Forecasting may not be a top-of-the-list item on the minds of many entrepreneurs and small-business owners. It should be, however. Failure to take a forward-looking, bird’s-eye view of a business could lead to critical mistakes and lack of direction, in the case of market surprises. A well-devised, objective forecast based on sound data can serve as a resource upon which management can establish realistic plans for the future of the business.
Forecasting, when done right, is more than a simple prediction. Business forecasting is based on analyses of information about the company, the industry and the economy, and can mean the difference between being ready for market changes and being left behind. Without routine engagement in forecasting, a business owner or management team may be left to simply wing it as business and market trends take their shape.
So what does a forecast look like? One could make forecasts for the market broadly or for specific metrics, such as revenue and inventory. Different methods will make sense for different businesses, but some common quantitative methods include regression analysis, a statistical model that predicts a variable based on its relationship with another variable; moving averages, which takes averages of previous periods to predict outcomes for upcoming periods; and simulations, which use probabilities based on historical data, often via computing software.
It is possible to make bad forecast. By definition, forecasting is a way of looking into the future, and it likely won’t be an exact exercise with 100% accuracy. However, one can conduct forecasts with greater confidence if potential shortcomings are identified in advance and kept in check. Some common causes of poor forecasting include the following:
- Not taking it seriously – Companies that believe a budgeting exercise is sufficient could fall into this pitfall. Management or the finance team may only conduct forecasts occasionally or reactively. This could lead to inaccuracies and almost always defeats the point of forecasting in an effort to try to equip the business for the future. Forecasts that are taken lightly and not fully understood may not have the credibility it needs in planning stages that follow.
- Ignoring reality – Planning done around pipe dreams rather than real circumstances may lead to less-than-effective forecasts. Aspirational qualities are necessary in running a business, but forecasts should be based on facts and verifiable data, which would then serve as a basis for realistic changes and growth that the company can digest.
- Using bad data – A forecast is as sound as the data on which it is based. Accurate quantitative predictions cannot be made if the underlying data points are insufficient or based on faulty assumptions. A mistake in a calculation somewhere in the process could have an outsized effect on the output and have greater consequences when left unchecked.
- Allowing biases in –Individuals have different ways of viewing the world and may think differently based on biases. An entrepreneur may be overly optimistic, or a management team may be too conservative. Some may be driven by confirmation bias and search for or interpret data in a way that confirms their pre-existing beliefs or conclusions. Guidelines and various levels of checks should be in place to ensure that analyses are conducted in an objective manner.
Creating a forecast is not an exact science, and there is no single right way to do it. Nevertheless, forecasting is a key aspect in managing a business for the future. When combined with detailed budgets and open communication among departments and leadership, a forecast can be an essential tool with which to navigate a business through what may come in the future toward success. Here are some suggestions how to improve on financial forecasting:
- Develop a process – Many companies have now adopted a quarterly rolling forecasting process instead of the traditional annual cycle. A rolling forecast requires timely gather of business data and and key inputs that will drive the forecast model, so it is important that the company develops a robust process in place to drive collaboration among the business analytics function, the forecasting function, and key stakeholders to incorporate business insights and decisions into the forecast.
- Understand your business drivers – No good forecasting can exist without a firm grasp of the underlying business drivers, which translate into the key inputs feeding the forecast model. At a minimum, the forecasting team should have a good understanding of the key factors impacting revenue and variable costs of the business, such as the pricing, the volume drivers, and the various distribution channels of the products.
- Keep it simple – There are many methods on forecasting, and it might take some time for each company to figure out what the best approach would be for its business and industry. In general, there is no need to use overly complicated techniques in financial forecasting, as simply methods such as moving average might prove to be more effective.