McKinsey recently examined how companies are generating business value from data in a report titled, Achieving Business Impact with Data. According to the report, in order to derive true value from your data monetization initiatives, it’s critical to understand all the moving parts in what the firm refers to as the “insight value chain.” This includes data and analytics, of course, but also your IT technology foundation, your people and culture, and your processes.

According to the McKinsey report, data monetization success requires getting all these things right:

  • Identifying, collecting, and storing data
  • Analyzing and visualizing data
  • Complementing data analytics with human intelligence
  • Taking a cross-functional approach

When it comes to use cases, the McKinsey report covers three categories that companies can pursue in their quests to capitalize on data. They include:

Top-line Use Cases

Primarily aimed at improving the customer experience and customer-facing processes, top-line use cases usually lead to increases in sales and customer satisfaction. These use cases can include more data-driven cross-selling and upselling, better optimized promotions, and customer churn prevention.

Bottom-line Use Cases

Typically tied to internal processes, bottom-line use cases harness data to drive greater operational efficiencies and reduce costs. Predictive maintenance, marketing effectiveness, and supply chain optimization are just a few bottom-line use cases being driven by companies today.

New Business Model Use Cases

With the potential for driving greater business transformation, new business model use cases are more tied to external offers and new businesses. This can include selling the data itself or creating new products in completely new markets.

Once you’ve determined the appropriate use case, the McKinsey report goes on to recommend taking a highly systematic approach to translating your data into business value with the following steps and activities:

  1. Generating and collecting data, including internal and external sources
  2. Refining data, including data mining and predictive analytics
  3. Turning insight into action with new processes and technology
  4. Mastering tasks around technology and organization, including culture and governance

While you may encounter some twists and turns along the way, knowing your goals, defining your use case and processes, and enabling your organization to quickly act upon data are all keys to success for data monetization.

For more info on the report, read the complete McKinsey article.