PwC has developed a forecasting solution for a DAX 30 enterprise. It is based on Artificial Intelligence (AI) and machine learning. Automated business planning drastically reduces planning efforts and substantially increases prognostic accuracy.
Why?
Classic business planning is time-consuming and cost-intensive and often does not deliver accurate results. A global market leader for industrial vehicles and supply chain solutions (DAX 30 enterprise) regularly reported overly-ambitious planning figures. Seasonal impact and heterogeneous market development both resulted in volatile prognoses, ultimately failed to meet targets, and thus generated a climate of unsettling insecurity with respect to future sales volumes. The company was forced to pour considerable time and human resources into rectifications and manual prognoses.
How?
PwC’s Predictive Analytics Suite (PAS) allows for the automated creation of target figures. We have developed and implemented a predictive, driver-based model in collaboration with our client; it can utilise large volumes of internal and external market data. The prognostic model employs an algorithm that is based on AI and machine learning and makes objective predictions by integrating the relevant internal and external data. The so-called forecast engine – tailor-made for our client – selects those drivers from big data that are relevant for the object of prognosis in each case. To name a few: economic growth, inflation, incoming orders and further internal figures. This way, positive or negative developments can be detected early and thus be controlled.
What?
This PAS solution allowed our client to drastically reduce planning efforts and increase prediction accuracy. They are now able to identify market changes at an early stage and proactively steer their company in the right direction. The implementation of the solution went hand in hand with the acquisition and development of prognostic skills, the coding of individual algorithms, data acquisition and editing, and the embedding of solutions into the client’s reporting landscape.
«Any forecast of today’s activities should be a matter of maximum automation to allow controllers to focus on the planning of strategic options and scenarios, and thus add value to the company and enable genuine business partnering at the same time.»
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