Finding diamonds in data

The right data can help cure diseases, make streets safer, improve customer service and create cost savings. It can help win battles and win ball games. It seems there’s nothing we can’t do better with the right data, along with the tools and skills to analyze it.

To explore the world of big data and analytics, CGI is launching this blog to talk about new applications where people are getting value from data. We’ll also explore the technologies, techniques and, yes, some of the challenges.

Analysts often look for specific kinds of insights that can be used to make something work better in their organizations.  We at CGI, call those insights “diamonds”. In fact, CGI’s common framework for Big Data Analytics is called Data2Diamonds. We’ll be blogging about the diamonds we’re finding in our work with clients, as well as how they are discovered and put to work.

Here’s a shining example.

ThyssenKrupp is a global company based in Germany whose elevator division, ThyssenKrupp Elevator (TKE), is one of the top 3 in that industry. Like any machines with moving parts, elevators require maintenance to ensure they keep working. Looking to use the data they collect from elevators to improve their uptime, ThyssenKrupp Elevator called on CGI and our partner Microsoft to develop an analytics-driven maintenance system. You can learn more about the project by reading CGI’s TKE case study and Microsoft’s TKE case study.

Since this post is about diamonds from data, what insights did ThyssenKrupp find? First, the data told a story about the condition of each elevator and how it was used.  Second, the sensor data about temperatures, vibration and power consumption provided another level of detail on the condition of the elevators and their need for service.

The “Eureka” insight—the diamond—was finding that the probability of an elevator going out-of-service within a week could be measured with great accuracy from the sensor data. (Like many diamonds from data, this is most exciting to people who are actually in the business—in this case elevator maintenance.) An accurate measure of the probability of downtime within a known timeframe means that preventive-maintenance service calls can be scheduled with far greater precision, improving uptime and customer satisfaction at the same time.

This kind of result is what “Data to Diamonds” is all about—in this case, a big “lift” to customer service.