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Consumer Packaged Goods Companies Could Improve Business Performance With Better Use Of Analytics, Accenture Study Finds

The majority of consumer packaged goods (CPG) companies are failing to place analytics at the heart of their decision-making process, limiting their ability to improve the customer experience and gain business advantage, a study by Accenture (NYSE:ACN) has found. Accenture's analysis also suggests that in many cases the problem is compounded by fragmented investment in narrow programs that are not well coordinated and fully optimized.

According to the study, "Building an Analytics-Driven Organization ," more than half - 54 percent - of CPG executives say their company has a fully defined analytics operating model. In contrast, just nine percent say their company has implemented an analytics operating model in its entirety and 15 percent say the plan has been only partially executed across the geographies in which they operate. Additionally, 40 percent of the respondents say that their company has only partially defined an analytics operating model, but 14 percent of those CPG executives say their company has not implemented it.

The study indicates a mismatch between how CPG executives perceive their companies' maturity in analytics and the actual state of their analytics efforts. Although 47 percent of the executives described their companies as either "analytical leaders" or having "ingrained analytics," the analytics teams of many of the companies represented in the survey remain focused on "pulling data" rather than using data to develop insights. Almost one-third (32 percent) of the respondents admitted that their analytics employees are focused on the management of "big data." However, just nine percent said they have made a priority of predictive analytics, which generates information that can enhance longer-term decision making.

"The research indicates that the analytics functions of many CPG companies are producing hindsight descriptions of what has happened, rather than delivering forward-looking insights that can be used to make well informed operational, managerial and strategic decisions," said Bob Berkey, managing director in Accenture's Consumer Goods & Services practice. "CPG companies need to focus more on implementing an analytics operating model that puts analytics-driven insights at the heart of their decision-making process. Only then will they be able to realize true value from their analytics investments and achieve increased efficiency, speed, flexibility and profitability."

Julio Hernandez, managing director, Accenture Analytics North America, said: "Today's CPG industry is focused on four imperatives - a better understanding of consumers, reducing cost and increasing service levels in the supply chain, enhancing relationships with retailers and hiring and deploying the right talent. In each area, big data analytics techniques and underlying technologies can provide a competitive edge by offering actionable insights from multiple sources of data, including business, third-party and contextual information, often in real time. The greatest benefits will be achieved by companies that speed up and automate the analytics process and systematically infuse data-based insights into their operations."

Accenture's study also found that many CPG executives are more focused on putting technology, rather than talent, in place to enhance their analytics capabilities. Analytics technology was named by 37 percent of respondents as their top priority in analytics, followed by analytics governance, at 31 percent. By contrast, only eight percent of the executives surveyed ranked talent as their top priority in analytics, and 55 percent ranked talent last on their list of analytics priorities. Despite the talent ranking, the survey shows that almost three-quarters (73 percent) of respondents are, in fact, actively hiring analytics talent, even though many say they are still defining their analytics talent needs. Two out of five executives – 42 percent – said their current talent focus is to determine the analytics roles they need to fill, and the skill sets in greatest demand are data modelling (53 percent) and data mining (44 percent).

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