverables. Other team members are having to clean up the mess and are beginning to resent it. Yet Ernest is blissfully unaware of the repercussions of his earnest efforts. By his estimation, he’s doing a fine job and, quite naturally, expects to be rewarded for it.
It is clear the project manager has to do something about Ernest. Trouble is she can’t. She has no say in the composition of his team, and the functional manager to whom Ernest reports reckons that Ernie is the best thing that happened to the company in a long time. Our PM’s in a pickle; one which I reckon isn’t an uncommon one.
There are two factors at work here:
- Ernest thinks he’s (way) more competent than he actually is.
- He isn’t aware of his shortcomings.
This story is an illustration of the Dunning-Kruger Effect, so named after the authors of this paper, published in the Journal of Personality and Social Psychology in 1999. In the paper the authors demonstrated, through a series of experiments, that less skilled individuals tend to:
- Overestimate their competence.
- Fail to recognise the extent of their lack of skills.
The paper suggests that improving the skills of such individuals not only increases their competence, but also helps them recognise and acknowledge their prior lack of skills – i.e. it improves their ability for self-assessment.
I should mention that not all authors agree with Dunning and Kruger. However, in a recent paper, Dunning and others appear to address many criticisms that were levelled at the original work. So the current academic consensus seems to be that the Dunning-Kruger effect is real.
So, going back to my original story, what can the project manager do about Ernest? Remember, Ernie can’t be relieved of his project duties because he has his manager’s backing.
The PM has a few options which I outline below:
- Provide Ernest with honest feedback. This has to be done with care as Ernest reckons he’s doing a great job. The PM should also be sure to provide Ernest with positive feedback where possible – compliment him on his enthusiasm, readiness to take on tasks etc.
- Channel Ernest’s positive qualities to good use. One way our PM could do this is to position less critical tasks as important, and suggest (or gently insist!) that Ernest take responsibility for them. This needs to be done carefully, as the PM needs to ensure that Ernest remains motivated.
- Suggest concrete actions that might help Ernest improve the quality of his work. This option is usually considered to be a non-starter given that there’s no time (or budget) for training in the middle of a project. However, there are a few other ways to achieve this: informal coaching, mentoring for example. These, however, are difficult to put into action because it is difficult to find time to coach or mentor while a project’s in progress. Besides, Ernest has to be willing to acknowledge and accept his shortcomings.
At all times, the PM has to be cognisant of the effect of the effect her actions (or inaction, for that matter!) on team morale. Plummeting morale is the last thing she needs in the middle of a project.
I’m sure most project managers would have had first-hand experience of dealing with individuals like Ernest. If so, they’ll know that fixing the problem is hard, especially if the project manager has no authority over team composition. Although I’ve suggested some strategies to deal with such individuals, I acknowledge that the solutions can be difficult, time consuming and expensive to implement; especially in stressed-out project environments.
As Dunning points out in this article, we’re strangers to ourselves. So we’re all potential victims of this effect (yes, I realise that includes me too!). Having said that, I leave you now to ponder this question: how do you rate your competence as a project manager?
On the intrinsic complexity of IT projects
Several years ago Fredrick Brooks wrote his well known article, No Silver Bullet , in which he explained why software development is intrinsically hard. I believe many of the issues that make software development inherently difficult have close parallels in IT project management – parallels which apply even in projects that don’t involve much writing of code. In this post I look at Brooks’ article from the perspective of an IT project manager, with a view to gaining some insight into why managing IT projects is hard.
Brooks defines the essence of a software entity as, “…a construct of interlocking concepts: data sets, relationships among data items, algorithms and invocations of functions…” This construct is abstract; that is, it has many different representations or implementations. A line later he states, “…I believe the hard part of building software to be specification, design and testing of the construct, not the labor of representing it and testing the fidelity of the representation…” The connection with project management (especially, IT project management) is immediately apparent: the hard part in many projects is figuring out what needs to be done, not actually doing it. Put another way, requirements, rather than implementation, are the key to successful projects. Project management methodologies deal with implementation reasonably well, but have little to say on how requirements should be elicited. Why is this so? To answer this it is helpful to take a closer look at the parallels between inherent properties of software entities (as elucidated by Brooks) and IT projects.
