Research published by thisismoney.co.uk (A nation of sales addicts? UK revealed as the promotion capital of Europe with 55% of food bought on offer) revealed that 55% of food and 59% of non-food items bought in UK are bought on some kind of offer.
There is no doubt that a company that learns to manage these ever increasing trade spend budgets efficiently is the one that gets huge competitive advantage. A prerequisite for any company wanting to get there would be having a mature IT system that can provide detailed data on actual sales, product costing, pricing, as well as manufacturing and sales forecasts.
Assuming you have all that, what else will you need?
The answer is a SAP Trade Promotion Management (TPM) solution of some kind. Each SAP TPM system normally offers few methods of quantitative analysis, but before we go deeper into science, let us just think about issues that any decent TPM system should be able to address.
Will you know whether money is earned or lost on a particular promotion? And if so, how much?
If you believe you know the answer to that, think again as there is a lot to think about indeed. Have you taken ‘cannibalisation’ into account? By this unpleasant, yet generally accepted term we mean the potential losses on sales of similar goods which do not have promotional offers. Cannibalisation is one of the most obvious factors; less obvious would be the long term effects on sales, such as:
Consumer goods with long shelf life are likely to reduce sales after the promotion (the effect known as ‘post-dip’)
‘Sold out’ label on the shelf due to overly pessimistic (or neglected) demand planning. The short-term effect of that is clear – the profit is lost. Yet the long term effect could even be more damaging – some customers might lose their loyalty to the brand and start looking on what competitors have to offer!
Premium brands are likely to have positive long-term impact after promotions as they tend to increase the brand’s customer base.
If you are a manufacturer of consumer packaged goods sold through various retailers, do you know whether the retailer you deal with makes or loses money on this promotion?
In the long run it would mean a lot for the retailer’s willingness to continue partnership on your terms.
As you can see, even after a promotion is finished and all figures known, it can be quite a challenge to see how much you have earned or lost on it. The good news here is that there is a way to take all of the above into account and come back with the precise figure. The even better news is that there is no need to overcomplicate the SAP TPM solution. On the contrary, if it becomes a black box for the users and no one understands how it works, that won’t make it more popular.
What about your plans? How do you approach profitability of planned trade promotions?
Well, the good news again is that there are not so many unknowns once you have some idea which promotions you are going to run and when. A mature system will easily provide you with data on pricing, product costing, projected ‘base’ sales volumes and so on to provide you with a good foundation of calculations.
The first subjective figure that you have to add on top of that would be the projected percentage of customers taking advantage of the promotional offer (this is normally called ‘redemption rate’). This one is not too hard to guess if you have results of the previous promotions to support you. And if you are running a simple price reduction (as opposed to ‘buy two get one free’ or similar), then you redemption rate is simply 100%.
The second one is far more subjective and controversial – the uplift volume, i.e. what we believe we are going to sell on top of ‘normal’ sales for that period. There are ways to statistically project that on the basis of previous promotion results, but that is where the science stops as there are too many factors to take into account. Seasonality or even the simple fact that your competitor is running a similar promotion at the same time would ruin all the most precise statistical calculations based on the past promotions. Normally a SAP TPM implementation would provide a suggested ‘base’ and ‘uplift’ sales quantity and let the end user change the latter one. And believe me, tracking that change would not be a bad idea.
Why are approvals necessary?
A few years ago I was at a conference devoted to trade promotion studies and one of the presentations indicated that around 30% of manual adjustments were way too large turning a ‘projected’ profitable promotion into a loss in real life. Another 30% of adjustments were in the wrong direction – i.e. account managers increasing suggested uplifts that in reality were lower than the default ones offered by the system, or vice versa – decreasing the uplifts that in reality were higher. This of course can only become clear after actual sales are known. Why is this happening? Chances are that your account managers are quite keen to sell on good terms to the retailers as they want to keep good relationship with their customer base. On top of that normally it is the sales volume and/or revenue that their bonuses are based on. So there might be some motivation to exaggerate the predicted effect of the promotion. That is why a good SAP TPM solution must have some form of Trade Promotion approval process in place - to prevent selling your goods for peanuts.
Yet even with the approval process, how can you measure the degree of subjectivity in your account manager’s estimate of the uplift volume?
I do not believe there is a realistic way to see that, however there is a way to measure the ‘sensitivity’ of the overall profitability of the trade promotion to the potential change in the uplift volume. Here science comes back again, and it is not rocket science at all – an additional measure that tells us by how much the volume has to change, in relative or absolute terms, in order for the projected profit to break-even. This makes the approval process so much easier – if you see that even a 50% decrease in uplift volume is still going to bring you some profit then the risk does not look so great. On the contrary, if you see that a 10% decrease in projected uplift is putting you to the break-even point, it does not look like a safe bet – you can lose money on that promotion if things are going even slightly worse than predicted!
Addressing the question raised in the title of this blog, the answer, in my opinion, would be: it is an art of knowing where to stop and finding the balance between usability and accuracy. The science and technology is also there to support us with numbers for whichever factors we want to take into account. All that provided that we build SAP TPM on top of a mature ERP/BI implementation with data on historical sales, pricing, product costing, sales and production forecasting.