Improve Your Forecast To Increase Your Profits

A lot of us hate math and anything that has to do with numbers, unless it’s about our profits. But as business owners, it’s a bitter pill we need to constantly swallow in every function in the organization if we want it to survive and grow in the long run. To name a few, finance would have the most to do with numbers as it involves accounting-related activities like taxes, marketing would require you to check the conversion rate of your ads to see if they are still generating sales, production would require you to know how much to produce.

Among all these math problems we have to face, there is one task that most often critically affects our profits, and that is forecasting. Forecasting is not just a fancy word that means estimating how much of something you could expect in the coming period. Production would benefit enormously if the forecast is accurate as it allows you to know how much of your product you need to produce without having too much spoilage or tying up capital. Production costs money, so you want to produce only as much as you can sell.

Forecasting can also give you an idea on how much of workload you would have in the following periods. If it tells you that peak season is near, you can ready your people, and devise new procedures to avoid overflow or get additional manpower. For businesses that regularly find their stores too small to accommodate the number of people who visits them daily, and are planning to move to a new location, forecasting would give them a hint on how big the store should be without going overboard. In inspecting the new location, and accommodating the level of foot traffic, forecasting would tell you how much additional customers you would gain in moving.

It is obvious that forecasting is very important but how do we about it? The answer differs widely depending on many factors with some needing the help of statisticians. Here are a couple of simple methods you can use if you are just relying on guesswork at present:

The “naïve forecasting” method is called as such because we are merely assuming that the previous data would be the same for the next month, or week- “naïve” because we do not factor in external forces that would affect our business. Using this method, if in August, you handled 30 customers in total, your forecast for September would also be 30. With this given data, you can assume that you would need probably 30 pieces of your product plus a buffer of maybe three to five just to be safe.

This is the most common method that is even performed by those who don’t know about naïve forecasting. Sometimes, instead of using the sales of the previous month as forecast, we use the sales of the same month from the previous year thinking that it would reflect the consumer trend. That is, if the next month is October, we look at October 2015’s sales, and use that as a forecast for this year. Again, it is not very accurate, but there is a good reason why companies use this. Data gathered from previous years show us how our sales move from month to month, giving us an idea what months shower profit, and what months kill us.

The “moving average forecasting” method is another simple forecasting method. To do this, you simply get the average of the total sales you made from the previous months. That is, if in June, you sold 10 of your products, 13 in July, and 12 in August, your September forecast would be (10+13+12)/3, which is 11.67. The divisor “3” comes from the number of months you used in the computation. This means you can expect to sell 12 units this September. You can increase the number of months that you factor in in the equation, but remember that the farther your data is from the period to be forecasted, the more inaccurate it would be. A five-month moving average forecast would probably the farthest you should go in using this method.

These are among the simplest forecasting methods out there. However, advanced formulas like the linear trend equation, exponential smoothing method, multiple regression and the application of Bayes’ Theorem, are beyond the scope of this column. These sophisticated techniques consider additional factors to make the forecasts more accurate. While the busy manager or entrepreneur may not be the one to do these calculations, having some knowledge of these would help a lot in communicating with the appointed person in case you will use them.

It is highly unlikely to get a 100-percent accuracy in forecasting because of factors beyond our control like competitor moves, new laws passed, weather, and unexpected events. But the point of being proficient in forecasting is to have the soundest basis possible given the ever advancing state of knowledge. This may give you the competitive edge to boost your profits.

*Originally published by the Manila Bulletin, C-4, Sunday, September 18, 2016. Written by Ruben Anlacan, Jr. (President, BusinessCoach, Inc.) All rights reserved. May not be reproduced or copied without express written permission of the copyright holders.