In a Board sponsored study, BARC explores the value of Integrated Business Planning, and the…
In the second part of this blog series, we looked at why integrating planning with analytics and automating processes are important. In this final post, we will learn why predictive planning and forecasting are rapidly gaining in relevance.
A major challenge in corporate planning is to generate meaningful and high-quality planning figures quickly and efficiently. Many companies are therefore looking for solutions to speed up forecasting and reduce their effort.
Predictive planning and forecasting, which refers to the use of statistical methods and machine learning in planning and forecasting, is rapidly gaining in relevance for many companies. They want to leverage modern planning approaches.
89% of companies rate the current and future significance of predictive technologies and forecasts as important at the very least.
This indicates that predictive planning and forecasting will fundamentally change corporate planning. Predictive models are designed to improve the results of planning – as well as the planning processes themselves – to achieve meaningful results more quickly.
The aim is to achieve greater automation of projections and forecasts, while at the same time improving the quality of planning and forecasting in terms of accuracy and significance.
The approaches and use cases for leveraging predictive planning and forecasting in organizations are manifold. They range from calculating default values and validating planning data entered to identifying value drivers for building robust simulation models.
When it comes to rating the potential of predictive algorithms, expectations are equally high. Most companies believe that predictive technologies will be able to deliver more accurate forecasts in the future than a human planner today.
These companies have very high expectations of the potential for improvement through predictive planning and forecasting. From their point of view, human intervention will rarely be necessary when business is running continuously. The aim is to optimally support and relieve human planners of routine activities and to compensate for a lack of resources.
The still low use of predictive planning and forecasting in practice is in stark contrast to the assessment of its relevance and potential in the future. Two thirds of the companies surveyed are only just beginning to address the topic and have not yet gained much experience. Only 4% already successfully use and benefit from predictive technologies and forecasts.
The gap between future expectations and the current situation is quite striking. Many companies will have to step up their technical and organizational approaches to tap the full potential of predictive planning and forecasting.
The first part of this blog series looks at the four facets of integrated planning and analytics.
The second part of this blog series explores why integrating planning with analytics and automating processes are top priorities for companies in corporate planning.
Learn more about this topic in the exclusive BARC study, sponsored by Board