Accurately forecasting demand has challenged business leaders across the retail and consumer goods industries. In this age of digital transformation, optimizing predictive modeling requires the consideration of an increasingly complex web of variables. Factors like consumer sentiment, average hourly earnings, and even POS data, all need to be examined. An increasingly digitized retail space further complicates the process of identifying and accurately accounting for these variables. Successful companies of today must go to market ready to face increased competition and shrinking margins, all while making the best decisions for their company in much less time.
As margins within the retail and CPG markets continue to shrink, companies are constantly trying to increase revenue by improving their forecasts, which the Institute of Business Forecasting found can often be off by as much as 17%
. Traditionally, demand planning models rely on internal levers such as promotions, advertising, prices and distributions. External factors such as economic growth and unemployment rate are recognized as important, but there has not been an efficient way to gather this information, quantify its impact on business, and use it in predictive forecasts moving forward. Because of this, reliance on past trends and educated guesses about the future often form the basis of demand forecasting for most companies. An incomplete view of performance drivers, as it turns out, end up being a big reason for variance in the forecasts.
According to studies by MIT Sloan Research
, leveraging external factors in addition to internal variables is the key to creating more accurate forecasts, though it requires leaving traditional forecasting methods behind.
Introducing Prevedere Demand Planning for Retail and Consumer Goods
Prevedere’s Demand Planning solution, built on Microsoft Cloud technology, empowers industry leaders to address the challenges associated with traditional demand forecasting solutions. Designed to enhance existing planning systems and processes, the solution enables business leaders to make better business decisions through real-time insights on their industry, their markets, and the demand for their products.
At the heart of the Demand Planning solution is Prevedere’s External Real-time Insights engine (ERIN
). ERIN combines the best of human intelligence and Azure Machine Learning capabilities to surface future-focused insights at the speed of business. ERIN constantly analyzes millions of external economic, consumer behavior, online, and social data sets, to provide access to the external factors that impact business as readily and easily as internal data.
The first cognitive computing engine of its kind, ERIN then determines the best combination of leading indicators, out of millions of possible choices, to surface actionable insights business leaders can easily consume through Power BI, creating unprecedented business advantages.