Government generates a wealth of data.
How can businesses use it to transform their strategies and operations?
As businesses work to fuel innovation and sharpen competitive edge, a growing number are recognizing—and tapping into—government’s vast stores of data. In fact, many now depend on government data to guide business investments, develop new products and service, and foster innovation. The Roundtable on Open Data for Economic Growth, co-hosted by the Center for Open Data Enterprise and the U.S. Executive Office of the President Office of Management and Budget (OMB), revealed work already underway and pointed to compelling opportunities on the horizon.
With all the recent attention on big data and advanced analytics, it is easy to forget that businesses have been using data to create new insights and innovation for centuries.
The term “business intelligence” was coined in 1865 by Richard Millar Devens in his Encyclopedia of Commercial and Business Anecdotes. It was first used to describe how a 17th century banker achieved competitive advantage by collecting and analyzing internal and public information relevant to his business activities.
While that may be ancient history, business intelligence remains highly relevant—and government has a key role to play in collecting and providing data.
These companies are already using government data to fuel business innovation and anticipate changes in customer wants and needs:
- CVS Health developed an online tool called myhealthfinder. It uses government health data to provide consumers with personalized recommendations for preventive healthcare services. By collaborating with the U.S. Department of Health and Human Services (HHS), CVS Health leverages government data to connect consumers with vaccinations, screening tests, and other useful services available at CVS Minuteclinic and CVS Pharmacy locations.
- Starbucks collaborated with Esri, a geospatial technology company, to develop a business intelligence system called Atlas. This data-driven platform uses government demographic data, government weather data, and proprietary sales data to develop highly sophisticated consumer marketing strategies. For example, Starbucks uses demographic data on the number of local smartphone users to determine where mobile app discount will be most impactful. Starbucks uses weather data to synchronize Frappuccino promotions with rising temperatures.
- Best Buy used government data in developing an innovative market segmentation strategy, which was key to growing the consumer electronics brand. Using a combination of government demographic data and proprietary sales data, the strategy employs advanced analytics to define and group consumers by personas. Each persona represents a different consumer segment with specific buying habits. Best Buy used these data-driven profiles to restructure its in-store and online experience, which together helped reinvent the brand to meet the needs of 21st century consumers.
Many businesses follow a problem-centric approach to using government data. The focus: combining proprietary data with publicly available data to address existing organizational challenges.
Other businesses use a discovery-centric approach, which allows data analytics teams to identify new correlations and trends by fostering intellectual curiosity. One such organization is the Kellogg Company, which applies data-driven approaches to help increase revenue and reduce costs.
At the Roundtable on Open Data for Economic Growth, a representative from the Kellogg Company shared four key steps of the process it uses, and any company can use, when applying government data for business decisions:
- Formulate the question and hypothesis. For example, data scientists at the Kellogg Company used government data to explore the impacts of cold weather conditions on consumer spending behavior. The question could be: “Is the harsh winter affecting our consumer sales?” The corresponding hypothesis could be: “Lasting cold temperatures are reducing the number of shopping trips and reducing cereal consumption.”
- Identify relevant datasets. Businesses can look to both government data and proprietary data. For the hypothesis on winter sales, for example, the Kellogg Company combined its own retailer point-of-sale data (by zip code, by day, and by three-year history), and government weather data (by zip code).
- Conduct analytics to develop insight. In this case, the Kellogg Company used data analysis to identify sales patterns and develop models to show how they correlated with weather patterns. The Kellogg Company discovered that sales drop when temperatures are below 20 degrees Fahrenheit for three consecutive days. However, they may not drop on Friday—when the effect of payday outweighs the effect of weather.
- Apply findings to business strategy. Use this process to enhance business strategy, optimize customer experience, support product innovation and improve operational efficiency and effectiveness. In this example, the Kellogg Company changed its digital coupon distribution schedule to drive consumers to make purchases on Fridays since the data analysis demonstrated that it’s a relatively “weatherproof” day.