Goodyear understands
the Analytics Value Chain

Many business leaders are struggling to understand how to drive business value from IoT. Others are having trouble justifying IoT projects to their organizations. Our view is that IoT Analytics is the key to why businesses are deriving value from IoT, and the Analytics Value Chain is the how.

We have seen that IoT projects have required leaders across an organization (IT, Operations, Analysts) to work together in ways they never have before. IoT Analytics, and more specifically a robust IoT Analytics Platform, allows these key players in a business to work together and successfully leverage IoT.

To understand how to get value and decide where they want to start with IoT, we put together the Vitria Analytics Value chain. This serves as a blueprint of sorts to help them derive value using IoT analytics in a variety of industries. There are six key steps in our analytics value chain:

  1. Ingesting data at speed and volume from IoT sensors and devices
  2. Correlating and contextualizing the real-time IoT data with historical data to provide a baseline for advanced analytics
  3. Extracting situational intelligence from the data
  4. Predicting failures, patterns and opportunities
  5. Prescribing actions based on the predictions
  6. Automating actions

Read more about Vitria’s Analytics Value Chain

The analytics value chain “blueprint” can also help guide companies that are looking to extend their offerings into new products and services. We recently had a chance to learn about a product-services value concept that we think is highly complementary to our value chain concept.

 
 

Goodyear has created a Complementary
Product-Services Value Concept

Goodyear Denver Location for Tires and Service

We were at the IoT Evolution Expo in July and had the pleasure of hearing Jim Euchner, the VP of Global Innovation at The Goodyear Tire and Rubber Company’s keynote presentation regarding how Goodyear is driving business value by re-conceiving Goodyear’s product offerings with a services-centric model. Jim’s concept is very comprehensive and gives product companies a practical framework for making the transition from a product-centric-model to a more services-focused model. When we took a closer look at Jim’s model it became easy to see how complementary it is to the Vitria Analytics Value Chain concept.

The Goodyear value chain has five levels:

  1. Augmenting Product
  2. Integrating Systems
  3. Enabling Intermediate Services
  4. Enabling Advanced Services
  5. Offering Extended Value

 
 

Here are our key takeaways from Jim’s presentation

Goodyear Value Chain from IoT Evolution Expo Presented by Jim Euchner
1. Augmented Product

Goodyear’s first action to leverage IoT to improve their business and offer their customers additional value was to augment their tires by adding internal sensors and to build a mobile application to read the sensors. These sensors made it easy for Goodyear to ascertain the tire pressure and any unusual vibrations. This real-time information was convenient, but only an incremental competitive advantage because other businesses quickly did the same thing.

2. Integrated Systems

The next thing they did was to integrate the feedback from the tire sensors into the automated control systems on actual vehicles. That way the pressure and vibration information was available to the vehicle control system. Incorporating the real-time information into the car’s control system was another wonderful achievement, but it only provided incremental additional value.

3. Enabling Intermediate Services

Looking for ways that they could provide significant additional value in ways that was not as easy to replicate, they started offering intermediate services whereby they used the tire sensors and analytics software to start predicting tire failures days in advance. This gave the tire owner time to address their tire problem and allowed Goodyear to prevent accidents and other negative outcomes caused by vibration and blowouts.

4. Enabling Advanced Services

Unfortunately, tire owners do not always act on the information they are receiving, so Goodyear decided they could do even better by leveraging their own information and analytics to offer a total tire care service. This premium service would manage the entire lifecycle of the tire from installation thru rotations, maintenance and replacement. They could offer this premium service to customers confidently because they were better able to manage their risks and lower their costs by using the data from the tire sensors.

5. Offering Extended Value

They have now reached the pinnacle of value by taking their predictive analytics to the next level and adding prescriptive analytics. Using their sensors and predictive analytics they can now measure driving behavior and predict accidents. They can also prescribe fuel savings strategies to drivers. When you understand what this means, it is huge.
For example, a delivery company can see what driving behaviors are causing the most accidents and then put policies in place to prevent future accidents. This lowers their risk and improves their brand. The system will also tell them the impact of individual driving behaviors on fuel economy, saving thousands of dollars in fuel costs across their fleet.
 
 

Putting it all together

As we mentioned earlier, IoT projects require a lot of cross-departmental collaboration within organization (IT, Operations, Analysts) to succeed. You can see that in the Goodyear example, many different departments had to work together to build the business value around IoT.

Jim did not mention this specifically in his presentation, but here is and educated guess on the roles and responsibilities at Goodyear.

  • Business operations had to decide to install sensors into tires.
  • Manufacturing operations needed to make sure the sensors were installed properly.
  • Analytics teams had to figure out how to leverage the real time sensor data and combine it with other data sources so that they could conduct predictive and prescriptive analytics.
  • Information Technology (IT) needed to enable a mobile solution so that the sensor data was available first to mobile devices and then to vehicle control systems. IT also needed to make real time data from multiple sources, combined with historical data (statistics) available to the analyst so that predictive and prescriptive analytics were possible.

Bottom line, everyone needed to work together to make this happen.

 

As we discussed in our recent blog, The Time has come for IoT Analytics – Accelerating IoT Market Growth and Business Value, most of the technology necessary to bring this altogether is readily available. The one critical, missing piece is having an IoT Analytics Platform available to bring all of the data together in a format where it can be visualized by everyone involved. Jim doesn’t address what kind of platform they used in his presentation, but we know by what they accomplished that it needed to be:

  • Powerful enough to make real-time predictive and prescriptive analytics possible.
  • Capable of ingesting data from multiple places in the organization and integrating it with powerful analytic tools.
  • A platform where the information from not just from one outside company, but other sources as well can be integrated and some of the easy, repetitive decisions could be automated.

 

He also didn’t discuss any planned IoT projects, but we thought of an interesting one!

What if the delivery company in Goodyear’s Extended Value example could use the driving behavior information and fuel saving information and combined it with schedule and location information in real time to instruct their drivers (automatically) when to get fuel and where to get it?

How much would they save by purchasing fuel at exactly the right time with the least possible delay for the best possible price across their entire fleet? Seeing as fuel is one of the most expensive and variable aspects of their business, the savings would be huge.

 

We really enjoyed The Goodyear Tire Company’s presentation because we believe it provides another proof point that leveraging an analytics value chain is the key to empowering business executives to see the possibilities and justify the investment necessary to get started with IoT projects.





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