Strategic decision making

One of the most important occasions for managing risk is when a big decision has to be made. People will be looking for more information, asking about the implications of things that might happen, looking at alternative courses of action… all of which is likely to involve a finance professional.

One of the keys to promoting responsible instead of reckless decision-making is to make people aware of what is not known or cannot be controlled, and help them cope with that uncertainty. Clear and helpful presentation is crucial.

The following questions are designed to pick up some of the most common mistakes in big decision-making in organisations, and apply to business planning, business cases for projects, and all manner of other important decisions. They should be applicable regardless of your organisation’s particular approach to big decisions and should be common sense to most people, even if they are not always done consistently in practice.

They could be considered when tackling a big decision or when reviewing procedures, tools or templates for decision-making.

In other words, can decision-makers see what actions are involved in a proposal? For example, do we state the locations involved, the number of people, the technology, and so on?

This seems like an obvious suggestion, and how could anyone be expected to make an important decision if it is not clear what they are deciding to do? And yet, here are some common mistakes that you will probably recognise:

• Stating objectives, perhaps also with financial targets, but with no actions to support them.
• Blurring the line between what has a credible plan and what is just a goal at this stage.
• Not quantifying the extent of work to be done.
• Focusing on the value of achieving a goal rather than the credibility of the plan to achieve it.

For example, in a recent review of a development bank’s lending documents, it was noticeable that projects were often justified more on the basis that the problem to be solved was important than on the basis that the proposed project was a credible solution to the problem.

One major reason for not being clear about what is to be done is that details have yet to be worked out. This is a crucial form of uncertainty with proposals. It should be made clear what actions are proposed and what still needs to be worked out and perhaps might be decided later when more information is available.

Decisions are always between alternatives, but these might not be clearly stated or might be misleadingly stated. This weakness comes in different flavours. In particular, projects justified by the savings they will generate need to be clear about what is assumed will happen if the project does not go ahead. “Cheaper compared to what?” For example, if redundancies are being considered then the savings will not necessarily be the salaries currently paid because some people might have left anyway.

If two or more projects are being compared then one can be taken as the benchmark for the other or both can be compared to “carry on as usual”. Whichever approach is taken it needs to be the same for every cost and revenue item, and readers of a business case need to be told what was done. It may also be important to clarify what “carry on as usual” means, especially if other changes are already planned.

Quite often the alternative is uncertain because it is to wait and see if a better proposal comes along. Here again it helps to be open about this and give some information that might help to judge the prospects for this uncertain alternative. For example, property development companies need to have a good idea of what a typical good opportunity looks like and need to adjust their ideas as the economy changes.

At the very least we need to consider if each of the consequences of a particular course of action is important and if it is helpful or unhelpful. Ideally, we will use judgement, data and models to make carefully quantified predictions.

Too often predictions deal with planned costs and hoped-for achievements only.

That leaves unplanned costs and undesirable side-effects, including indirect effects, unstated. For example, redundancies may save salaries directly but if the work those people are doing is not cut too then someone will have to do it and, sooner or later, in some way, the costs will come back. Similarly, moving to a central office may save on rent and the extra travel costs for some employees will be met by them – in the short term. Longer term there will be extra costs that creep in, distributed and invisible, as people adjust.

Another dangerous mistake is to make a theoretical plan and estimate its cost then write a list of ‘risks’ and add up the cost of each risk multiplied by the probability of the risk occurring. Adding the total of these average risk impacts does not give you a risk adjustment. It just adds an amount that should have been included in the initial estimate. Risk is more about the extremes of outcomes than their statistical mid-point.

Strictly speaking it is not necessary to predict every consequence clearly. If you can see from the predictions that are easy to make that a plan is a good idea provided the other consequences are not very important and negative, then it may be enough to just consider if the other consequences are bad enough to make a difference.

However, precisely stated predictions using numbers are better than rough indications using quantitatively vague words like ‘large’ and ‘significant’.

Precise predictions should not be precise best guesses presented as reliable facts, and there are several ways to avoid this mistake. We can explain key points about how predictions were made, drawing attention to factors that were and were not considered, data and judgements used, assumptions made, and predictions that were particularly uncertain.

Numbers and graphics can be used to give predictions as ranges or mid-points with ranges, or even distributions. A list or matrix of predictions can be given, showing how a key result would vary with one or two key assumptions. The combined effect of many uncertain input estimates can be summarised using a Monte Carlo simulation.

For example, suppose that the resale value of some asset after five years is a key estimate required for a decision and you are 90% sure it will be between £190,000 and £390,000. How do you explain that? You could just put in an estimate of £300,000 and trust in rounding to convey your doubts. Alternatively you could say it will almost certainly be between £200,000 and £400,000, or just present the range as a graph so that readers can see the figure will be between just under £200,000 and just under £400,000 but the exact figures are not stated. These are just three of the possibilities using the numbers alone. Narrative and alternative summary predictions give you other options.

This type of disclosure is crucial to helping decision-makers appreciate the value of caution and of building learning and adaptation into plans.

Decisions should be based on information, ranging from statistics about the past to projections of the future, and all the input estimates that go into them. Decision-makers should be told where that information came from. If the estimates are based on judgements, then whose judgements were they? Where did that chart about the size of the market and its future growth come from?

Is there an explanation, at least brief, of how information was generated? For example, expert judgement can be gathered in various ways, from workshop guessing games to scientifically validated elicitation and de-biasing procedures. Even information from impressive-sounding external organisations is not necessarily reliable. It may be based on voluntary reporting, samples, or definitions designed to suit some vested interest.

In summary, the decision-support material should be clear about what is being proposed, what else could be done, what might happen in future and what those predictions are based on, who provided information, how that information was generated, and how accurate those predictions might be.

But these evaluation questions only tackle the final presentation of information designed to support big, strategic decisions. Of course it is also important to gather relevant information, develop plans, consider alternative futures, do calculations, consult appropriately and so on. But what a waste to do all the ground work and then fail to present it in a way that helps people make full use of it. The final presentation is important and usually less work to get right.

Also, this good presentation of uncertainty is a contribution to risk management that is embedded within the most important decision-making activities of the organisation. That surely makes it important.

Download pdf article:

• Strategic decision making
  Business & Management Magazine, Issue 259, November 2017

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