As part of this research, each CPG company interviewed was asked, “Who owns the analytical maturity of the organization?” There was a notable difference in the responses. Some organizations (Stages 1-3) did not have a clear owner, or it was simply unclear who was responsible for developing the analytical maturity of the organization. In other instances, it was determined that each functional group should specify their own needs and resource requirements for analytical capabilities. Many companies separated “data” from “analytics,” indicating that the data assets of the organization were owned by one or multiple groups.
Deloitte asked a panel of leading Wall Street industry analysts the following question: “From your perspective, what level of the organization should own developing the analytical maturity of the organization?" For the full video with the UBS Analysts click here.
Conversely, those companies with a more developed analytical maturity had a more clearly defined and structured organization supporting analytics with more clearly defined executive leadership. For these companies, the priority and emphasis placed on using analytics to support decision making manifested itself in a variety of ways. For example, Procter & Gamble (P&G) constructed a physical room, called the Business Sphere, where leadership convenes in order to make decisions using the information assets of the organization. The room has wall-to-wall data visualizations that reflect the status of various aspects of their business. There is a business analyst in the room who facilities the discussion and decision-making process with the group. P&G reports that they currently have more than 50 of these types of environments across their operations (see "P&G Turns Analysis Into Action" - Doug Henschen).
The emphasis P&G places on the usage of analytics in decision making is in many cases predicated on having a strong analytical culture within the organization. This culture sends a clear message to all levels of management (and potentially to prospective analytical recruits) that the organization puts an emphasis on fact-based, analytically supported decision making.
The research suggests that companies with a strong analytical culture have been investing in that culture for years. For these companies to be where they are today, they have historically invested in many of the capabilities reviewed as part of Recommendation and Conclusion 1. It was also observed during interviews that companies with a stronger analytical culture tend to be less risk adverse, have more agility, and therefore are able to experiment quickly with new innovations.
Summary of the Analytical Maturity Model
This concludes our discussion of the fifth category of analytical maturity. To summarize the overall maturity model, most CPG companies are still focused on developing analytical capabilities using existing data assets the industry has had for more than a decade. As we move into an era of rapid innovation and resulting Big Data, it will be a challenge for the less analytically mature companies to keep pace. Conversely, the companies with the required foundational capabilities – across all five areas reviewed in Recommendation and Conclusion 1 – are in a position to leverage Big Data to gain competitive advantage. This analytical “maturity gap” within the industry may have existed amongst competitors for many years; however, the implications will likely become increasingly visible in this new era of rapid technological and digital innovation which will be outlined further in the following conclusions and recommendations.