According to Brooks, the essence of software systems (as defined above) is irreducible – i.e. it cannot be simplified further. This irreducible essence, he claims, has the following inherent properties: complexity, conformity, changeability and invisibility. These characteristics are present in any non-trivial software entity. Furthermore – and this is the crux of the matter- any advances in software engineering or development methodologies cannot, in principle, solve difficulties that arise from these inherent properties. I discuss these properties and some of their consequences below, pointing out the very close connections with IT project management.
- Complexity: Brooks describes software entities as complex in that no two parts are alike. This complexity increases exponentially with entity size. Deriving from this complexity, he says, are issues of difficulty of communication among team members leading to product flaws, cost overruns and schedule delays. This should sound extremely familiar to IT project managers.In an earlier post I looked into definitions of project complexity. In a nutshell, there are two dimensions of project complexity: technical and management (or business) complexity. Brooks defines complexity in technical terms, as he is concerned with building software. However, in large part the complexity he talks about arises from business complexity (or complex user requirements). The latter is often what makes IT projects difficult, even when there’s not much actual code cutting involved. Furthermore, this characteristic is intrinsic to all but the most trivial IT projects.
- Conformity: software entities must conform to constraints of the environment into which they are introduced. To paraphrase Brooks, “…These constraints are often arbitrary, forced without rhyme or reason by the many human institutions and systems to which interfaces must conform…” This too has obvious parallels with IT project management – the deliverables of any IT project have to fit into the environment they are intended for. This fit has to be at the technical level (eg: interfaces) but also at the business level (eg: processes). I’m sure many IT project managers would agree that the technical and business constraints imposed on them are often arbitrary (but compliance is always mandatory!). So we see that this characteristic, too, is intrinsic to most business and technical environments in which projects are conceived and implemented.
- Changeability: Brooks describes the software entity as being “…constantly subject to pressures for change…” This, he reckons, is partly because software embodies function (i.e. it does something useful) and partly because it is perceived as being easy to change (italics mine). One would think twice (or many more times!) before asking for large-scale changes to a building that has already been erected, but there’s considerably less restraint shown when asking for major changes to software. This, again, has parallels with IT project management – shifting requirements are the norm, despite the high cost in terms of time, if not money. Change control processes are put in place to dampen this tendency, but it is ubiquitous nonetheless.
- Invisibility: According to Brooks, software entities are, “… invisible and unvisualizable…,” in all but the simplest cases. Unlike the floor plan of a building, which helps project personnel visualise the finished product, no pictorial model is available to software builders. Sure, modelling techniques do exist, but they do not (and cannot!) depict the complexity of a non-trivial software system in any meaningful way. This, says Brooks, “…not only impedes the process of design within one’s mind, it severely hinders communication among minds…” Here too, the parallels with IT project management are clear – communicating the requirements of the project would be so much simpler if there were a visual representation of what’s required. If Brooks is right, though, a search for such a representation is akin to the search for the philosopher’s stone.
Yet Brooks is not a pessimist. Towards the end of his article, he mentions some techniques that can alleviate some of the essential difficulties of building software. These include: rapid prototyping and iterative / incremental approaches. Grow software, he says, instead of building it. Such an approach, which incorporates frequent interactions between users and developers, reduces risk associated with missed or misunderstood requirements and clarifies design in small, digestible steps. This is also good advice for IT project managers, as I’ve pointed out in a previous post.
In the last section of his article, Brooks states, “The central question of how to improve the software centers, as it always has, on people” and then goes on to discuss how talented designers (or architects) can greatly reduce the essential difficulties in building software. I believe the parallel here is between designers and project managers. A talented project manager can make all the difference between the success and failure of an IT project. What are the attributes of a talented project manager? Well, that’s a topic for another post, but I think most of us who’ve worked in the field can recognise a good project manager when we see one.
Brooks believes the essential difficulties associated with building software make silver bullet solutions impossible, in principle. The parallels outlined above lead me to believe that the same applies to project management. Methodologies may help us along the road to project success (and some do so more than others! ), but there are no silver bullets : managing IT projects is intrinsically hard.

