Predictive analytics: precise forecasts for more planning reliability

In our white paper "Corporate management in volatile times", we explore the question of why predictive analytics has not yet been able to establish itself in corporate planning and management despite the availability of technical solutions. These five hurdles are decisive: individualised solutions, a lack of willingness to trial and error, challenges in data management and availability, definition and digitalisation of process structures and change management.

Data is crucial for predictive analytics. Complete, consistent and cleansed master data is required to be able to analyse this accurately. In many companies, there is a lack of high-quality data management - for example in the financial sector, where data is only collected on a monthly basis. In contrast, our experts recommend a minimum of weekly generation, or even better, daily generation. This in turn requires continuous data governance and automated company processes.

It is also important that employees in companies develop a mindset for the automation that predictive analytics entails. It is important for company management to allay fears, raise awareness and train new skills. Employees can and should be involved in the processes.

KPMG has developed the Intelligent Forecasting Solution to implement predictive analytics in companies. Our framework offers clear recommendations for action and shows how companies can proceed in four steps - from planning and conceptualisation to proof of concept, implementation and scaling to other areas of the company. Successful implementation of predictive analytics can have numerous benefits. These include greater planning accuracy, improved information quality, cost efficiency and a positive overall impact on financial performance management.