Key takeaway
Analytics can help you to make better business plans, both by breaking down plans into their components, and by aggregating plans so you can see the big picture
What do you want to achieve?
We spend a lot of time with C-Suite executives at our clients, helping them with their plans. But, intriguingly, we often see that they find it hard to articulate and enumerate their objectives. We can point to three typical weaknesses:
How to avoid the impossible business plan
Another common situation is where in our strategy or diligence work we come across an impossible business plan. Penetration, frequency and category share all behave together according to a set of laws, e.g. you can’t have low penetration and high frequency. The return on investment in media spend is always going to deliver diminishing returns, but we still see magical business plans with increasing returns for higher spends. Sometimes we see business plans with impossible growth rates that have a plausible annual number, but which would imply a month-to-month increase implying a crazy level of sales by December. In our diligence work we spend a lot of time breaking down business plans into their components… and it’s surprisingly common to find that they’re utterly unfeasible. We urge you to break plans into granular elements, understand the realism of their inter-related assumptions, and look at monthly data, not just annualised numbers.
Castles in the air
A few years ago, I did a project for an airline that wanted to increase ancillary revenue, i.e.: non-ticket sales. But they had separate teams addressing seat upgrades, baggage fees, onboard food, car hire partnerships, hotel partnerships. They’d never spoken to each other, so they created their individual plans as castles in the air. The first thing I did was add up all the implied extra spending and showed it would require every passenger to double their ticket value, which was obviously impossible. So, joined-up thinking is vital when you ask teams to build different parts of the business plan. In this case we went on to look at different customer groups and create a detailed and joined-up plan taking account of the interdependencies, for which we created a matrix of customer segments and ancillary revenue opportunities.
The discipline of analytics, and understanding customer segments, penetration, purchase frequency, basket size, share of wallet, etc, and how all these come together in a (near) Newtonian understanding of your business plan can avoid these common mistakes.
“Analytics needs to be embedded in business as usual and should be holistic in terms of integration with other business initiatives”.
An extract from our research on other ways that analytics is changing businesses ‘Putting analytics to work’.
Next time we will unpick analytics and discuss what analytics is and how it can function best in your business “Analytics through the looking glass – the Dummy’s Guide to analytics”.
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