Data Analytics is becoming the main driver of innovation in the financial services industry. A recent report shows that data analytics investments in the banking sector totaled $20.8 billion dollars in 2017 and will certainly continue to rise as credit union executives leverage the wealth of potential that utilizing consumer data and developing successful, sustainable data strategies enables.
While more and more credit unions are realizing the value and future potential of data analytics, they are still grappling with some barriers, including: lack of in-house talent, how to appropriate their analytics budget, and formulating a data analytics strategy that sticks.
Plotting the Best Course
In my years of consulting credit unions (and work with organizations in the healthcare, retail, distribution, and government sectors) to help maximize the value of their data, one common thread I see among many is the lack of a strategy and a road map that plots the organization’s best course. What is a data analytics strategy?
The strategy allows your organization to establish goals from the starting point to provide direction, alignment and a clear path to success. I’ve reviewed several of the key benefits of creating a strategy in a past post. Simply put, your strategy will help you create a solid plan, determine your objectives, allow you to bridge the talent gap, communicate the data analytics objectives and mission to your team, set and measure benchmarks, assess technology capabilities and data quality, and so much more.
Additionally, having a data strategy ensures that data is managed and used as an asset and not simply as a byproduct of your organization’s processes. By establishing common methods, practices, and processes to manage, use and share data across the credit union in a consistent way, a data strategy ensures that the goals and objectives to use data effectively and efficiently are aligned.
Making a Data Strategist
Often, I see credit unions attempt to formulate a data strategy internally using two approaches. The first approach is to assign the task of establishing the data strategy to a line-of-business head. Perhaps, a Chief Lending Officer or Chief Marketing Officer – someone in a strategic position that sees the big picture for the credit union. The second approach is to pass it off to IT or another technologist. This individual tends to build the strategy from the ground-up – focusing on the tactical and technical challenges without necessarily knowing the full strategic picture.
The problem with the first approach – using a line-of-business strategic leader – is that these individuals rarely understand the tactical and technical aspects of day-to-day operations that must be factored into any data strategy. They might be quite adept in their LOB (i.e. marketing, lending, retail, etc.), but they will struggle to adequately understand how the daily use of data and processes must be addressed by a data strategy. The outcome from these individuals tends to be a very strategic and conceptual deliverable for what data analytics could do for the credit union – rarely does it address the how.
The flaws of the second approach – using a technologist or IT resource to formulate the data strategy – is that these individuals do not have strategic insight of the credit union nor the enterprise-wide perspective that is necessary. They may know certain systems or processes inside and out – valuable, no doubt – but lack the big picture for how integration prioritization, deployment and change management planning, and other more strategic decisions need to be factored into the establishment of the strategy. These individuals tend to place too much focus and emphasis on the technology decisions and not enough focus on other critical aspects that a data strategy entails.
What’s The Best Resource/Team to Create a Data Strategy ?
The best individual or team to establish your credit union’s data strategy is one that balances the strategic business needs of the organization with the technical and tactical requirements that must be addressed. The best team/individual understands that the technology choices you make are no more critical than how you handle cultural change management throughout the analytics solution implementation. Striking the perfect balance between business and technology with the right blend of strategic thought and a tactical mindset are key.
The catch? I rarely see this work using only the credit union’s internal resources. Every vendor has a “analytics solution” now and every company that does anything in consulting or IT has a “data strategy service”. It’s difficult for individuals within an organization who lack the deep understanding of the analytics solution and service marketplace to formulate the right data strategy that isn’t heavily dependent on sales material alone.
Unfortunately, many data strategy service offerings are led by either line-of-business strategic leaders (approach one from above) or by pure technologists (approach two). Just like this doesn’t work within a credit union, it certainly doesn’t work with your consultants.
Find a firm that has the right resources from both the technology/tactical realm as well as those with deep strategic line-of-business expertise. Only with that blend of skills will you yield a data strategy that can guide your credit union to both short-term and long-term analytics success.
Looking for help with developing your data strategy and plan for analytics? The Knowlton Group is staffed by resources with both extensive technical analytics skills and decades of a line-of-business strategic leadership knowledge. We’ve worked with many credit unions in the past by helping them understand the full impact of data analytics to their business model, define a compelling data analytics strategy and ultimately provide results. From strategy, to conceptualization to full implementation, we are ready to make your credit union a data-driven organization. Contact us today.