Words that strike fear into my heart
Here is a question for you. How reliable do you think business models are in producing the same results every time they are used? This questions leads some managers to ask those fearful words: "What is the statistical probability of the outcome of the model?".
The question is not unreasonable if you are spending time and money going down a certain path; you want to know the dependability of the model in generating a predicted result?
Models are theoretical frameworks. There are too many variables for them to be predictive to plus or minus 5%. Take the AIDA model for example. This framework tells us that action can only take place when there has been a build-up of awareness, interest and desire. The model is portrayed as an inverted pyramid. The theory is that the percentage of people with an interest in a product will be less than those who are aware of it. And the percentage of people who desire a product will be less than those who are interested. And the percentage of those who take action will be less than those who desire it.
All this makes sense. The problem is that we cannot say exactly what these percentages will be. Much depends on the product or service in question – is it a new product or an established product? Is it a technology product with a fast burn or is it a basic product which engages at a much slower pace?
I have seen a suggestion that the levels of engagement are halved as you move through the sequences. In the diagram, 80% of a population with an awareness of a product ends up with only 10% taking action. This is only an indication, reminding us that the conversion rates will almost always be a relatively small proportion of any group of people.
Theoretical models help us understand how and why things happen; they are not formulas with precise predictive answers. Sometimes in business we obsess too much about precision. We have got used to producing forecasts every year of sales and profit and are deemed good managers if we can deliver against these numbers; even better if we can beat them (although some may say that overshooting the forecast is also misleading).
All this said, models help us minimise risk even if we can’t be absolutely sure of the result. Take a soccer team, for example. The manager has no plan other than to instruct his players to "go out there, do your best and enjoy the game". However if the opposing team manager says exactly the same and has a strategy for Tiki-Taka control, managing the defence, and mounting an attack, my bet is that the opposition will win.
Frameworks and models may not give precise answers on results but they will give you a much better chance of success.