How long does it take to step away from your desk, go to the bathroom, and return back to your desk? Eight minutes for Jim Bampos, Vice President of Total Customer Experience at EMC. Eight minutes is also the time it takes his organization to run a Customer System Reliablity report, thanks to Big Data. Jim Bampos calls this Bathroom ROI, as shrinking the report time from five days to eight minutes has had a tremendous impact on improving customer service and optimizing field operations at EMC. The key to this success story was defining a clear business case and partnering with EMC IT and Greenplum, compelling EMC executives to support and fund Jim’s Big Data vision.
What is the goal of the Total Customer Experience(TCE) organization at EMC?
Our goal is to provide the industry’s best total customer and partner experience through a customer-focused, data-driven strategy via management and analysis of data.
Sounds like a data driven organization. That is what Big Data is all about. What led TCE to embrace Big Data to improve customer service?
We actually didn’t realize the potential of Big Data until EMC brought it to our attention. We as an organization collect and aggregate all kinds of quality and experience metrics that represent customer performance – system reliability, product quality, customer service, and other metrics that are really focused on quality as defined from a customer’s perspective. For example, there is a tremendous amount of data, from numerous data sources, that goes into generating System Reliability metrics. And for each customer, system reliability is based on the architecture, the part numbers, supplier information, shipping information, service request data, etc. So there is a lot of data and complexity that goes into generating a System Reliability report.
Big Data is not just hype, but rather a catalyst for organizations to rethink about how they can leverage modern, Big Data technologies to deliver business value. Would you agree?
Yes. We approached Big Data as an opportunity, first by leveraging our System Reliability metric because we know it’s what our customers value, and would also give EMC a competitive advantage. This metric is also monitored on a regular basis by many stakeholders across EMC, so we knew we had a solid business case or justification for our first Big Data project, since it is a metric critical to our customers’ success and critical to EMC’s success. The project’s success provides the foundation for EMC’s transformation of the TCE program via Big Data
In order to meet your goals for System Reliability, you chose EMC Greenplum as the Big Data platform. What pain points were overcome with EMC Greenplum?
We gave several challenges to EMC IT and the Greenplum organization to see if we could really gain value from Big Data. First, we wanted to reduce the time it takes to generate a System Reliability report for each customer. Second, we wanted to leverage EMC IT, the Greenplum team, and the Data Scientists team to see what gems we could uncover with massive amounts of historical customer data. Last, we wanted to become more automated in nature so that when a Field Service personnel calls or a Sales Rep calls and says, “I need to understand Systems Reliability performance of my customer over the last five years,” it doesn’t take a person in my organization five days to generate that report when the sale is going to be closed tomorrow.
We were very successful in terms of our partnership with IT and Greenplum, as the partnership with IT and power of the Greenplum Unified Analytics Platform exceeded our expectations. After successfully loading 12+ TB of historical customer data into the Greenplum Database, we reduced the time to generate one customer System Reliability report from five days, to eight minutes. I call this ‘Bathroom ROI’ because that’s usually the time it takes from hitting submit, going to the bathroom, and coming back to find the report complete.
At the same time, we enrolled people within our own organization in the EMC Data Science and Big Data Analytics training as an opportunity to become more predictive when it comes to System Reliability. Our new ‘Data Scientists’ worked closely with the Greenplum Data Science team to uncover the ability to predict part failure six to twelve months ahead of time for every customer. For example, if we could predict that a disk drive was going to fail six months ahead of time of when it failed, we could create a service request to a customer, go into their site, backup their disks, replace their drives, fully load them back on and be gone before the customer even knew there was a remote potential of a problem. There are opportunities ahead of us that are almost limitless at this point.
When you said Greenplum exceeded your expectations, what did Greenplum do that made you realize, ‘wow’?
I think two things. One was the fact at how easy it was to take data sets from different systems and consolidate it into the Greenplum Database without worrying about complex database schema design. The second is the speed of the Greenplum Database. It really is unbelievable.
So how does Big Data translate into business value?
Lowering operational costs, in terms of preventing failures. The engineering and global manufacturing teams needed faster reports in order to quickly identify critical failures, test them, and take corrective action to fix and prevent future failures. We were allowing failures to happen on a more regular basis and needed to improve the speed of getting those reports out.
Increase in customer satisfaction and deal close rate, in terms providing better sales support during a major sales cycle. Five days is unacceptable in a sales engagement where a major customer was asking EMC to demonstrate our product’s System Reliability performance.
Improved productivity, in terms of faster and automated report generation. The entire process for generating a system reliability report was automated; therefore, an individual on my team no longer had to spend five days in generating a single customer System Reliability report.
We are now looking to integrate all of the unstructured data around Voice Of Programs such as open text responses. An example would be, “How can we better serve you to make you more successful as a customer?” By correlating customer responses to other customer attributes, we would be able to uncover additional insight to improve customer loyalty.
If you were talking to one of your peers in the industry, and they need to get buy-in from others for a Big Data project, what kind of advice would you give to your peers?
Think big, start small. Create a use case and/or a business case that will compel executives to buy into your project, while having an enterprise program as the overall goal. When we did System Reliability, it was an early success because we had a clear objective in mind to prove the success, which will then enable us to scale the program to the Total Customer Experience. The reason we got buy-in was because it is a key metric that our customers and EMC uses to drive business.
For more with Jim Bampos on Big Data, read latest article from Fortune