Bringing Data Analytics Home,
Making Data Analytics Part of Your Credit Union DNA

By: Peter Keers
October 15, 2019

In a 2018 global study of $1B+ companies, McKinsey and Company found 8% of the surveyed companies were leveraging data analytics to bring real value. The lessons learned from those companies can serve as a guide for credit union decision-makers to craft their pathways to successful data analytics. The findings fell into three categories:

• Aligning on strategy
• Building the right foundations of data, technologies, and people
• Conquering the “last mile” by embedding analytics into decision making and processes

CATEGORY: ALIGNING ON STRATEGY

1. Obtaining a strong, unified commitment from all levels of management - from the top-down
While grassroots movements sometimes work in the political world, successful analytics programs seldom start this way. Your senior leadership team needs to champion the drive to establish an analytics culture. This means top managers must learn how to raise analytics awareness across the organization. Professional education may be necessary for senior managers and middle management. It is this corps of managers that extend analytics to all corners of the organization.

2. Increasing analytics investments, with a focus on the “last mile.” A road map to drive analytics out into all levels of the organization is a substantial investment.
As in any race, the last mile is the toughest. For analytics, the “last mile” is bringing the analytics culture to the furthest ends of the organization. It is at that point that analytics can truly deliver its highest potential. However, this is an expensive proposition. To paraphrase the 80/20 rule, the last 20% of the journey to an analytics culture takes 80% of the effort. However, it is a wise investment given the potential of delivering analytics capability across the organization.

CATEGORY: BUILDING THE RIGHT FOUNDATIONS OF DATA, TECHNOLOGIES, AND PEOPLE

3. Developing a clear data strategy with robust data governance
Credit unions are realizing increasingly that their data is a strategic asset. Until recently, however, this asset was profoundly undervalued, resulting in weak or non-existent data management. Inadequate data management introduces a host of risks that hamper a smooth progression of building an analytics culture. An early priority in the analytics journey is understanding the extent of the data management challenge and crafting a blueprint to bring things up to par. Programs like Data Management Consulting can provide a jump start for your credit union towards achieving a desirable data management maturity level.

4. Using sophisticated analytics methodologies - Leverage vendors.
Except for the larger organizations in the industry, credit unions typically lack the staff with the right skills to make use of cutting-edge analytical tools. It is limiting your ability to take advantage of innovative techniques that are constantly being introduced into the market. There is an opportunity for credit unions to leverage vendors that are up-to-speed with the latest analytics tools. Once your data management is at the right maturity level, making that data readily available to state-of-the-art tools will bring value faster.

5. Possessing deep analytics expertise enabled by a tailored talent strategy. Build your own in partnership with vendors.

A credit union, especially a small one, could indefinitely follow the strategy noted in #4 above. However, many organizations seek to build their internal capability for a variety of reasons. Reduced cost, tailored solutions, and faster turnaround are all possible advantages.

Building an internal analytics capability can happen in many ways. An obvious one is to send staff members to analytics training. Another is to leverage vendors. Building a knowledge transfer stipulation into vendor contracts will allow credit union staff to acquire the necessary skills to make the analytics journey a primarily internal effort.

6. Creating cross-functional, collaborative, agile teams. Don’t silo data efforts.
While a top-down push and empowerment of middle management are essential, driving analytics to all levels of the organization will also require cross-functional teams. A significant risk in promoting analytics across the organization is uneven adoption that results in silos of expertise. If conducted on a department by department basis, some areas will climb the learning curve faster. A solution to this is to create crossfunctional teams that bring the organization to new levels of sophistication evenly, thereby maximizing the analytics investment.

CATEGORY: CONQUERING THE “LAST MILE” BY EMBEDDING ANALYTICS INTO DECISION MAKING AND PROCESSES

7. Prioritizing top decision-making processes. What are the pain points?
Building a cross-organization analytics culture impacts decision making across all levels and functions. It also presents a problem of where to start. Luckily, you can address this with a familiar business prioritization technique of evaluating “pain points” in the organization. Executives typically have a keen awareness of the foremost issues facing the credit union – start here. However, this process must be updated continuously to prioritize the most critical problems.

8. Establishing clear decision-making rights and accountability. Who makes what decisions at what levels?
This prerequisite should be a priority even if analytics are not on the radar. Astute organizations think through what decisions to make, in which department, and at what level. In establishing this framework, the business is simply in a better position to reach its strategic goals.

9. Empowering the front lines to make analytics-driven decisions. Providing the tools at all levels.
In organizations where there is an established decision framework, the effort to deploy the right analytics in the right place at the right time becomes immensely more efficient and brings business value much faster.

Where are you on your data journey? We would be excited to partner with you no matter where you are. Send us an e-mail or visit us.