Assumptions of competence

In a recent post, I wrote: “…most folks don’t really need to be managed because they’re competent at what they do, and go about doing their jobs in a generally diligent manner.”

On reading this an old friend wrote to me saying, “I am sincerely of the opinion that most people are not competent at their jobs…”  And a bit later in the same message, “If you are looking for quality and excellence, don’t expect to find it in business and corporate culture.”

Incidentally, he is an independent consultant with over fifteen years experience, much of it gained in  large corporations . His observations regarding the general lack of competence and quality in the business world must, therefore,  be taken seriously.  Nevertheless, I reckon he’s at least partly off the mark: I believe it behooves managers to  begin with the assumption that people are competent, and that they want to do high-quality work.

Let me start my case with three stories which may sound familiar:

Jim is a developer at the regional office of a large multinational. He is overloaded with work, typically working on at least two (often three) major projects concurrently. As a consequence he cannot do justice to any of them.  It is clear that Jim will not meet the deadlines on any of the projects. Though it is clear that his situation has been caused by poor management, he’ll be the one carrying the can.

Tracy is an experienced database programmer working on a large project. She has worked on similar projects before, and is arguably the best person to provide technical input regarding the design and implementation of database program modules for the product. Yet, her manager insists that every suggestion she makes be approved by him prior to presentation to the team, often adding his two-cents to her designs.  Of late the team has noticed that Tracy has been unusually quiet during project meetings.

Sanjay has been working as an ERP adminstrator for a while.  He has the job well under control, and is looking to pick up some new skills. The company he works for has just purchased a large number of licenses for a major business intelligence platform, so there’s going to be plenty of work building new reports.   Sanjay knows this area is under-resourced: there’s only one person working on the new platform, right from metadata design to creating reports. Clearly, this person could use some help, and it’s a perfect opportunity for Sanjay to pick up new skills.  Sanjay approaches his manager for permission to get involved,  but the manager refuses outright.

Sooner or later…

Jim’s blamed for the failure of his project(s).

Tracy has lost interest in her job.

Sanjay’s administering his ERP system competently enough, but spends his (considerable) free time surfing the Net. He’s bored, and makes no effort to hide it.

To a casual onlooker it may appear that Jim, Tracy and Sanjay “are not competent at their jobs”, but that is a superficial observation. The real problem is that they are no longer motivated by their work. The basic reason for their demotivation is bad management. More specifically:

Jim’s expected to achieve the unreasonable or impossible.

Tracy isn’t empowered to make decisions that affect her work.

Sanjay isn’t given the opportunity to learn new skills.

Fact of the matter is, these folks want to succeed at their jobs and even go beyond  their job description, but they aren’t given the support, opportunity and / or the means to do so.

I did say my friend’s partially right, and he is: with a demotivated team, quality and excellence and all those wonderful things we’re supposed to strive for in the workplace aren’t going to happen.  The question is, who is responsible?  As Deming mentions in his management / quality classic, Out of The Crisis, the fault lies largely with management.  I agree, but many don’t.  I’d be  interested in hearing what you think. Do let me know through your comments.

A note on bias in project management research

Project management research relies heavily on empirical studies – that is, studies that are based on observation of reality. This is necessary because projects are coordinated activities involving real-world entities:  people, teams and organisations.  A project management researcher can theorise all he or she likes, but the ultimate test of any theory is, “do the hypotheses agree with the data?”  In this, project management is no different from physics: to be accepted as valid, any theory must agree with reality. In physics (or any of the natural sciences), however, experiments can be carried out in controlled conditions that ensure objectivity and the elimination of any extraneous effects or biases. This isn’t the case in project management (or for that matter any of the social sciences). Since people are the primary subjects of study in the latter, subjectivity and bias are inevitable. This post delves into the latter point with an emphasis on project management research.

From my reading of several project management research papers, most empirical studies in project management proceed roughly as follows:

1. Formulate a hypotheses based on observation and / or existing research.
2. Design a survey based on the hypotheses.
3. Gather survey data.
4. Accept or reject the hypotheses based on statistical analysis of the data.
5. Discuss and generalise.

Survey data plays a crucial role in empirical project management studies. This pleads the question: Do researchers account for bias in survey responses? Before proceeding, I’d like to clarify the question with with an example. Assume I’m a project manager who receives a research survey asking questions about my experience and the kinds of projects I have managed. What’s to stop me from inflating my experience and exaggerating the projects I have run? Answer: Nothing! Now, assuming that a small (or, possibly, not so small) percentage of project managers targeted by research surveys stretch the truth for whatever reason, the researcher is going to end up with data that is at least partly garbage. Hence the italicised question that I posed at the start of this paragraph.

The tendency of people to describe themselves in a positive light referred to as social desirability bias. It is impossible to guard against, even if the researcher assures respondents of confidentiality and anonymity in analysis and reporting. Clearly this is more of a problem when used for testing within an organisation: respondents may fear reprisals for being truthful. In this connection William Whyte made the following comment in his book The Organization Man, “When an individual is commanded by an organisation to reveal his innermost feelings, he has a duty to himself to give answers that serve his self-interest rather than that of The Organization.” Notwithstanding this, problems remains even with external surveys. The bias  is lessened by anonymity, but doesn’t completely disappear. It seems logical that people will be more relaxed with external surveys (in which they have no direct stake), more so if they are anonymous. However, one cannot be completely certain that responses are bias-free.

Of course, researchers are aware of this problem, and have devised techniques to deal with it. The following methods are commonly used to reduce social desirability bias

1. The use of scales, such as the Marlowe-Crowne social desirability scale, to determine susceptibility of respondents to social desirability bias. These scales are based on responses to questions that represent behaviours which are socially deemed as desirable, but at the same time very unlikely. It’s a bit hard to explain; the best way to understand the concept is to try this quiz. A recognised limitation of do not distinguish between genuine differences and bias. Many researchers have questioned the utility of such scales on other grounds as well- see this paper, for example.
2. The use of forced choice responses – where respondents are required to choose between different scenarios rather than assigning a numerical (or qualitative) rating to a specific statement. In this case, survey design is very important as the choices presented need to be well-balanced and appropriately worded. However, even with due attention to design, there are well-known problems with forced choice response surveys (see this paper abstract, for example).

It appears that social desirability bias is hard to eliminate, though with due care it can be reduced. As far as I can tell (from my limited reading of project management research), most researchers count on guaranteed anonymity of survey responses as being enough to control this bias. Is this good enough? May be it is, may be not: academics and others are invited to comment.

A scope management farce in five limericks

It began as some projects do,
with users who hadn’t a clue.
Their requirements
made no sense,
filling merely a page or two.

The PM,  he knew the score.
He asked the users for more.
They flatly declined
saying “We have no time,”
and booted him out the door.

The PM, now filled with dread,
went to the sponsor and said,
“We cannot proceed.”
The boss disagreed,
commanding him to press ahead.

The team, though flying blind,
worked hard (no time to unwind).
Built an app to the spec,
but the users said, “Heck,
this ain’t what we had in mind.”

The moral is clear to see:
With specs unclear or murky,
you’d do well to try
using techniques agile,
delivering frequently.

—

Some recent posts in my “five limericks” series are:

A cliche-ridden corporate crisis in five limericks
SOA what? A clarification for CIOs in five limericks
A cynic’s introduction to project management artefacts in five limericks
An IT system tragedy in five limericks