An innovative push from the open source world has accelerated the development of advanced analytics and algorithms, shifting from insights that describe or (at best) diagnose, to predictive and even prescriptive algorithms.
With more – diverse – data available from internal and especially external sources, findings are corroborated, rather than depend on guesswork, and thus become much more accurate.
A catalog of these algorithms, if made available to the business, can make a decisive difference in business performance and competiveness.
Off-the-shelf analytics are a quick, viable alternative to building algorithms yourself; this market is rapidly growing.
A life science company uses weather and social data to refine forecasts, streamlining their supply chain.
A major consumer goods company actively analyzes social media to refine campaigns, decide on marketing strategies and protect brands.
A global insurance company develops analytical models to analyze external media for events that could affect their customers, and hence their exposures.
A leading auto manufacturer analyzes internal and external data to accurately predict arrival of a car at the dealer, right from its arrival at the port.
Getting more new value from data from various – often external – sources, beyond the traditional business intelligence benefits
A better understanding of future customer behavior, optimizing the supply chain, shortening delivery routes, saving energy, identifying the right personnel for the job, predicting health issues, tax fraud and machine defects
Modeling, simulating, and deciding around alternative business scenarios and key outcomes to decide the next best action