I’ve been looking forward to this fortnight’s post as it’s on a topic which intrigues me, but that I haven’t explored too much in the past. You see, we’re talking today about decision tables.
Decision tables are not panels of people who sit in judgement over a difference of opinion. Nor are they panels of wood standing on four legs at which people solve important dilemmas. Nor are they giant Ouiji boards that magically spell out an answer.
No, a decision table – a simple decision table – can be seen as a matrix that represents what the decision should be in a given scenario based on specific criteria. They are a way of converting business rules into processes, but also keeping the criteria themselves out of processes – so that processes can be clear and easily understood. Generally you will have two types of criteria in a decision table, down the furthest left column and along the top row, however it may be that you can be creative with the set out so that you could end up with three or four criteria.
It is obviously possible to have more than three or four factors in a decision-making scenario, however then you may need to leave decision tables behind and use a different type of decision support tool or algorithm (think Bayesian networks and decision trees). Hopefully not though; I have the idea in my head that in fact you can break down such complex decisions into a chain of decision tables and therefore be able to work through your problem (decision) in a clearly transparent way. This might be one idea that I have to explore on another day.
Although I’m trying to talk concept only and stay away from practical examples for another few posts yet, I think I’m going to have to make an exception today. Decision tables just sound confusing in the abstract, when in fact they are all about making decision making simpler.
Let’s use an example that fits today’s post itself (so that I don’t have to dream up anything too creative… it’s a public holiday here so I deserve a break!) and say that I need to be able to decide how to classify a concept for an organisation that specialises in organisational improvement.
Here’s my hypothetical decision table:
As you can see, there are three criteria that I am using in making the decision: potential possibilities, degree to which the possibilities have been explored, and relevance to interests. I think it’s pretty easy to see from the above decision table that I would classify a concept with infinite possibilities that has not been thought through properly yet and which is extremely relevant to organisational improvement will be classified as ‘intriguing’, whereas a concept with only some peripheral relevance to organisational improvement, limited application and lots of existing research will be ‘not particularly interesting’ at all!
What I find interesting about decision tables is that they are such a simple concept with such broad application and yet, in my experience, they can scare people.
I can see several reasons for this – and maybe they’re not too dissimilar to the general reluctance to document processes, procedures and reporting requirements.
1. The perception that it will be a lot of work.
2. The perception that putting the decision criteria in writing will show them up if or when they make the wrong decision.
3. The perception that they will do themselves out of a job.
Let’s address these one at a time.
1. I would agree that it always takes time and effort to undertake proactive instead of reactive thinking and that people struggle to push this type of work to the top of their priority list. However when you plan ahead of time, you have the best available knowledge at your fingertips to make the best decision you can with confidence, when a time-critical decision comes up.
2. Isn’t there value in learning from your mistakes? I see the big issue is where an organisation does NOT learn from its mistakes – and if it isn’t clear about why and when a decision was made that ended up being a mistake, how will it change things next time? Another issue that I see with taking an airy fairy approach to decision making is that not only might you repeat the same mistaken decision next time around, but you also miss a chance to learn more about your subject matter.
What we’re really talking about here is adaptive management. About setting up a framework in which adaptive management is understood and actually practised. If you think about it, this is how any body of knowledge is developed. The scientific method is based on hypothesising the best answer to a scenario given a certain set of assumptions and then testing it – and the results (whether the hypothesis was wrong or still a valid answer) improve the scientist’s understanding. The only difference between adaptive management and scientific research is that one is practised when circumstances force a hypothesis to be tested in less controlled circumstances, whereas the other is practised at the discretion of a scientist and often under the circumstances controlled by the scientist.
I think that as long as you are clear about the circumstances and reasons on which a decision is based and clear that you are making the decision based on the best knowledge available – albeit not full and perfect knowledge – no one should blame you if the decision ends up being wrong. You’ve just tested a hypothesis that now does not needed to be tested again – a different kind of win for your organisation!
3. This is always a tricky one as it’s often about the way people and their managers perceive the purpose of an organisation and a specific task. I can only talk about it from my perspective… Decision tables are decision SUPPORT tools, not decision MAKING tools. You cannot document everything, nor can you build intuition or an imagination into a system. Therefore, the same as for a process or procedure, if you put rigour around decision making criteria and so have a very clear picture ahead of time of the information you will need to make a decision and at what point you have considered something enough, you are likely to save time, save unnecessary work and effort and allow the experts to get on with exploring additional factors and nuances so as to truly make wonderful decisions in the future.
Before we finish up today it is probably important to mention how decision tables hook into an organisational model: decision tables are associated with processes. Imagine you are following a process to recruit a new team member and you get to the decision-making step: decide whether the candidate will be short-listed…
There’s your decision point, your decision making step where suddenly decision support tools come into their own and the process player is not left on their own, stranded and unaccountable. It is far more user-friendly that the decision-making step in this kind of process refers to a decision table or other decision support tool, rather than integrating a determination against decision criteria into the process itself.
But don’t just take my word for it. What do you think?
Do you have some good examples of where decision tables have helped your decision-making? And what other decision support tools have you used?