Four Incremental Steps to Data Transformation
Evolution does not happen overnight. Leaders who take small, thoughtful steps deliver the most meaningful change over time.
By Shazia Manus, Chief Strategy and Business Development Officer, AdvantEdge Analytics
As a new, digital world has layered over the physical one, a parallel universe of unfathomable potential has come into view. It’s not only our opportunity, but our responsibility, to get in there and explore the ways we can play in this new reality.
Increasingly, we see that mastering digital engagement with members hinges on a credit union’s ability to translate data into insights. Credit union leaders who can actually hear the stories their data is trying to tell transform faster. It’s why we say digital and data are two sides of the same coin.
That is certainly not to say data transformation is easy. Reprogramming our analog minds for the digital era is not something that can be completed in a year, or even two. And in the credit union space especially, with challenges around legacy infrastructure and outdated technology, data transformation requires strong leadership and an equally strong vision.
At the same time, there are incremental steps that can be taken to deliver meaningful change over time.
1. Start at the Problem
I just started pushing myself to become a runner a few years ago, and I’ve learned a lot about how to “win” a marathon. It’s not about being the first one to cross the finish line. It’s about setting your own personal goals. In my first race, the goal was simply to finish. By the second, I wanted to complete the race without stopping to walk. Today, I’m focused on much more professional sounding goals like per-mile minutes.
The point is, a credit union’s data transformation goals should be specific to its organization – or more importantly, its members.
By focusing on the real and pressing problems to be solved, credit unions have a leg up on transformation. While trial and error will still be a part of the journey, the achievement of various milestones will happen faster.
2. Build a Data Corpus
Executing on a transformation plan requires a lot of data and a strong competency around analytics. Of the problems a credit union identifies, it’s important to know which are likely to bring the volume, velocity, variety and veracity of data necessary to properly deploy a solution.
It’s equally as important to make a plan for how the credit union will ultimately process large volumes of data. This is where cloud computing enters the picture.
Gartner predicts that cloud data centers will process 92 percent of workloads by 2020. That’s next year. Will credit unions be among those benefiting from the cloud? Or will they be steamrolled out of position by more nimble digital brands that know the cloud because they were born in the cloud?
The cloud isn’t just about capacity and speed for processing data; it’s really about agility. The movement will have to become more nimble to stay relevant and competitive. With cloud solutions on our side, we stand a much better chance of discovering new value propositions.
While I’m a big thinker, I’m also a realist, and I talk to a lot of credit union people. I hear the objections to the cloud, and frankly, a lot of them still center on myths around security vulnerabilities. We need to change the conversation as an industry to move past those fears and get real about what it’s going to take to give our most important stakeholders what they expect in this era of real-time, hyper-personalized and predictive demands.
Rather than ask “Is the cloud secure?” I think the movement would be much better off asking “How can we use the cloud securely?”
3. Exploit and Explore
To know where you’re going, you have to know where you are. Credit unions can think of data transformation in terms of “as is” and “to be” states. By doing the work to exploit core competencies while also exploring new horizons, credit unions have a clear picture of the areas where data analytics and cloud computing can help deliver that competency in an even richer way.
Credit unions should think about the future through the lens of their members’ own evolutionary track: What will they need tomorrow? How is the credit union uniquely positioned today – or capable of becoming positioned tomorrow – to meet their changing needs?
To read more on exploit and explore strategies, check out “The Infinite Potential of People Helping People in the Digital Era.”
4. Establish a Culture of Analytics
Because data analytics is rooted in exponential technology, it calls on organizations to have agile strategies nimble enough to evolve quickly as new technology, methodologies and consumer demands dictate. Organizations with analytics cultures invest in data and visualization platforms so insights can become available across the enterprise. They also encourage and empower employees to think ahead, and to never be afraid to fail. Not all ideas are great when they first land in our frontal lobes. They have to be massaged, tested, retested and reconfigured.
Cultures that foster an experiment to learn mindset empower their leaders to take risks and be okay with micro-failures.
Consumers, including credit union members, are beginning to feel the results of data transformation. They see it in the user-centric strategies and improved digital channel experiences they get from all the brands they let into their lives. Credit unions are certainly feeling pinched to keep up. But, there is no reason we can’t. By taking those first steps and progressing down a path of incremental change, members will begin to feel the credit union difference in entirely new and highly personalized ways.