Is it surprising to you that a relatively small company like Sunny Delight could end up with so many different analytics tools? How might the fact that Sunny Delight has changed ownership multiple times have impacted the number and variety of BI tools being used? What are some of the trade-offs of a move to an enterprise-level analytics solution for individual end users who might have grown accustomed to working with their own customized solutions for generating data? According to a recent report by Gartner, most business users will have access to some sort of self-service BI tool within the next few years; however, Gartner estimates that less than 10 percent of companies will have sufficient data governance practices in place to prevent data inconsistencies across the organization. Why do you think so many companies continue to invest in new analytics tools without implementing governance programs that ensure data consistency?
When implementing a self-service analytics program,
For Sunny Delight Beverages, a Cincinnati-based producer of juice-based drinks, the payoff from using selfservice analytics software has been significant. The company, which generates more than $550 million in annual revenue through sales of its SunnyD, Fruit20, and VeryFine brands, estimates that its newly implemented, self-service analytics program has resulted in a $195,000 annual reduction in staffing costs and a $2 million annual increase in profits.
Getting to these results, however, has not been easy for Sunny Delight. Like many companies, it had developed a patchwork of departmental business analytics applications over the years. Sunny Delight’s infrastructure was particularly complex as the company has been bought and sold multiple times since it was founded in 1963. At one point, Sunny Delight’s 480 employees were working with eight different legacy BI applications, resulting in some departments spending up to a week each month producing data that was often not in agreement with the data generated by other departments. Reconciling and rolling up the data was time consuming and left little time for in-depth analysis, much less strategy development and execution.
The data silos also meant that Sunny Delight had no real visibility into its business, which lead to revenue unpredictably, higher-than-necessary inventory levels, and lower margins. The company’s sales efforts were hampered because the sales team did not have a true understanding of the effectiveness and profitability of specific sales promotions. For example, the sales department was unable to correlate the impact of a promotional discount with order volume—a key metric for judging the effectiveness of a promotional program. The company was also unable to tie shipping costs directly to specific promotions, which was significant since the timing of many promotions required shipping products to stores on weekends, when shipping and warehouse labor costs were higher.
When the company made the decision to revamp its analytics efforts, the company’s CIO and CFO pulled together a cross-functional team of managers from sales, marketing, logistics, warehousing, and accounting who were responsible for developing a comprehensive picture of the required BI functionality—which ranged from simple, canned reports to complex, ad hoc data analysis tools. Working to understand each department’s needs built credibility for the project team and helped them choose the solution that would be most effective across the company, which they did after evaluating 17 different options.
The team selected Birst, a cloud-based, self-service BI solution that offers an end to data silos with what it refers to as “local execution with global governance.” Because the project team understood that a centrally manage
According to John Gordos, Sunny Delight’s associate director of application development, Birst provides Sunny Delight with a single, networked source of data, which employees at all levels can access quickly and easily, regardless of where they work. Birst’s data governance features mean that Sunny Delight’s IS team maintains final control over all data, while the user-friendly interface, which is the same whether users are accessing data on a PC, laptop, or smartphone, makes it easy for nontechnical users to access and customize the system’s departmental dashboards.
According to Gordos, “Birst helps [Sunny Delight] employees to think fast because they no longer have to worry about building and aggregating the data. They just get the data, and then they think about it—instead of accumulating it.”
Critical Thinking Questions
- Is it surprising to you that a relatively small company like Sunny Delight could end up with so many different analytics tools? How might the fact that Sunny Delight has changed ownership multiple times have impacted the number and variety of BI tools being used?
- What are some of the trade-offs of a move to an enterprise-level analytics solution for individual end users who might have grown accustomed to working with their own customized solutions for generating data?
- According to a recent report by Gartner, most business users will have access to some sort of self-service BI tool within the next few years; however, Gartner estimates that less than 10 percent of companies will have sufficient data governance practices in place to prevent data inconsistencies across the organization. Why do you think so many companies continue to invest in new analytics tools without implementing governance programs that ensure data consistency?
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