As a consumer packaged goods (CPG) supplier, this pet care subsidiary of a large, global producer ($37 billion in revenue) struggled to keep up with analytics due to exceptional growth in its digital business. Making decisions based on data was time consuming and inefficient.

NTT DATA introduced a decision-based architecture, determining which data and corresponding metrics the CPG could use to answer key questions. As a result, the company continued its fast growth and increased share by 50 basis points.

Business Needs

Despite exceptional growth in its digital business, this company's immature analytical capabilities kept it from fully leveraging the huge opportunities in the growing online segment of the $200+ billion pet care market.

Succeeding as an Amazon supplier requires access to a multitude of metrics that must be understood and acted upon quickly. Having to pore over Excel-based reports and data gleaned from third-party data scrapers was a losing proposition in this fast-moving digital space. And it was a highly inefficient, time- and resource-intensive way to try to manage key business levers, such as pricing, inventory, digital shelf placement, search and their $30 million activation budget.


30% business growth
50 basis point market share increase
  • Creates visual, relevant analytics to better understand the state of business
  • Optimizes inventory through better decision making
  • Sustains and grows online retail relationships


Working with NTT DATA’s Data and Analytics experts, and using the Decision Architecture methodology, the business acquired high-level decision process mapping. This brought a new understanding to how the sales team acted on the primary business levers and what types of questions could be answered with the data.

The first step was to determine key questions related to inventory health, ordering, supply and allocation. Each of these key questions was then connected to decisions, actions and corresponding metrics to create high-level requirements for visual analytics.

Search- and media-effectiveness analytics helped the team quickly identify areas of under- or over-investment and capture revenue growth opportunities. Category diagnostic analytics highlighted gains and losses in share and connected them to causals such as pricing, supply or page content issues so the company could take corrective action.

Dense spreadsheets requiring days of analysis to try to spot issues have been replaced with visual, relevant analytics. Now, the team can quickly understand the current state, spot problems and opportunities, and efficiently make decisions to optimize inventory as well as sustain and grow their valuable online retail relationships. Powered by these analytics, the business has not only continued its fast-paced growth of over 30% but also increased its share by 50 basis points.

About the case study

A CPG company turned to NTT DATA to replace dense, cumbersome spreadsheets with visual, relevant analytics.


Retail & CPG


United States

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