“In Conversation With” is a video series where NTT i3 executives engage in conversation with some of our most visionary partners at NTT’s Operating Companies and global enterprise customers, futurists, and leading Silicion Valley technologists, entrepreneurs, and researchers. The explorations may be around current and near future developments in IoT, big data analytics, machine learning, AI, network virtualization, and security. At times, we also investigate the human impact of technology and the role our values and culture have on how we decide to use what we are inventing.

In this episode, Ravi Srivatsav (CPO and CBDO at NTT i3) joins Scott Gibson (Group Executive for Dimension Data’s Digital Practice) from the finish line at the Tour de France in Paris.  The topic: How machine learning and predictive analytics create new immersive experiences for Tour de France Fans.

Ravi:

So let’s continue the conversation and jump into my favorite topic about machine learning and predictive data analytics.  At NTT i3, we’ve done real-world prototyping as well as released products to help leverage the data that we collect from telemetrics and human sensors in projects such as IndyCar Racing and the Toyota Prius Challenge. There’s been a ton of learning that’s come from these inititatives.

 

Scott:

What’s been so exciting for us this year is working with NTT i3 to be able to use machine learning and predictive analytics. We’ve used this with our various digital platforms to predict who the winner would be, who the top 5 would be – and we’ve had a lot of success.  It’s an exciting development for 2017.

Machine learning is about ultimately improving the customer experience.  For us and the Tour de France, it’s about improving the fan experience.

 

Ravi:

So Scott, what were some of the things that you used machine learning algorithms to predict and what were the outcomes?

 

Scott:

We used machine learning to predict a couple of things this year.  We had the DD predictor that gave ratings for first, second, and third place riders at the end of each day – and with that we had a 75% success rate.  Secondly, we provided predictions on the top 5 for the end of each stage – and again we got to a 75-80% success rate.

 

Ravi:

How did the audience react to this?

 

Scott:

With DD predictor, we saw a lot of blogger and reporters start to reference it, as well as a lot of retweets of the social content we provided. I think that we increased the Tour de France Twitter followers by about 8000 people this year.  There’s no doubt that having this information available and creating a different story to the race has been an important aspect to this years Tour.

 

Ravi:

It’s great to see how audiences react to stories and experiences created and delivered through data.

 

Scott:

That’s the reason we do this. What we have delivered for the Tour can be applied within any vertical industry – automotive, retail, manufacturing, you name it. IoT, hybrid IT, the cloud, cybersecurity, machine learning, predictive analytics, and collaborative distributed workforces are important for all businesses. I think that we have shown that as a group we can get this right.

 

Ravi:

In wrapping up this conversation, innovation is all about continuous learning.  So what are some of your experiences and learnings from this year’s Tour de France?

 

Scott:

One of the key learnings has been that this is a difficult environment for delivering a data solution. There’s not a fixed office or data center; it’s in constant motion everyday.  We’ve really had to think on our feet to make sure that we understand as a company how to manage that.  The cloud and virtualization have been our saviors as far as that is concerned. Our ability to leverage to be able to leverage more computing power through the cloud has been our number one learning.

Second- we were also surprised about the 75% accuracy of our machine learning predictions – how high that was. Sports is always so unpredictable in its nature, so this level of accuracy was surprising. It’s given us the confidence that machine learning is here to stay, and that it is something that we can apply in other vertical and industries that are probably more predictable than the one we are in (Tour de France.)

 

Ravi:

It was great working with your team. I look forward to working with you on the 2018 initiative.  The experiences that we can supply to the audience is limitless with machine learning.

 


Next: Ravi and Shriranga Malay talk about how the convergence of IT, OT and IoT are changing datacenter operations and customer expectations. Or, click here to check out all of the videos in our “In Conversation With” series.

 

30 Most Innovative Companies 2017 – NTT i³: Finding a New Approach to Innovation
Using Machine Learning to Redefine the Travel Experience at the 5th CMU-Emirates Hackathon
The Future of Smart Cities – A New Relationship Between Technology Companies, City Government, and Citizens
NTT i³ Exhibits CLOUDWAN at ONUG Fall 2017 Conference: CLOUDWAN is a Powerful Next Generation Networking Solution Enabling Organizations to Future Proof Their Business

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