Improving forecasting: digital tools and techniques
When it comes to planning, many companies invest significantly in the improvement of forecasting. Great facilitators of this endeavor are digital tools and techniques, including:
- Automated data collection techniques – for example, through Artificial Intelligence – that allow companies to assemble internal and external data from multiple sources.
- Advanced analytics methods which help create (cross-)links and investigate a much broader range of issues as well as the way in which these are interconnected.
Improved forecasting reveals the causes of current performance problems and planning-related inaccuracies: it enables the conception and implementation of more focused solutions. Furthermore, tradeoffs can be mapped in a better way.
In other words, today’s advanced digital tools and techniques lead to forecasting that is much more accurate in nature. This, in turn, helps companies anticipate and prevent issues, create a better planning, and support a continuous improvement cycle consisting of plan-do-check-act. They can rid their chains of waste regarding inventories, capacities, and supplies, and improve their service levels.
Forecasting and reality
Despite these developments, forecasting will always consist of a ‘best guess.’ Therefore, it is important to accept that all the above-described techniques cannot prevent a frequent deviation from predesigned schedules. Unexpected internal and external factors – from an additional customer demand to weather conditions and supplier delays – can and will continue to occur, and you should be able to respond to them in a swift and flexible manner.
Therefore, you need to be well aware of the limitations of planning and forecasting. When and where do they fall short? What is the impact of reality-based changes? And how much time do you require to fix these? When answering such questions, it is crucial to have a clear picture of the internal and external constraints that provide the framework for finding solutions. Reveal the hurdles that are put up by these constraints and define the effects of eliminating them.
In our experience, such flexibility should be incorporated into the design of operational processes. You can achieve this by building in spare capacity, ensuring you have covered all critical areas. Subsequently, you can employ digital techniques that measure performance in real-time. These enable operational control centers to decide how this spare capacity can be adequately deployed at any time. Predefined scenarios serve as an excellent basis and backstop in this regard.
Conclusion: two sides of the same coin
Forecasting and agility are inextricably interconnected. New digital technologies provide a wealth of opportunities to simultaneously improve both forecasting and flexibility. At M3 Consulting, we emphasize the importance of evenly dividing the attention you devote to these two aspects. Whereas companies seem to focus primarily on the improvement of forecasting, we advocate the development of an equally well-thought-out and solid design of agility. After all, the efforts to shape the latter can be easier in nature, and they may very well bear more fruit.