What is Managerial Forecasting?
Managerial Forecasting is a systematic technique of planning, which helps the management to cope up with future uncertainties. It mainly relies on the data collected from the past and present through trends analysis.
What’s the most challenging part of being a corporate finance professional? Most of you will unanimously agree that it is the “Managerial Forecasting”. Being able to prepare your organisation about the future course of events is indeed a task of responsibility.
But most people find it to be a challenge too big to overcome. That’s not entirely true. Managerial Forecasting can be fun too, especially if you know how to lay the framework of a good forecast.
Most financial analysts confuse forecasting with prediction. Now that’s one of the biggest mistake for sure. Prediction relies on certainty of future, but forecasting factors in uncertainty and plays around the possibilities of events. So it’s not about making sure shot prophecies, but about identifying where things could go off track and developing a strategy to derive maximum benefit out of the situation.
Still confused? Don’t be. Forecasting is one of the most crucial part of being a financial analyst and you cannot afford to get it wrong. Let’s see 6 ways how to master the art of forecasting:
1-Let go off your biases, fears, emotional triggers
In Forecasting, there is no place for personal biases, insecurities, fears or emotional triggers. These things are better nipped in the bud. Forecasting is about being as objective as possible. Before you make your assumptions for forecasting, you need to see the situation as it is. For eg: You may not want automation to take away a few jobs from the business, but if that is the prevailing scenario, you have to factor it in your forecast. You may be a teetotaller and may not identify with those indulging in drinks and tobacco, but if your company sees a sizeable growth in its revenue from liquor and cigarettes, you need to take it in account when you predict their sales. So, you see personal preferences and emotions can cloud your judgement skills when it comes to forecasting.
2-Clearly identify your objective and the problem.
What exactly do you want to forecast? The goal of forecasting or the business problem at hand must be as crystal clear as possible. For example, a cement company may need to understand the percentage of its demand in housing sector. An e-commerce company may want to figure out how much sales does it garner from organic search. Once the actual aim of the forecast is known, it becomes easy to build a roadmap and approach the work.
3- Be all ears for inputs and suggestions
Most of the business forecasters are experts in the field of finance, accounting, economics and management. But it may come as a surprise to you that even people from other field can also offer valuable suggestion. These may be things you may not have even though about. If you are making a forecast for a garment company, the apparel designer on board will be able to tell you the upcoming fashion trends which could drive sales and eventually the bottomline. A technology expert could identify what’s going to be the latest craze in smartphone market. So be open to other’s opinion as well and stay in touch with every department.
Cycle of Probabilistic Forecasting
4-Break the problem into chunks
No problem is too big to solve. All it needs is a practical approach to deal with. This also goes for business problems. After identifying the exact goal of forecasting, you need to break the problem in solvable chunks. For example, if you need to forecast what percentage of girls in Mumbai would like to spend on home salons, you would first need to find out the percentage of females in Mumbai, then the percentage of women who are regular customers of salons and spas, and so on. This kind of filtering down approach would finally lead you to the nucleus of the problem, and with all the ground work already done, the rest would be a cake walk.
5-Learn to pick subtle signs
Sometimes evidences and data can be confusing. There may be some data points which may be too obvious but may not be too relevant to your managerial forecasting goal. At other times, there are situations when you need to pick not so blaring information. For eg: you may focus more on the consensus or management guidance on growth in a social media company’s revenue from Europe, but ignore the implications of GDPR in that case. The company may not want to talk directly about its impact on the revenue or subscriber base, but as an expert in forecasting, you need to be very open to subtle hints like this one.
6-Choose the right forecasting technique
Due to the complexities in the nature of business forecasting, it is very important to choose the correct forecasting technique. The selection methodology of forecast technique depends on a lot of factors such as goal of the forecast, availability and quality of data, relevance of the data, degree of accuracy, time period of the forecast, the level of accuracy desired, and ultimately the cost-benefit analysis derived from the forecasting technique. It depends on the judgement of the forecaster as to choose the most suitable technique of forecasting.
Conclusion: Good forecasting is a blend of various factors
It is quite aptly said that managerial forecasting is an art rather than science. It just doesn’t depend on data, evidence or techniques. The judgement skills of the forecaster plays a very important role in the success of the forecasting exercise. The results of the forecast needs to be shared with the management and the forecaster must keep provision for relevant changes suggested by the management. Accurate forecasting is thus the blend of knowledge, technique and experience.