The Data Analytics Strategy Roadmap: Critical Steps Every FI Should Take, Part 1

Here is a surprising statistic I recently read: more than 90% of strategic plans are not successfully accomplished with 67% of failed plans attributed to a breakdown in execution. (1)

I’m a firm believer that strategy without execution will fail and that execution without strategy will also fail. But few organizations have figured out the antidote to close the gap—especially when formulating plans to become data-driven. For those financial institutions ready to implement analytics initiatives, success requires a top-down approach. You should focus first strategically, from a higher level, before you start focusing only on the operational, the technology and some of the tactical components that analytics requires.

Sounds simple, right? If only.

The antidote requires masterful integration and alignment and deployment of high-level goals down to more tactical objectives. Key strategic leaders need to make a top-down commitment to the implementation of data and analytics through communication with the gatekeepers of key operational processes, constant training, reinforcing a culture of accountability, and doing all these things in a manner consistent with a shared long-term plan.

So, how does this correlate to credit unions and community banks working to implement a successful data analytics program? Start with the end in mind by crafting a roadmap to guide you along the journey. These key steps will help navigate your course:

Step 1: Determine your objectives:

The first step in crafting your data analytics roadmap is to clearly understand your financial institution’s strategic business objectives and outline how data analytics will help achieve and/or measure progress towards those objectives. Knowing your strategic business goals now (i.e. deposit growth, opening new branches, new products, digital channel alignment, etc.) and in the coming years will help your organization devise a living, breathing roadmap that aligns analytics with key business objectives.

Establishing your goals from the starting point will provide direction, motivation and a clear path to success.

Step 2: Create a long-term budget:

In budgeting for your BI initiatives, remember that this is not a one-time purchase. A successful data analytics program requires continuous investment as the data needs of your FI grow. In most BI/data strategy projects, plan for a minimum of 18-36 month roadmap. Planning and developing the implementation this way ensures greater success from a development perspective but also allows time for cultural shifts in the organization to take place.

Step 3: Build awareness:

Once you have clearly outlined the long-term strategic goals, during the planning and goal-setting phase, make certain objectives for the data analytics program are documented and communicated with all personnel who will be involved in the initiative. All too often, I’ve seen business and IT leaders develop their own priorities and silos which is a large reason why so many data analytics projects fail.

One of the first orders of business is to ensure the entire organization understands and is aware of why you are building an analytic-driven organization and how it will support the overall business and growth goals.

Step 4: Appoint a committee

Once you have documented and agreed upon the strategic direction, identify the capable individuals within the FI who, given the time and resources, can select an appropriate technology vendor, software upgrade or technology investment for your data analytics program. This effort should not be driven from a technology perspective — instead it must be a business-led effort based upon the strategic priorities of the FI. Senior managers and employees that represent each of the major business functions can bring broad knowledge of the business, operations and existing technologies to the table.

Step 5: Bridge the talent gap

Too often analytics projects fail due to lack of resources or the right analytics talent. Answer critical questions such as: “Does our organization have the right technical team and data savvy talent to achieve the goals we’ve established?”

Analytics projects often require different skill sets especially with some of the new tools and technologies that are available. Drill down and make sure you have the right people in your organization to transform data analytics into profitable insights and actionable information.

As your organization begins to fully leverage data and analytics for decision-making, key staff such as a chief data officer, data stewards, and a data governance team will become increasingly important.

Additionally, when you start combining business, IT, data, and corporate strategy issues all on the same project, you need clear and experienced leadership. Recommended the organization hire experienced outside consultants and third-party partners that can help assess your staff, technology capabilities, and readiness before you launch any data analytics program.

Stay tuned as we provide the final critical steps in deploying your data analytics roadmap.

Does it sound complex so far? Yes, data analytics can be complex especially if you don’t have a roadmap in place to guide your strategy. But, if executed well, analytics systems can have an enormously positive impact for your organization.

Still skeptical? The Knowlton Group can help. Our expertise, years of working with FIs on assessing and implementing a proven data analytics strategy, can work for you.

Contact us today to learn how!

Resources
(1) The Balanced Scorecard, authors David Norton and Robert Kaplan