2015 Readers' Choice Survey: Demand Data Analytics
Consumer packaged goods companies are drowning in data. Lora Cecere, founder of Supply Chain Insights, analyzes today’s downstream data challenges and explains how technology systems are poised to help consumer goods companies come up for air and make data actionable.
Can you comment on this list?
Cecere: IRI and Nielsen have long been favorites in helping the marketing organizations within consumer products companies understand market share, market basket data and overall demand insights. Likewise, JDA is the dominant player for category management analytics. These positions are well cemented in traditional processes.
While many of the companies listed are active in analytics within the demand signal repository market, this technology market segment remains fragmented and immature. The market is waiting for the addition of predictive analytics and the building of outside-in processes to invest in the demand signal repository technologies in a big way. For right now, the demand signal repository market is stalled with companies fighting it out for market position. We don’t see this changing anytime soon.
Absent from the list are analytics providers, like Cloudera and Hadoop, in the providing of non-relational technologies, Teradata/Aster Data and SAS for predictive analytics, Qlik for in-memory, SAP for its work on HANA, and Spotfire/Tableau for visualization. The list is heavily slanted toward marketing analytics.
Are downstream data analytics initiatives now being wrapped up in big data projects?
Cecere: While the term Big Data permeates the vendor pitches and articles, it is being over-hyped. Most analytics projects within consumer goods today are not big data projects. What is the difference? Big data is a project with a marked change in data volumes, data velocity and variety. Most of the projects are not within the petabyte definition of big data, but there are a number of projects that are using some of the big data technologies to capture insights from a variety of data — unstructured text mining, streaming data, maps and weather, and customer comments. Using this definition, the use of RFID tags in food and beverage for track and trace is a big data opportunity.
Where should consumer goods companies focus data-driven investments in 2015?
Cecere: In 2015, we see innovators investing in cognitive learning and new forms of visualization to drive new forms of insights. We also continue to see a strong market for in-memory analytics like those from Qlik combined with the visualization technologies of Spotfire and Tableau. These technologies are not cost prohibitive and have strong, positive customer sentiment.
More and more, consumer goods companies are looking for software-as-a-service (SaaS) solutions, which explains the popularity of Retail Solutions Inc. and Market6.