Data analysis is not a new concept. Companies such as Nielsen and Information Resources, Inc. are built on a foundation of gathering large swaths of information, analyzing it and developing insights subscribing companies may use to improve performance. What is new is how cost-effective it has become for individual companies to gather their own data, conduct analysis and develop proprietary insights that may drive many aspects of a business, whether it is product development, operations, marketing or customer service. The challenge facing most companies is developing the internal competencies to analyze the data in an effective manner and develop actionable insights across an entire organization.
The Starbucks Coffee Co. offers a good example of how one consumer packaged goods company is using data generated by its loyalty program to improve performance. By analyzing shopper data generated by its rewards program Starbucks is able to respond quickly to market trends, giving it an advantage over competitors.
An extensive report published by the Grocery Manufacturers Association and produced in conjunction with Deloitte Consulting L.L.P. outlines the opportunities “big data” offer food and beverage manufacturers. Titled “Formula for growth: Innovation, big data and analytics,” the report reviews how data mining technologies are starting to transform the consumer packaged goods marketplace and outlines what companies may do to use the technologies to improve performance.
It is easy to be overwhelmed by data with its variety of formats and the unique analytical skills required to properly review the information. Data also may have different meanings to business functions within an organization, and the G.M.A. report does a thorough job of outlining the types of data companies may use to derive insights. Suggested sources include consumer call centers, customer service centers, shipment and inventory data, supply chain data, retailer shopper profile data, consumer product reviews and many others.
The challenge most companies face is harnessing data and putting it into formats that allow for review across business segments. The G.M.A. report establishes different stages of analytic capability. Stage one, the lowest, is categorized as “analytically impaired” while stage five, the highest, is titled “analytical competitors.” Most consumer packaged goods companies reviewed in the report fall into stage two, “localized analytics,” which means each function within a business maintains its own reporting and analytic capability that allows the function to make basic decisions based on historical data. Examples of stage two localized analytics include trade promotion, category management, or demand planning, according to the report. Companies that fall into stage two are missing opportunities to develop insights that may benefit an entire organization.
In addition, the G.M.A. study notes one weakness among many C.P.G. companies is the lack of qualified personnel to do data analysis.
“The reality is that to take advantage of big data, C.P.G. companies need the right people with the right skills and talents to improve the quality of decision making,” according to the report. “Big data in itself is not a solution but simply an input and enabler to becoming a better informed, more productive organization. All of the investment in dig data and analytics is wasted if decision makers feel the insights they receive are erroneous. There is also little value in having big data insights in the hands of decision makers who lack the skills and competencies to derive the proper business decisions.”
Data development and analysis have greatly altered a variety of businesses, ranging from e-commerce, finance, logistics and even professional baseball. The food and beverage industry is on the cusp of realizing the benefits of “big data” and forward-thinking companies must have the resources and people in place to take advantage of the opportunity.