By Reshma Krishnan,
Perhaps the one thing that stumps most students is forecasting. How do you know what that number next year is going to be? Someone says we are going to grow by 10 percent. How did they get to 10 percent? Maybe it’s 11. Maybe it’s 5. How are they so sure? The Imarticus FMVC course, India’s leading program in Financial Modeling and Valuation dedicates significant time to forecasting by applying our fundamentals across various industries like Steel , Banking and IT. But we begin small, to understand how to forecast the financials of a small chai shop. We call it the ‘The Chai Shop’ assignment, which has helped many a student to grasp the fundamentals of both modeling and forecasting. So in the next few blog posts I am going to try and introduce you to forecasting beginning with some fundamentals and then moving on to a more detailed way to do The Chai Shop.
Forecasts are almost always wrong- If forecasts were always correct, astrologers would be the richest people on earth. Here’s the thing about forecasting. It’s probably going to be wrong. The basic premise of forecasting says, the past is the best indicator of the future. Past information that is, because we are assumptions are always based on what we know or think we know and that always has its origins on past data. For instance, when forecasting next year’s market for pencils, we assume that every child is going to need at least two pencils for a particular duration, let’s say a week. But that data comes from the fact that in the past, past pencil usage. But things might change. Pencils might get longer, children might start using pens or there could be disruptive technology like laptops that render pencils useless. Since we are almost always using the past and accounting for future changes to past performance, our forecasts will almost always be wrong, even if the past is the most accurate indicator of the future.
So why do we do it?
Because we need to have a plan, however terrible that plan maybe. We need to have an objective. A plan helps us prepare and mitigate risk. This is why I always tell my students forecasts need to be the most conservative because you are doing it to mitigate risk. The question we need to ask after we forecast is, how wrong is this forecast? Because while it will never be accurate, it’s all we have.
