There are many, many other methods and here are just a few of them to whet your appetite, and from there you'll hopefully be able to decide which of them will be most suitable for you and/or your client.
But before looking at the first one, I said I would explain how to calculate a straight line (which will make the Dynamic Difference Analysis work). This is not an easy thing to do outside of a classroom but let's try anyway. (If you get bored then scroll down to "Percentage of Sales").
It's easy to draw a straight line - but less easy to calculate one.
Every straight line may be described by the equation;
Where
Y = dependent variable
a = constant quantity
b = coefficient of regression
By determining the values of (a) and (b) one can establish what line they represent. As I mentioned earlier, I could go on and give you the normal equations applicable - but you really don't want to go there do you?
So let's move on to something which everyone understands.
This is an extremely simple method, where expenditure is pegged at a given percentage of anticipated sales.
For example, advertising costs for a car manufacturer are fixed at, say, R2,000 per car and, as he expects to sell 10,000 cars during the year, his advertising budget is fixed at R20,000,000.
Whilst this method finds huge favour among unimaginable managers and does contain some semblance of responsible planning, it makes one fundamentally incorrect assumption because it implies that:
Sales = Advertising
And, of course, we all know that it's the other way round (or should be).
This is less responsible than the educated guess because it implies that the advertising costs are a necessary evil and are funded from profits (resulting in a profit drain of course).
There is still strong resistance in many companies to "spending" the money.
Of course, we all know that advertising is definitely not simply spending money because, in truth, it's an investment. But because this method carries little risk of costing the advertiser more than he can afford, it remains a very common practice.
The advertising budget is calculated by multiplying projected sales revenue for the campaign by a set percentage (similar to the "Percentage of Sales" method) and implies a direct reliance on the sales forecast - which is the major flaw in this method.
Its only justification is that, as an arbitrary method which simply considers the current availability of money supply in the short-term, it will prevent a company from spending more than it can afford.
In the longer term, if the sales forecasts are wrong, then all kinds of problems will have to be faced. In reality it will result in an unrealistic or inefficient budget.
This method relies on the budget being calculated following an analysis of competitive expenditure - on the assumption that increasing the industry average will increase market share in more-or-less direct proportion.
The inherent danger of course (which you've no doubt spotted already) is that it implies that the competitor is right and it cannot allow for any change in competitive strategy (e.g. the increase/decrease in adspend or launch/withdrawal of products etc.)
It also assumes the "collective wisdom" of the market place and, in so doing, must also accept the consequence for "collective stupidity".
It makes no allowance, for example, for a superior creative strategy (in fact very few budgeting methods do).
This method was extremely popular a few years ago but has become less fashionable these days.
Although it appears to be an intelligent approach, it does have some flaws. For example it has, at its foundation, the premise "to reach an Opportunity To See (OTS) of 3.5 and in order to reach that objective our task is...." The error is fundamental because what research exists to say that the average consumer will act on the advertising message after being exposed to it 3.5 times?
Although it's little better than the "Guess" method it does, however, disguise any guesswork by introducing some quantifiable elements into the exercise.
Firstly it demands that a task, or objective, be set. For example, to increase sales by X%
Secondly it requires the determination of the most effective advertising plan in order to achieve the objective - the calculation of true cost will evolve from this exercise as it is the total of media and production expenditure contained within the advertising plan.
Finally, management will decide whether or not the campaign is viable in terms of the required cost juxtaposed to anticipated income (via pre-determined objectives).
The essential flaw exists, of course, somewhere between the determination and identification of what "the most effective advertising plan" really is. It really is a Catch-22 situation.
Assuming there is access to reliable data - which reveals the average response rate to given advertising exposure - and, given that accurate costs involved in reaching such potential customers are known, a simple arithmetical calculation can be made. For example;
b) I also know that the cost of reaching potential customers is R1.00 per head.
c) I can therefore calculate that to reach 100 potential customers will cost 100 x R1.00 = R100
d) A 2% result will mean 2 units are sold and therefore the advertising cost per unit is R50
e) The required advertising budget is therefore Z x R50 (Z being the total number of units I wish to sell).The smart reader will immediately see the flaw - which is at point (a) because, no matter how good you think the research is, you can never be that sure. And when you make a mistake (even a small one) at the beginning of a calculation like this it can have disastrous consequences.
And I've run out of space again...so I'm going to conclude this series of "constructing an advertising budget" next week by looking at seasonal swamping, marginal analysis and the imperfect market influence. If you haven't bought a copy of Erik du Plessis' book then you should (mine is out of print). Or give me a call.
Keep your calculators clean!
Read my blog (brewersdroop.co.za) or see what other amazing things we do at brewers.co.za
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