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How can credit unions pull off data-driven transformation?

At a typical credit union, employees are overtasked, experience and data skills are in short supply and overburdened IT systems are unlikely to be able to handle the incoming tsunami of new data. In this reality, how can credit unions find a reliable way to move their companies into the data-driven future without endangering the present?

The task is imperative, and can only succeed if it is cost-effective, incremental, and sustainable. This means starting off with pilots that pay off quickly, followed by a strategic plan to prioritize important use cases and, last but not least, developing a program for building long-term capabilities.

This three-step approach is faster, likelier to succeed and much more cost-effective than a complete overhaul of your strategy.

Phase One: Identify quick-win initiatives

First, identify rapid digitization efforts that can deliver quick wins. These projects will make an immediate impact in key areas. Sales support or marketing are likely targets. Rather than taking years (as re-inventing your core IT system would), wins occur within months and the benefits can be communicated throughout your credit union almost immediately. Pilot programs like these prove that your credit union can benefit from data-driven digitization, and provide important lessons on how to roll out data transformation across the enterprise. The extra value that quick wins create helps pay for longer-term efforts, potentially making the transformation self-funding.

These initial projects might be limited in scope but it is extremely important that they succeed and serve as a convincing, internal marketing machine for the benefits of digital transformation across the credit union. For this reason, choose projects with care and also be pragmatic about execution. Try to avoid projects that require a fundamental change or restructuring of your data strategy. Quick-win projects should be limited in their timeframe (3 to 4 months), and their value should be demonstrable within weeks. In this phase, you can develop the ability to execute quickly across all departments. Quick wins will also energize and inspire managers and employees, who will benefit from the success and impact.

How do you ensure the success of quick wins? Follow these three steps:

  1. Collaborate with your staff to identify immediate opportunities: Ask your IT, marketing, risk, lending, compliance or member service to engage their teams to collect and rank ideas. Impact, Time, Cost and Risk form the basis of a simple business case.
  2. Adjust accountability, budgeting and reporting, give your teams the authority and accountability to move toward innovation: Transformation needs to happen quickly. Forgo traditional budgeting allocation and implement simple weekly or monthly reporting to measure impact and track progress.
  3. Redefine risk: Expect that some projects in this phase will fail. Even so, your credit union will transform faster with less cost, and may achieve positive changes in productivity, safety, efficiency, performance and customer satisfaction by working with startups and scaleups.

Phase Two: Create the vision

Once you have established quick wins, you can start preparing a roadmap for the data-driven transformation. This begins with a clearly defined vision, which you can translate into a ranked list of initiatives. The logical order of initiatives could be based on factors such as size of impact or opportunities. This involves identifying and prioritizing departments and initiatives that can benefit most from transformation, while also identifying possible roadblocks. While developing your vision, you need to understand where your credit union stands in terms of data, digitization, and current capabilities. You need to quickly and objectively assess your situation and gauge how your capabilities stack up against best practices. This assessment of data capabilities gives you the information you need to carry out the following five critical steps:

  1. Build a vision: When planning a data-driven transformation, set the appropriate vision for your business.
  2. Select the portfolio of initiatives: Using the vision and strategic priorities, create a full list of transformational initiatives.
  3. Devise an analytics operating method: Specify how you want the data analytics function to work, how much should be done in-house and how much should be outsourced.
  4. Establish data governance: To ensure the quality and integrity of the data you will use for business decisions — with and without human intervention — you must have strict governance rules and a data governance structure.
  5. Define data infrastructure: Ask yourself: Can our current infrastructure support our future data value map? Should we make or buy?

Phase Three: Organizing for repeatable performance

In this phase, digital and data-driven processes and work methods spread to every corner of your credit union. Each employee learns to work across silos to enable data-driven processes, and leaders make the organizational changes necessary to make these new approaches sustainable. You create a data-driven culture by investing in the ability to use analytical insights and embed new mindsets, behaviors, and ways of working.

To deliver a sustainable performance, move on these three fronts:

  1. Define new roles and governance rules: Make clear who has responsibility for building and running new systems, and maintaining specific types of data. Embrace risk. Act more like a software developer, embracing a test-and-learn culture that encourages experimentation, accepts — even celebrates — failure, and is always learning.
  2. Adopt agile ways of working: Use the agile method in everyday operations to increase responsiveness and adaptability.
  3. Cultivate the necessary talent and skills: For data-based transformation to work, it’s important to have talent with the right skills to execute data-driven strategies and manage data-based operations. This may mean retraining current employees, hiring new talent or using a partnership to get the right capabilities.

No wonder data-driven transformation has become an intriguing opportunity for leaders and executives in the credit union world. We all desire to make better decisions and digitize processes to improve performance and efficiencies. And, there’s certainly pressure to keep up with competitors who are considered leaders in this space. This might tempt some credit unions to make huge bets in hopes of achieving quick, enterprise-wide change. In many cases, this will turn out to be counterproductive. Instead, the winners will be agile, pragmatic and focused on small, quick steps. While they move fast and create small wins across the credit union, they will carefully develop a transformation roadmap to optimize performance and impact. They will work under the premise of “Success is a series of small wins.”

If you’re interested in AI, Machine Learning and Data Strategy, please sign up to receive the current issue of THINK Review Magazine: The Data Strategy Issue.

And, please join us at the Grand Sheraton at Wild Horse Pass in Chandler, Arizona, May 7 to 10, 2018 for THINK 18, the premier conference to discuss AI, Machine Learning and Data Strategy.