A guide to Informatica’s Data Transformation
Every one of us is going through his or her own version of data transformation. And we each define that transition differently. For some of Informatica’s customers, data transformation is figuring out how to get closer to their customers, obtaining that end-to-end view. For others, it’s making sense of the sheer amount of data from sensors and the Internet of Things, or it may be offering ambitious new digital services that disrupt, as we say, our legacy business models.
It’s mindboggling to realize that while there is someone in your organization tasked to know how many laptops your enterprise owns, there’s probably nobody who knows how many databases you’ve got, and what’s in them. If your basis for disrupting your market or for defending against disruptors is a data asset, you can’t do it without knowing where your data is, and that it’s secure, trusted, and accessible.
I guarantee you, an airline knows where all its planes are and banks keep pretty good track of their money. Because these are critical assets. And we need to treat our data the same way. But how do we get there from here?
Different Flavors of Data Transformation
We each define our own version of data transformation differently. But I’ve found that through every transformation discussion, there are two common threads. One is that you have to think about this level of change in a connected way across the entire company. It’s no longer about executing brilliantly within one functional silo. It’s about how you can align and unite processes across the whole company for that comprehensive, end-to-end view of your data.
And the second common element across all data transformations is the shift to competing on a digital asset instead of a physical asset. Most legacy companies have entered the digital arena fairly recently. Even Netflix, often held up as an exemplar of the “digital unicorn,” is an older startup whose initial product was physical discs, and whose first competitor was the local brick-and-mortar DVD rental shop. But even companies that were data-driven from their (relatively recent) beginnings are finding it a challenge to extract full value from their data.
My view of Enterprise Data Management
I’m biased, of course, but I’d argue that the CIO has the most critical perspective on data transformation and on the data that is now a core—sometimes the core—business asset. While the CEO is charged with overseeing the entirety of business success, only the CIO has an enterprise-wide view of data and the infrastructure around it. CIO’s see the end-to-end connection across the entire company, how all the different process work together, and how all the applications that serve those processes must to work together to optimize the outcome for the enterprise and, most importantly, its customers.
My approach when I joined Informatica was to understand the legacy. I was pleased that we were already a strongly cloud-oriented company, but there were older systems that were being continually jerry-rigged to keep up with change. So my first step was to eliminate technical debt. And I define “technical debt” as any technology that stops us from moving as quickly as we could and should. We set about remediating such points of weaknesses in the overall IT infrastructure, and I felt lucky that we didn’t face too much of that.
The next focus was a reorganization of how IT works with the business. Before I arrived, we had dedicated resources to business functions like marketing, which resulted in IT leaders being caught up in the business function’s view of its own silo. Instead, we assigned a point person to each key business process, such as campaign opportunities. The result? Individual IT leaders, viewing processes across several business units, are empowered to improve delivery of a business priority.
Take the Full Roadtrip
I hear a lot from our customers about digital disruption, and often share our own approach to data-driven data transformation. If you’re evaluating your own transformation initiatives, check out our Data Strategy Playbook with advice and experiences from successful CIOs.
What are you doing to map out your data? What have you found to be your biggest legacy challenges? While I’m happy to share my experiences, I’m much more interested in learning from my peers so I appreciate you sharing your insights as well. Thanks!