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Mastering the art of the 80 percent: How to drive sustainable B2B pricing excellence with data and analytics

The path to value creation with data in B2B pricing is riddled with pitfalls. A lot of companies jump to technical solutions without defining clear use cases first.

We have found that the winners succeed by applying the 80/20 rule in multiple respects: they size the prize up-front and focus on the use cases that have the potential to make a real difference.

Later, they find out that the solution they chose does not meet their needs. Others are convinced that they don’t have enough data, or the right data, and end up doing nothing. Yet many companies do manage to create significant value with data-driven pricing, typically in the magnitude of 2 to 7 percent margin improvement.

We have found that the winners succeed by applying the 80/20 rule in multiple respects: they size the prize up-front and focus on the use cases that have the potential to make a real difference. They make a realistic assessment of data quality and implementation feasibility up-front. Last but not least, they are prepared to augment and enrich existing data sources in creative ways. Building on this pragmatic spirit, leading players continuously refine and improve their data regime to create sustainable impact over time. In this article, we explore the dos and don’ts that help companies get started with data-driven pricing efforts, from opportunity sizing to data management.

Before you start in-depth data gathering or buy a software package for data-driven pricing, make sure you know where the value lies for your company. Involve business owners from day one to take advantage of their experience and ensure buy-in for the effort. Work with them to develop hypotheses on the most promising business improvement opportunities that could be addressed with data and analytics.

At last year’s McKinsey European Data Summit in London, a financial-services executive summed up his experience with data leverage for commercial excellence as follows: “Put impact before data. Five years ago, we created a data lake with an off-the-shelf interface, assuming the organization would figure out what to use it for. We failed miserably. Very few people used it at all, and everybody else tried to prove the output wrong. Now, we work with our most experienced people to size the impact potential and build our data regime one use case at a time. To get people to want to work with data, they need to see how it can make their lives easier and their businesses more successful.

Examples of typical B2B pricing use cases for data and analytics include:

  • More consistent list pricing
  • Streamlined discount management
  • Value-driven deal pricing, reflecting customer lifetime value
  • Surcharges that reflect actual cost, e.g., for express delivery or small orders
  • Better payment terms

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