Building a data science team at michelin tyres

1. How I helped Michelin tires built a data science team and overcome challenges including lessons
learned
Business problems identified= Let us look at the pain points of business and then figure out what problems
we can solve with data. Not all problems can be solved.
a) Smart Manufacturing=Optimizing efficiency and quality in the manufacturing process
b) Integrated value chain=Demand forecasting
c) Services built=temperature, pressure, GPS for tyres. These tyres are used for formula 1 cars.
What we achieved=
a) Overall scrap reduction=15%
b) Reduced cycle time for mixing=2%
c) Improved demand forecast error=mean error reduced by 6%
So people, process and technology required=
a) How did I go about hiring=When you start something outside the corner at a big company, you
may be considered an outsider. Made it like a start up reporting directly to the CTO. Helped move
out of bureaucracy pattern-flat structure. More than 40,000 people but outside the classic hierarchy
and bureaucracy.
b) IT department is outsourced-that sometimes creates a problem. Bring expertise inhouse
So get the technical and business savvy insider team from different departments. That helps you manage
the challenges better. Hiring from known sources, Media and social media sources, References,
Teaching experience, Speaker at various conferences.
c) I hired physicists, statisticians, computer scientists, UX designers, product manager and full stack
developers -people thinking in different way. A flat organization.
d) Made it an agile group and kept talking about successes and failures- total transparency and trust.
e) We were business driven and trying to solve business problems with specific KPIs for success.
Every iteration we had to bring suggestions to business how it will help them.
f) The key point was when we started questioning the business -how do we get these demand forecast
Think about how you can streamline the data ingestion, data intake and integration using tools like
Dominos, Alteryx etc. Choose the right tools at the right time. Do not wait for the perfect technology
stack.
g) How did I build and retain the team=
Change the Leadership mindset, provide a career growth path, Hackathons and competitions,
sponsorships, Problem solving and innovation approach, Challenge and professional development,
Recognition and reward, Teamwork and team building, Providing internal mobility, Learning
opportunities
Summary for hiring=Hired talent outside and inside, be business driven, be agile, tech stack is not the
first key of success. Had a goal to democratize data and the key is to reach the goal, show progress and
results by using the right tool and the right size
What are the key requirements and lessons learned=
a) Top management commitment – have to be very open minded.
b) Integrate with business
c) Have a great relationship with IT.
d) Expectations and portfolio management of stakeholders
e) Recruit and mentor talent
f) Understand there will be resistance to change
g) Becoming a data driven organization
How did I create a data driven organization=3 points

2.  Consciously mapped how the organization used data in each phase of the product lifecycle
 Treated data as first class citizen
 Created a culture which expects decisions are made on basis of data at all level of organization