Data Is At The Heart Of The Intelligent Enterprise For Consumer Products Companies

Don Gordon

Until quite recently, consumer products (CP) companies were relatively passive about the use of consumer and other data to inform decisions. On one hand, the large CP companies were growing so steadily that intensive data-driven efforts hardly seemed necessary. On the other, CP companies lacked the technology and – just as important – the competency to undertake large-scale data analytics programs.

Of course, all of that has quickly changed. Growth in the industry has slowed considerably, and new competitors are emerging from all quarters. Leading CP companies now recognize that effective use of data has the potential to drive transformation across myriad functions, from R&D and supply chain all the way through sales and marketing. In addition, the technology has evolved to the point that it’s possible to integrate data from across the enterprise – essentially, to achieve a holistic view of the enterprise in order to make better decisions faster.

Then what are the challenges in the CP industry? According to the recent Retail & Consumer Goods Analytics Study 2018, 63% of consumer products companies say their top challenge with analytics is that they lack the right tools. Only five percent believe that their capabilities are on par with or better than the industry leaders.

This gap must be closed. Growing volumes of valuable data await your use to better understand the needs of your customers, to forge more agile partner ecosystems, to optimize manufacturing and value chains, and to capitalize on economies of speed and scale.

Next practices

From our global experience working with the leading, most innovative CP companies, here are three SAP “next practices”– capabilities and outcomes to help your company utilize data and analytics on a grand scale.

Integrate diverse data sources. Data is scattered. It’s in multiple applications, files, data warehouses, data lakes, and public and private clouds. For example, for customer sentiment analysis, you need to aggregate structured, unstructured, and historical sales data from orders, CRM systems, pricing applications, and market data. Without visibility into that data, you have a limited view of the customer.

Next practice #1: Integrate your data by combining data sets – including Big Data, process data, product data, analytical data, etc. – as needed, into a single data universe for much greater visibility.

Make data more useful. Your data comes to you structured, semi-structured, and unstructured. It may be spatial, chart, numeric, geographic, time-series, relational, JavaScript Object Notation (JSON), etc. Integrating all of these different types of data is extremely complex. But without it, your company is at a competitive disadvantage, squandering available resources.

Next practice #2: Integrate your data sources using orchestration and governance solutions. Go from raw feed to intelligence with real-time analysis of vast data sets. How? With solutions to understand, integrate, cleanse, manage, associate, and archive data to optimize business processes and analytical insights.

Simplify your data landscape. Centralized. Easy to use. Automated. That’s what you want from your data analytics platform. And those features have been a challenge because of all the different databases, apps, and clouds in your IT and business environment. But now a centralized data management solution is available that manages all facets of your data universe. Represented visually, the architecture is easy to share and understand. Stakeholders assigned to an architecture team within your company can collaborate through a user-friendly Web application in the planning, design, and governance of the architecture.

Next practice #3: Create and maintain a complete landscape architecture that is easy to share and understand. Open up this landscape to an array of company employees and managers to jointly manage your data environment as an agile, strategic tool.

A growing number of data analytics use cases for consumer products companies

Data analytics is being recognized as a vital tool for consumer products companies that need to innovate ever faster, create new markets and products quickly, and attract and retain customers. The need for speed has grown – along with the diverse types and quantity of data. Becoming a truly intelligent enterprise consumer product company thus requires a reliable, easy-to-use platform to capture, ingest, process, orchestrate, compute, and consume data at tremendous scale.

For more on how consumer products companies around the world are transforming into intelligent enterprises, read the new SAP white paper “The Data-Driven Consumer Products CompanyData Management for the Intelligent Enterprise.”

And please listen to the replay of our “Pathways to the Intelligent Enterprise” Webinar, featuring Phil Carter, chief analyst at IDC, and SAP’s Dan Kearnan and Ginger Gatling.


About Don Gordon

Don Gordon leads global Consumer Products industry marketing for SAP. Previously he led global Retail industry marketing for IBM. He lives in Philadelphia, considered by many to be the finest city on earth.