Data-Driven Growth Strategies: The Future of Business Intelligence
By taking a holistic view of future demand, consumer goods manufacturers and retailers can untap deeper consumer insights and make smarter, bolder business decisions.
That was the key message presented by executives from Prevedere and Microsoft during an informative session in April at the Retail & Consumer Goods Analytics Summit in Chicago. The session was conducted by chief executive officer Richard Wagner and head of marketing Pawan Murthy from Prevedere and Microsoft's
Shane O’Flaherty, senior executive for retail, CPG and hospitality.
The goal of the discussion was to illustrate the deep predictive insights that can be gained when companies combine global data with cognitive computing to mimic the mind of an economist with the processing power of millions of CPUs.
By enhancing their existing analytic processes with external economic and consumer behavior to identify leading demand indicators, companies can increase sales but also avoiding costly planning miscalculations. The benefits, therefore, also include improved profitability and marketing ROI.
Despite ongoing advances in analytics, the practice "is still internal and historical," explained Wagner, as he described a three-phase timeline of business intelligence formulated by Notre Dame economics professor Barry Keating, PhD.
Put simply, companies must move from basic analytics capabilities that let them understand "What Happened?" and even beyond causal models that determine "How Did It Happen?" to adopt cognitive computing using global data to predict "What Will Happen." "How do we collect all that data outside our four walls and use it to make smarter, more informed decisions," asked Wagner.
The presentation included several case studies illustrating how product manufacturers have been able to dramatically improve forecasting by identifying key indicators that would never have been uncovered using traditional BI practices. Prevedere's tools, for instance, are capable of examining 2.5 million data series from hundreds of different sources that are delivered in a wide variety of formats and frequencies.
One notable example: a spike in the number of Google searches for "morning sickness" is a leading indicator of increased sales for hand and body lotion seven months later.
To hear highlights from the RCAS session, watch the video above.
