The Decision Maker

6 Steps to Develop a Data-Driven Vision

Posted by Nate Wentzlaff on Mar 19, 2015 12:30:00 PM

As an industry in the middle of a massive shift, credit unions must steer in the best direction to enter a prosperous future.

Data-Driven-Credit-Union

The Financial services industry has traditionally been an industry where change happens gradually at the direction of a few large institutions.  Since the introduction of the internet in the 1990’s, finance has been in a state of exponential change.  The digitalization of money is causing an even more powerful catalyst of change: the proliferation of data at a pace most credit unions cannot fathom.  Consequently, credit unions must form a data-driven vision to act as a strong rudder to navigate through the data storm.

Step 1: Establish a Data-Driven Culture

Big Data/Analytics experts have been preaching the need for organizations to establish a data-driven culture for years.  Many authors have spoken at length of the necessity and advantages of becoming a data-driven organization.  Credit unions are no different.  With more data than most industries can only dream of, they stand to gain the most (or fall the hardest).  Management must lead by example by developing data-driven metrics for the entire credit union.  Establishing a culture that relies on data is essential to the progression of a data-driven vision.

Step 2: Conduct Thorough Data Analysis

Before casting a vision, credit unions must conduct a deep analysis of their data.  A credit unions history lies within its data. Data informs credit union employees what has occurred at the credit union (and what has not).  Most of the time, there is a vast difference between management’s perception and the data.  Utilizing data analysis tools, credit unions have the ability to draw a clear picture of their institution.  With the art and science of data visualization, management can develop a deeper understanding of where the credit union has been and where it is going.  Understanding a credit union’s history (through its data) is the best way to establish a data-driven vision that will stand the test of time.

Step 3: Construct a Mission Statement

Many credit unions build their mission statement at a remote location with ambitious and ambiguous goals.  There is usually an inadequate understanding of data.  Most mission statements should be called fantasy statements because they are not built on facts.  Credit unions that do this are stuck in a top-down philosophy and think that a mission statement should come only from visionary leadership (without the process of data analysis).  The mission statement, however, should be built from the bottom up.  Clearly analyzing the historical facts of the credit union will give leaders a much better foundation to envision their future.

Step 4: Incorporate Industry-Founding Documents

The credit union industry was founded on the 7 cooperative principles. As members of the cooperative movement, credit unions should incorporate these principles within their vision.  Financial services have gone through many transformations throughout history as various ideas of money management have been developed within diverse societies.  One of the strongest movements has been cooperative finance.  Cooperation has revolutionized how money is managed in societies throughout the world.  Incorporating ideas from the founding documents of cooperative finance will strengthen the data-driven vision.

Step 5: Integrate Financial Laws

The local, state, and national laws that govern a credit union’s membership will shape its data-driven vision.  Laws are constantly changing and credit unions must participate in the creation and elimination of laws throughout the legal system in which they operate.  Developing analytics on various laws (and their effects on the credit union industry) will help management pilot their respective departments. 

Step 6: Continuous Vision Improvement

The modeling of business processes in their current state (and the data models which support them) is the reason a credit union needs a well-established vision that all employees and members can adhere to.  The vision must be taught and re-taught as it lives and breathers life into the credit union.  As credit unions continue to develop data-driven visions, they will be able to lead their memberships into the future of financial services.

Topics: Analytics, Big Data, Data Integration, Members, Decision Support, Big data/analytics, community, data integrity

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