In conversation with Eric Chaniot, Chief Digital Officer & Senior Vice President of Michelin

According to the CGI Client Global Insights, IT and business leaders see increasing opportunity to use analytics in a range of ways, driving them to become more data-driven and to nurture cultures that encourage the use of data more ubiquitously. According to our 2019 insights from interviews with more than 1,500 client executives, leaders cite applying analytics as their top innovation investment area in the next three years.

Eric Chaniot, Chief Digital Officer & Senior Vice President of Michelin, is leading the group’s digital transformation with one goal—to turn Michelin into “a leader in the digital world and specialist in mobility and related services.” In a recent conversation with CGI, he speaks about this transformation and how data is a game-changer in this journey.

Michelin is experiencing its “fourth industrial revolution.” How does data fit into this strategy?

We have two goals for the next three years: first, to make Michelin a data-driven company to benefit from data in all our lines of business, including research and development (R&D), supply chain, manufacturing, etc. Then, start using artificial intelligence (AI) in a number of business areas.

One of Michelin’s historical values is respect for facts; nothing is more factual than data. For example, when I bring my car in for an oil change, the garage always advises me on approximately when my next oil change should be. However, depending on how often or how rarely I use my vehicle, the date they indicate is never accurate! In reality, the car itself tells me what it needs through a simple indicator light on the dashboard; this information is more accurate and, in fact, more difficult to call into question. That’s what data offers—information that is irrefutable, reliable, and easy to understand.

Our ambition, therefore, is to use data to imagine and deliver new, innovative services to our clients. We want to be the world leader in connected tires, offering products that warn the driver that “it’s time to change tires” or “it’s time to rotate tires,” while taking into account the type of driver you are, your usual route, the roads you’ve taken, etc. In other words, using actual rather than declared use, because we know that the facts and our view of those facts—or the reality and our perception of reality—don’t always align.

What are the key steps and directions of your data strategy?

They consist of four key aspects:

1. Proximity—In general, digital systems and data, in particular, must provide us with an unparalleled way to engage, understand, and be close to our customers to create an extremely strong connection.
2. Symmetry of attention—Thanks to the unique relationship and connection digital systems offer, you can provide your customers with the services and products they expect. Once you provide exceptional digital services to your clients, you must also provide them to your collaborators. We are paying close attention to this.
3. Continuous improvement—Data and digital manufacturing must allow us to optimize our operations. It defines and creates value for the supply chain, for R&D and its power to innovate, for production chains, etc.
4. Finally, automation and co-creation—When you want to launch a new service or product, surveying or interviewing users often reveals the difference between the proposal and what users really think. We pay close attention to adoption and actual use, not simply what is declared. Our obsession is really to get an unbiased view of the world around data. This is true for testing with our clients, for internal discussions with our collaborators, and for co-design and co-creation projects.

At Michelin, we have developed a robust innovation policy, and we strongly believe in minimum viable product (MVP) as a concept. Proofs of concept (POCs) are launched to arrive at the solution as quickly as possible, using data next to check its coherence and viability.

What organizational model did you set up around data?

It’s important to understand that data is not a digital matter or an IT problem; rather, it is a concept that should concern the entire enterprise. We are therefore in the process of implementing a hybrid organizational model with a central structure that oversees governance, cybersecurity, compliance, the choice of enabling technologies, platform deployment, etc. We are convinced that we need to stay close to our lines of business to become a data-driven company and look for people in our various business units, regions, and functions who will use data in a tangible way. This creates teams that combine business data owners with data analysts, data scientists, and data engineers. We strive to achieve the best of both worlds, merging the benefits of a central structure with those of a decentralized one.

Once you’re convinced, like us, that data is a key component to making better decisions and guiding your actions more effectively, the data culture must radiate across all levels of the organization. An example of this can be seen in the launch of our marketing automation platform. First, marketing teams are encouraged to share their insights; second, they are encouraged to personally take charge of data initiatives and actions that affect them and measure the outcome of those actions. The aim is not for everyone to become an expert, but for everyone to understand, at the very least, the environment and benefits of data. How does this impact the challenges you face in your line of business? What about your needs? How does this actually help you? We spend a lot of time teaching, and plan to launch a Digital Academy. Data, much like digital transformation, is 95% change management and only 5% technology.

You have approached your digital transformation voluntarily. How can we learn from it?

Michelin has been driving innovation for 130 years, which makes things easier. Everyone here knows that data is key to our business, and our executives have long been convinced of the value of digital systems. This engagement from top management is truly vital. At the beginning of the year, we hired a Chief Data Officer who reports exclusively to the Chief Information Officer and myself. As for me, I report directly to our CEO. This is very important because it means a streamlined decision-making process. When a decision is made, everyone pulls together to implement it quickly.

Next, organization is paramount. We are working to combine teams to benefit from the input of both our digital and business collaborators. This union of skills and knowledge is extremely rewarding and promotes creativity.

It is also important, in my opinion, to look at what is happening outside the organization. Observe and get inspired, particularly with respect to all aspects of AI. This is a major revolution whose impact we have yet to fully grasp, which will take time. I’m convinced that whatever your line of business, it will be impacted by AI in one way or another. The companies that will make the difference are those that will be able to combine all the exceptional potential of their collaborators with that of AI. This is our vision at Michelin.