The design of decision making processes is often what differentiates the winners from the losers. So how good are the inputs to decision making at your organisation – is your process delivering successful outcomes?
We are biased towards relying on conventional approaches to research and data analysis to inform our decision making, all the more so as increasing amounts of data becomes more readily available and easier to analyse. The ability to be ‘rational’ and ‘logical’ are highly valued and considered key to getting organisational buy in to new initiatives. For example, a proposed new marketing initiative which cannot be supported by fact based research will likely not achieve the internal approval to proceed. However, there are some serious potential problems with relying solely on this approach:
- By definition data is historic. There is no guarantee that analysis of historic trends, even if data is ‘up to date’, will reflect future conditions.
- The aggregation of data and averaging affects can hide important insights. For example, there may be no ‘average’ customer. Your ideal target customer may be an outlier.
- Social context is key to data interpretation but this varies a lot and cannot be easily captured in a reliable systematic way.
- There is an implicit risk averseness in conventional data analysis. If there are issues with certain data availability and reliability it tends to be ignored.
- The complexity of the real world is not easily captured by data analysis. However, it can be tempting to accept easy answers which deliver what turn out to be false conclusions, based on and an overly simplistic analysis of a situation.
- The most efficient is favoured over the most effective because it is easier to measure. Quantitative factors have greater weight simply because they can be measured not because they are more important. For example, the popular trend towards moving call centres overseas often led to a disastrous reduction in the customer experience – ignored in decision making process because it could not be quantified. Social media advertising is more cost effective but does it always work better than conventional approaches?
- Even minor incorrect assumptions in calculations can dramatically affect the final conclusions.
- If your competitors are using the same source data and analytical approach they will come to the same conclusions. This will make differentiation more difficult to achieve and competition on price more likely.
- Market research is notoriously unreliable. People don’t always say what they think or do what they say. For example, the only reliable poll in an election is the exit poll – we can only rely on ‘revealed preferences’ ie what people actually do.
So what might you change to improve the chances of making the correct calls in your organisation decision making going forward ?
Some suggestions :
- Be less risk averse – try out novel approaches and ideas. Be open minded and be prepared to consider the counter intuitive. Create a culture which values creativity and embraces a ‘trial and error’ approach, within limits. Why something works may not be clear initially but the fact that it does work is what is important. The more we try out new ideas the greater our chances of stumbling on a winner.
- Value ‘purely anecdotal’ inputs, after all these come from the real world.
- Embed the exploration and consideration of behavioural and motivational aspects in decision making processes. We are social and emotional animals – it would be a mistake to assume that we make decisions based on a ‘rational analysis of the facts’. Remember that a decision which appears to be ‘irrational’ can still be the correct decision if wider considerations are taken into account.
- Hire for diversity – take chances on people who do not ‘fit the mould’
Winners are different. A quick look at the great corporate success stories of the last twenty years will show that very few followed the conventional norms of the day, and that many success stories came about more by accident than design.
