Data-Driven Pricing

While most strategic and tactical decisions in an organization aim to create value for customers and shareholders, pricing decisions are the ones that are meant to capture this value. For many companies, deciding on a price comes down to a strategic debate. The quantitative part of pricing, on the other hand, is often delegated to competitive benchmarking, adjusted “appropriately,” and to the company’s annual financial statements for inferring the underlying cost structure.

Data and IT have the potential to revolutionize pricing. In fact, they already have in very competitive industry sectors such as airlines, hotels, and mobility: data-driven pricing pioneers have reported impressive profitability improvements. Their success has been based on leveraging the power of granular data, and on using advanced analytics to obtain data-driven insights regarding the price sensitivity of narrow customer segments, or even of individual customers, as a function of the sales channel, of the timing, of the product offering… Models and algorithms, then, assist in optimizing and automatizing pricing decisions (B2C), or in providing decision support systems to managers (B2B).

As granular customer data becomes ubiquitous, the required IT backbone cheaper and more accessible, and data scientists in higher supply, the potential of data-driven pricing opens to many more industries. The key challenge to reaping its benefits is organizational and managerial: one needs to build, lead, or collaborate effectively with a data-driven pricing function. To that end, mastering the strategic tradeoffs of pricing does not suffice: one also needs to have an understanding of the tactics and analytics of pricing, at a basic level.

The Data-Driven Pricing Program targets mid-level managers and executives, with functional roles primarily – but not exclusively – in Sales, Marketing, Commercial Finance, and Operations/Supply Chain Management; effectively, any manager or executive that needs to assemble, lead, or collaborate effectively with a pricing function (whether such a function formally exists in their company or not). No technical background is required; only some proficiency with data analysis in Excel, and willingness to learn new concepts and methodologies.

OBJECTIVES

Understand: participants understand the fundamentals of pricing analytics: Aggregate demand and consumer choice modeling Price sensitivity estimation Market segmentation Price optimization Demand forecasting Bid-price control Opportunity cost evaluation

Apply: The course adopts a very practical, hands-on approach to teaching data-driven pricing, learning by doing (in Excel): Cases accompanied by datasets (simplified, but realistic) Workshop-style sessions: theory-analytics-discussion Technical notes to assist preparation Excel solutions shared ex post

Analyze: Participants analyze the implications of data-driven pricing at the level of strategy, technology, and organization; for instance: Who should be making pricing decisions within a company, and why? What infrastructure and organizational structure are required? How does one evaluate a pricing analytics initiative? How does a company compete through data-driven pricing?

Create: Participants acquire the tactical and analytics skills of pricing that, combined with the strategic perspective provided in the core SFP, enable them to assemble, lead, and collaborate effectively with data-driven pricing functions in their organizations.

The focused executive education program on Data-Driven Pricing targets managers with functional roles primarily – but not exclusively – in Pricing, Revenue Growth, Sales, Marketing, Commercial Finance, and Operations/Supply Chains; as well as executives that need to assemble, lead, or collaborate effectively with a pricing function (whether such a function formally exists in their company or not). No technical background is required, but some willingness to learn new concepts and methodologies, and experiment with them through AI-powered chatbots, is expected.

Learn to optimize pricing with advanced analytics.

Gain insights to lead and structure pricing functions.

Apply concepts through hands-on, real-world exercises.