Data-driven business forecasting
There is a substantial number of methods and approaches that are used for business planning purposes. You could for example use a bottom up approach, focusing on the individual elements and then combining them up. Or you can use a top-down approach - starting from the overall picture and going down towards your position. You can also use an expert approach - relying on your team's experience in the respective field, or perhaps do a combination of all the above. While they have historically proven to be often quite effective, there are several important problems with their use:
- Not all parameters can be reliably estimated based on the suggested methods, especially in dynamic environments
- Risk is often difficult to incorporate with business forecasting and point estimates are usually used
- The element you are forecasting may have quite complex relations with other parameters that require advanced models
If the traditional planning methods work for you, then you probably don't need to go a step further. If however you are reaching the end of their capabilities, data driven analytical tools for forecasting are a logical step forward. They bring much richer mathematical and statistical methods that can be used to plan a complex, dynamic and risk centric models, which can achieve substantially more than the traditional methods.