Setting an example
Some enterprises are already leading the way with future-proof forecasting. Whether you're using algorithms to predict demand for new products, harnessing analytics to enhance resource allocation, or translating social media buzz into demand insights, advanced forecasting practices are boosting the bottom line.
Informed product launches
A US manufacturer of audio equipment was struggling with inaccurate demand forecasts, leading to losses, high inventory costs, and write-offs. When launching a new product, the manufacturer transformed its forecasting capabilities with AI and machine learning algorithms. It incorporated new external data points – such as product reviews, promotions, and web visits – to predict customer demand. Able to react in real-time to these early signals, the enterprise improved forecasting by 40% to manage inventory levels more effectively.
Enhanced resource allocation
A pharmaceuticals enterprise has transformed cash-flow forecasting into a suite of predictive analytics models to consolidate accounts receivable and accounts payable insights. This gives the finance team a view of expected future events – such as seasonal fluctuations – that drive cash requirements. This visibility empowered the workforce to make better decisions on short- and long-term resource allocation.
A luxury cosmetic company had a limited understanding of the macroeconomic factors that drive demand, resulting in lost sales, stockouts, and poor customer experience. A sophisticated demand forecasting model needed to incorporate fluctuating data points – for example, the impact of a leading social media influencer promoting one of its products. The new and improved model incorporated 15 different data sources, including an innovative customized social media buzz index, to achieve a 30% improvement in overall demand forecast accuracy.