Consumer packaged goods (CPG) companies generate a ton of manufacturing, marketing, supply-chain, and other types of data that can be analyzed and acted on to optimize operations.
For that matter, the customers who buy their products also create massive amounts of behavioral, sentiment, and transactional information that could be used to better guide product development, placement, advertising, pricing, and other types of decisions that could help strengthen marketing and sales results.
Despite the opportunities available to them, CPGs aren’t using big data and analytics to their fullest. Many CPG companies are under-utilizing analytics to improve the performances of their businesses, according to a study by Accenture.
Just 9 percent of CPG executives say their companies have implemented total analytics operating models, while 15 percent acknowledge that such efforts have only been partially executed across all of the geographies in which they operate.
There are also discrepancies between how CPG executives view the maturity of their organizations’ analytics strategies and their actual progress. Even though 47 percent of the Accenture respondents describe their companies as either “analytical leaders” or as having “ingrained analytics,” few companies are focused on using data to generate insights.
There are several ways in which CPGs can use various data sources and predictive analytics to strengthen both business and operational performance.
For example, a CPG can analyze point-of-sale data, promotional data, and other types of information to determine the most effective price for a product at a particular time and in a particular set of stores or in a specific region.
The use of predictive analytics can help a CPG determine whether reducing the price of dishwashing detergent by 10 cents instead of 8 cents would result in a greater likelihood of increased sales and whether the volume of sales would offset the anticipated loss of profit.
CPGs can also use analytics to identify opportunities to generate efficiencies in their supply chains. For instance, a soft drink manufacturer that trucks its products to multiple supermarket chains across a 12-state region can use visual data discovery techniques to reveal the cost savings that could be achieved through improved route optimization.
Next Steps:
- We invite you to watch our complimentary, on-demand webcast, “The KPIs that Deliver Ultimate Customer Insight.” In this webcast, you will discover that by leveraging the volume and variety of your customer-based data, you can achieve a higher level of actionable insight and enable strategic decision making across your CPG&R organization.
