Big Data Is Still Disruptive: Transforming Business Decisions with Better Data
By Rich Wagner, President & CEO, Prevedére
As the population booms, infrastructure ages, new markets emerge and regions urbanize, data around society demographics, financial markets and even weather patterns is being captured by the second. Despite this unprecedented amount of information, executives are typically left wondering what to do with it all. Can all of this data really be mined efficiently to generate meaningful insights? Is it even worth filtering through this vast landscape to derive business value?
The answer is yes. Big data that goes beyond a company’s own four walls is becoming an increasingly powerful tool for brands looking to disrupt their industries and remain competitive.
Pressure to Innovate Antiquated Models
Internal analysts and research teamsare faced with immense pressure to compile accurate, comprehensive company data for finance teams and key decision makers. This data, encompassing historical performance, market share and consumer demand,has been the model for determining supply chain needs, creating forecasts and anticipating demand for new products for decades. With the big data revolution came even greater access to customer profiles, competitor performance and business results with constant, real-time updates. But it’s not enough – companies are simply feeding greater quantities of the same information into their business intelligence systems.
What if you could determine that the price of beef is a six-month indicator of your businesses performance? Or that yesterday’s weather directly affects your store traffic today? With the disruptive power of big data, smart companies are uncovering those correlations and making business decisions accordingly. Factors such as the strength of the Yen, changes in consumer spending, weather forecasts or growth of emerging markets can all be critical determinants to company performance, yet the significant challenge facing CIOs and CTOs is how to make use of all of this information and efficiently determine which external factors are critical to their businesses. As a result, most information technology teams are still relying on internal data that’s dated and insufficient to power critical business decisions.
Smarter Decisions Powered by Disruptive Data
Changes in local weather, consumer behavior or the rise and fall of the housing market are all external factors that greatly impact many companies’ supply and demand. Internal data, such as monthly sales information and purchasing peaks, is typically used to create forecasts, yet this is only half of the predictive analytics puzzle. Such touch points must be incorporated with external drivers to better understand why peaks or drops in sales are occurring and which products will have a higher demand – and why.
Convenience store giant RaceTrac, for example, couples internal data such as inventory, sales and store traffic, with weather patterns and external demographic drivers to determine which products will be the most popular, at what location and what time of the year. The company can now predict store traffic with 99.9 percent accuracy – not only maintaining adequate supply, but also ensuring proper staffing levels. These cost-effective decisions help the chain maintain a competitive advantage over stores that are less in-sync with individual market needs.
The Way Forward
As China’s economic meltdown puts pressure on Wall Street investors, companies worldwide need to factor in how these changes will affect their global supply, logistics, demand and overall revenue. Relying on old models for data-driven decisions will yield the same results. In order to innovate and break the traditional paths of competitors, information officers must incorporate new forms of big data that will paint a clearer picture of business drivers and future performance.
Companies that want to remain competitive are being forced to disrupt their own internal processes and think smarter about how to run their business.The first step is to look beyond historical data and incorporate micro and macroeconomic conditions to make accurate predictions, and ultimately better decisions. Information technology teams need immediate access to robust information that helps decision makers understand potential threats and market opportunities, and react proactively – ahead of the competition. Implementing this forward-thinking process will transform the way companies make marketing, manufacturing and operational decisions, improving their overall performance.