Making valid predictions is a difficult business. The Predictive Planning method takes this problem to the next level by using intelligent algorithms to take business planning to the next level. Predictive planning has become a relevant trend for planning optimization.
Without planning possible future scenarios, the economic success of a company can hardly be organized. However, as the environment becomes more and more complex, combined with unexpected events, painstakingly created plans often deviate from reality. As a result, the company reacts retrospectively instead of looking far into the future. An extension of the planning cycles can help to a certain extent, but the limited resources set a limit. Predictive planning makes it possible to exceed this limit.
The next level of business planning
Many events happen unexpectedly. In this case, a company has to react quickly – at best with a knowledge advantage. Predictive planning focuses on the analysis of specific processes and challenges of a company and is rapidly gaining relevance for many companies (75% of companies see increasing relevance of predictive planning).
Reliable predictions through the use of intelligent analytics
Predictive planning refers to the use of predictive models based on statistical methods, machine learning and artificial intelligence for business planning. The drivers for this are the ever-increasing amounts of generated and processed data, as well as the more comprehensive use of machine learning in business intelligence and analytics due to the simple availability in the cloud.
Predictive planning and forecasting are intended to provide better technical support and shorten existing processes. Furthermore, the planners are to be relieved. The aim is to automate projections. This offers considerable time savings in the analysis.
To this end, the quality and accuracy of planning should be increased by identifying cause-effect relationships and integrating them into planning models. In the foreground, knowledge about the company and its environment is to be gained. This will be done by linking internal and external data with the help of explorative analyses. In this way, a realistic representation of future scenarios can be created.
In the second part of the article, opportunities and benefits as well as areas of application of the predictive planning method are presented.
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