statistical forecasting

Why you should incorporate insights from Sales and Marketing into statistical forecasting.

As statistical forecasting is inherently reactive, getting input from Sales and Marketing is the only solution to make the forecasting process proactive.

Good sales managers typically prefer relationships, people and seeing opportunities over data. They get motivated by understanding how their input to statistical forecasting will minimise their work – not by lots of numbers, Excel sheets and statistical models. Operations managers, on the other hand, are often motivated and dependent on these statistical models to succeed. With the different functions in a company being interconnected, this gap needs to be bridged in order to achieve the targets of both Sales and Operations.

By using the information that Marketing has about tenders, promotions, increasing or decreasing pipeline and new markets and customers, the forecasting process can be made proactive. Combining these inputs with statistical forecasting methods is a prerequisite for forethoughtful and unbiased demand planning, since sales managers tend to overforecast in the short-term horizon and underforecast in the long-term horizon.

Creating an unbiased and proactive forecast by aligning goals across departments

The solution to complications, arising from the misaligned motivational goals of the different stakeholders, is threefold, namely by explaining the impact of sales forecast bias at the specific company, which is why bias can only be reduced by the involvement of Sales and Marketing and how their workload can be minimised in the process. Purpose and collaboration are the keywords to sales involvement – the answer is not to create more KPIs. Purpose can be demonstrated by involving Finance and have them prepare a financial planning profit and loss statement to provide insights into profitable sales that will attract interest from Sales.

The key to getting Sales and Marketing’s input is to minimise their workload, which can be achieved by keeping their sales forecasting focus at an as aggregated level as possible in the product hierarchy. Furthermore, segmentation helps to focus sales forecasting efforts in areas where it creates the largest impact, and by combining statistical forecasting and knowledge of Sales and Marketing in the best possible way, keeping minimum workload for Sales and Marketing can still provide great input for sales forecasting. An efficient way to share knowledge from Sales to the other stakeholders is to align their existing forecasting processes, such as marketing plans and budgets, with the statistical forecasting process. This will both minimise their efforts and increase the quality of the different forecasting processes.

Scenarios are essential to addressing opportunities and are a helpful tool in demonstrating the effects of sales forecast bias. Hence, scenarios can play a key role by increasing motivation for knowledge sharing between departments’ functions and providing an adaptable tool that all departments can understand. They allow an illustration of how possible outcomes to actions taken by the different departments will affect the overall result of the company, which in turn has the potential to reduce siloed thinking.

Incorporating input from Sales and Marketing with the statistical forecast can thus provide a proactive and more unbiased sales forecast and can be conducted in a way that keeps the workload at a minimum level to let the different departments focus on their core business functions.