Choices and Decisions

We spend our lives making choices and deciding things - blue or black pen, accept the offer, buy or rent, walk or drive, meat or fish - so how come we are so bad at it? We can spend ages agonizing over a pointless choice, then jump to conclusions on something important without understanding the impact or consequences.

I believe our decisions are typically plagued by one of two fundamental mistakes: too much information and not enough information. A good decision needs to be a careful balance between heart and mind; focusing on one or the other will create issues. For instance, if I want to open a restaurant in a given neighbourhood, I could do go ahead based only on my desire to do this without realizing that there are already too many established restaurants there and it would be extremely unlikely that another would be able to survive without being extraordinary. That would be a foolish decision based on heart without mind.

On the other hand, if you just look at national statistics and discover that 60% of all restaurants and 70% of all new businesses fail within one year, no one would ever start anything.

Within the CMMI®, there is a process area called "Decision Analysis and Resolution" (DAR) which aims at rationalizing decisions and keeping trace of the analyses performed. Like a lot of CMMI, a superficial first reading would give the impression that the decision should be all brain, no heart. It would encourage you to research, measure, compare and document every aspect of a decision. This would apparently create a completely scientific approach to decisions, without any emotional content.

I believe that implementation is wrong.

DAR is frequently implemented at the project level. Many organizations see the level 2 process areas as being limited to project management (which is completely wrong, maybe a subject for a future entry here) and continue in that mind-set when looking at the next level.

I believe that implementation is wrong.

The main purpose of DAR is to formalize decisions so that they are not challenged or continuously revisited in the future.

I remember working for a division of a French multi-national when a representative of the mother company came to tell them about rationalizing the infrastructure and technology across the international organization. What they actually showed was that all non-French suppliers of services, tools or technologies were being replaced by French ones. This included the requirement to fly with Air France, even if this meant replacing a 1 hour flight between Brussels and Frankfort by a 4 hour flight with stop-over in Paris. This is the kind of stupid decision which is open to challenge and questioning and has a serious impact on management credibility - and it is not that uncommon. Most of us have come across a choice that was made strictly on emotional reasons (purchase from the manager's son in law, or the company we have always used rather than put it out to tender).

On the other hand, many decisions are made based on a purely rational, mathematical basis, which are just as wrong. A traditional error in this approach is the government (or company) decision to put something out to tender and buy from the cheapest bidder, without concern for the quality of the service being delivered. This is the approach which is responsible for all those projects which went 450% over budget and were delivered three years later (look up government contracts in your country for further details).

The more important a decision (bigger impact, risk, cost...), the more a clear structure needs to support the decision. I would expect to see DAR practices used systematically at the board or senior management level and regularly at the project level.

When deciding on mergers and acquisitions, management should have detailed and measured evidence on the probability of success; but that is not enough, if they want to make sure that the decision is not doomed, they also need to be able to demonstrate that they have seriously considered the reasons not to do it. The DAR approach requires a number of steps:

  • identify the decisions for which the approach needs to be formalized;
  • set up the decision criteria and mechanism to be used;
  • collect the data required for your selection criteria;
  • analyse the data according to the decision analysis mechanism (process, template, methodology...) selected;
  • make your decision;
  • and document all this so that, should the decision be challenged or questioned at a later date, you can demonstrate that it was done based on the best information available at the time.

The typical implementation of this approach is flawed in a number of ways. First the decisions requiring formalization are typically defined at the design, engineering or project level tasks instead of being based on the importance of the decision. You should formalize decisions that may involve a budget greater than X (money or work-hours) as well as formal decisions to bid on a contract, select a supplier, or collaborate with another organization. This means that the prime candidates for formalized decisions must be the board and senior management decisions and not just the project, design or engineering activities. Bizarrely, in many cases management places little control on major decisions, while forces project managers and team leaders to perform detailed analysis on minor ones.

Senior management must to be able to justify their choices if (when) challenged (running a company does not allow you to say "because I say so", you are responsible for the lives of many people).

The second common issue in the DAR implementation is the pseudo-scientific approach deduced from the idea that you need to identify the options and approaches to take. This frequently ends up being more than a sheet of paper with a list of reasons for and a list of reasons against -- or a fancy electronic form thereof. Listing the reasons why you should not want to do what you want to do is rarely a useful exercise, unless it is done in a formal, structured and managed way.

Salespeople know this and will happily help you fill in the list of pros and cons - or at least they will help you fill in one side of the list, leaving you to do the other on your own. You need to go a lot further in examining the reasons why a choice should not be made. A significant decision should be actively challenged, from every point of view.

If the decision has a sufficient impact, you need to consider it from a risk management point of view: what are the risks of getting this wrong? What would be the risks of not deciding this? What are the risks that we will regret this in 10 months or 10 years' time?

Of course, most people -- and that includes managers -- are not keen for others to consider that they might be wrong in their instinct, yet that is the basis for leadership.

If you do not accept the challenge, you are probably unsure of the result and expect failure. Therefore, it would be best if you were to organize the challenge directly and thoroughly as part of the decision process. Make sure your decision can stand up to emotional and data-based challenges before you invest too much in it.

There are a number of methods to facilitate intelligent decisions and make sure that choices are made for all the right reasons - financial and emotional - but these are rarely applied intelligently. Maybe management should consider investing in "decision training" for the higher levels of the hierarchy...

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