Developing Data Literacy

A new method for helping executives prepare for digital transformation.

THE TECHNOLOGICAL DISRUPTIONS introduced by big data are forcing businesses to reinvent themselves, yet many of today’s top executives do not have the data literacy skills they need. In fact, by the year 2020, half of all organizations will lack the requisite skills to handle technology, according to “A Data and Analytics Leader’s Guide to Data Literacy,” a piece from research firm Gartner. Furthermore, most business managers struggle to translate their vision for digital transformation into practice.

To help executives gain data literacy and learn to infuse data logic into their projects, the two of us have developed the Data-Driven Business Models (DDBM) method. We began working on the methodology in 2017 as we offered multiple workshops and assignments at several EM Lyon Business School campuses in France.

To develop DDBM, we began by defining three components of data literacy: acculturation, or a familiarity with how data works and how it can create value; methodology, or an understanding of the available methods; and hands-on experience. DDBM workshops provide these components through sessions that incorporate these elements:

  • Business Model Canvases. We use these visual templates, popularized by Alex Osterwalder and Yves Pigneur, to help executives formalize their projects and ask themselves essential questions.
  • Current business literature. We also share the latest insights from experts in the field, such as Andrew McAfee’s work on how technology affects business and society.
  • Design thinking. We teach executives this process for creative problem-solving so they learn to balance the three pillars of desirability, viability, and feasibility.
  • Agility and teamwork. We take participants through a series of timed, focused exercises as they fill in their DDBM canvases and determine how to pitch their projects to their executive committees.


Before executives participate in DDBM workshops, we first have them acquire fundamental knowledge about the concepts through online readings and videos, as well as a two-day seminar that explains the managerial relevance of current technologies such as artificial intelligence. The DDBM workshops themselves last half a day to a full day.

During the workshops, participants are grouped into three- to five-person teams that collectively decide on a business project to address—usually a case from one of their companies. Together, they fill in ten canvases that lead them through defining their target users and their problems, identifying potential sources of data, and aligning their solutions with the organization’s business strategy. By the time they have reached the last canvas, participants have designed a business project that delivers value, guides the organization through digital transformation, aligns with organizational strategy, and meets the needs of the end user.

After groups have finalized all their canvases, they take turns sharing their ideas in three-minute pitches that simulate presentations to an executive committee. Group members must structure their pitches around three essential topics: what problem they’re trying to solve and for whom, how they are solving it, and why the solution is important for their organization.

Executives who have participated in DDBM workshops consistently identify four features they appreciate most. First is the time-boxing approach, which forces them to zoom in on essentials. Second is the opportunity to receive unbiased feedback from peers working in other functions or industries. Third is the canvas format, which leads them to ask the right questions about their projects. Fourth is the fact that the workshop results in a tangible, reusable deliverable.

DDBM is part of a growing and recent trend in adapting managerial toolkits for organizations interested in becoming “data mature.” It is free to use, and all materials can be downloaded from our website. We think a method develops best when it is tested and challenged in a variety of settings, so we welcome input from professors and executives so we can continue to improve it in the future.

Guillaume Lecuyer is product marketing director of software vendor Visiativ and Clément Levallois is an associate professor in data valuation at EM Lyon Business School, both in Lyon, France.

Get details on the Data-Driven Business Models method.


Developing Data Literacy Chart 1

For this canvas, which participants fill out near the beginning of the workshop,
managers build a profile of an end user who faces a particular problem or frustration.




Developing Data Literacy Chart 2

For this canvas, participants identify sources of data they can use to solve a particular
business  challenge—and note whether those data sources already exist or must be created.


Developing Data Literacy Chart 3

Participants also fill out canvases like this one, in which they consider how their
proposed projects align with the strategic objectives of their organizations.