If I were to take a guess, I’d bet that we’ve all been in situations where we need to make an important decision quickly – where one of the possible options is presented in such a compelling way, it seems like a foregone conclusion. Perhaps the option appears to have benefits that are so hugely significant, it is seen as a ‘no brainer’ – a decision that is so ‘obvious,’ there is little point in putting much thought or contemplation into the decision making process itself. Perhaps it’s ‘obvious’ that we should launch into a new market, slash our prices, buy a new software package or restructure a particular department.
This desire to make decisions quickly is understandable and rational – after all, it’s important that we avoid ‘analysis paralysis’ – yet a real danger awaits the unprepared. In many cases, ‘no brainer’ decisions have far wider consequences than the decision maker might initially appreciate. In fact, further analysis of the data might show that you are being duped into making a bad decision with confidence. Let me illustrate with a hypothetical example.
Imagine an online retailer sees a sudden sustained drop in its sales. It knows that competition in the market is cut-throat, and it needs to retain its market share. It could be seen as a ‘no brainer’ to temporarily cut prices or offer some other type of incentive to increase sales volumes. In some cases, this might be an appropriate response – but in others, it might lead to a dangerous race to the bottom – with all firms lowering their prices until they can bear it no longer.
In the hypothetical situation mentioned above, it would be far better to look at the business situation holistically. It would be beneficial to carry out analysis and look at the business environment and establish what data and insight is available. Maybe there are other reasons that sales have dropped overnight, or other factors that should be considered. For example: was there a similar drop last year? Is there a seasonal peak in sales? Has the weather been unusually hot/cold (which might affect the pattern of people buying or ‘shopping around’)? Are people buying a completely different substitute product altogether (think Netflix affecting DVD sales)? There would, of course, be many other factors to consider too.
In situations like this, it is hugely beneficial for organisations to look at their data and analytics for insight. Carrying out analysis in this way – before making so called ‘no brainer’ decisions – helps to avoid the ‘knee jerk’ reactions that can lead to unexpected and unfavourable outcomes. Ensuring that businesses move from data collecting to curating actionable data and insight is key.
So – if you’re presented with a ‘no brainer’ decision, what should you do? Here are five key questions that you might consider asking: