DataOps: When Success Is Even Bigger Than Exceptional Metrics
Last night we (Delphix) took home top honors from Morgan Stanley with the Innovation Award in the software category.
And yes, there certainly are some impressive metrics surrounding cost savings, productivity gains, and improved time to market that contributed to our win.
But, the thing I love the most about being at Delphix, is the impact that we have had that goes beyond the metrics. I don’t want to put words into Morgan Stanley’s mouth, so let me explain via a conversation I had today at another Delphix customer, a Fortune 20 financial institution.
During our meeting, we were collaborating with our customer to determine and capture additional operational and business-level metrics in an effort to continue to optimize and improve together. They explained that one particular application refresh used to take over 210 hours, best case, before Delphix. Now, that process only takes about 10 hours and is completely automated. Now, if you are a Delphix customer, these types of operational efficiency gains are nothing new to you. After hearing that, I asked the question, “What does this mean to the business? What is the impact that they see?”
The answer I got was unexpected, as I was really driving at “Do you release faster? Do you have higher quality releases?”, etc. His response was, “Our developers are happier. Before Delphix, developing against this application was so hard and cumbersome. Data friction made it near impossible for developers to work efficiently, produce high-quality code, and not break each other’s work due to environment sharing. Now they get fresh data whenever they need it and have all the environments they need. They are over-the-moon happy!”
And though I was caught off guard as to how he interpreted my question, this is a very familiar impact that I hear from our customers, and this is why I am still so passionate about Delphix. Stories like the one above, or about no longer missing t-ball games due to last minute data requests, or not losing their job because of an unintentional data drop that was easily recovered. How can you put a number on that?
And I suppose that is just a reflection of life at large. Sometimes the most important things are almost impossible to measure, but their effects are what matter the most.