The Decision Maker

Top 5 (and 5 most missed) of 2016: Credit Union Big Data and Analytics – Part 1

Posted by Mark Portz on Dec 29, 2016 12:39:55 PM

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TOP 5 (AND 5 MOST MISSED) OF 2016: CREDIT UNION BIG DATA AND ANALYTICS – PART 1As 2016 draws to a close, it is time to look back on all that we’ve learned, and apply it to better our organizations for 2017. The credit union industry is rapidly changing as financial institutions are gaining better understandings of the necessity to optimize analytics and become truly data-driven organizations. As 2016 comes comes to an end, I have taken the liberty of compiling some of the industry’s favorite Big Data & Analytics related articles (and some you may have missed) from OnApproach’s blog, The Decision Maker. This is part one of two and features the most read pieces of 2016. Click here to see Part Two highlighting the some good reads you may have missed over the year. Enjoy!


The Top 5 Favorites:

  1. Identifying & Measuring Value the Credit Union Gives its Members

Value is a difficult term to quantify as it has many interpretations. Fortunately, Eric Almquist, John Senior and Nicholas Bloch from Bain & Company have tackled this problem and published their findings in a recent issue of Harvard Business Review.

To summarize their research, they identified value which they delivered as a Maslow-inspired hierarchy of four needs; functional, emotional, life changing and social impact. Each need tier is further subdivided into value attributes that help provide clarity and definition to each need. The authors state that when these needs are combined, they increase customer loyalty and drive revenue growth. Click here to learn about the methods to identify and develop organizational value...  

  1. Big Data vs. Little Data: Part 1 - Structured and Unstructured Data

It’s clear now: Data can be one of a company’s most valuable assets if properly stored, managed and analyzed.  What’s unclear to many however, is what data is the most valuable and how to harness the value of each type of data.  There are two main types of data: “Big Data” and “Little Data” or, respectively, unstructured data and structured data. Both types of data can deliver a significant amount of value to a credit union. However, figuring out how to harness each type of data can be a challenge when dealing with the array of different data sources. Finding a healthy balance is key to delivering value without succumbing to analysis paralysis. Learn more about the differences between big and little data here...

  1. The Death of the Branch: A Lesson for Credit Unions

Just over 20 years ago, Amazon entered the book market with a simple mission – deliver personalized experiences to its customers and make each interaction unique and customized to the individual.  At the time, Amazon was just one man, Jeff Bezos, selling books out of his home. For the book market retail giants, Amazon was hardly a threat, just some crazy guy trying to compete with very large and long-established institutions – companies such as Barnes and Noble and Borders Books which had well over a thousand retail locations and were selling books hand over fist.  Well, we all know how that story ends - Amazon is one of the top retailers in the world and Borders Books is now bankrupt with its failing assets being absorbed by Barnes and Noble, which is still struggling today. Click here to see how this lesson relates to credit unions...

  1. Why Attracting Millennials Requires Data Analytics

Millennials are living in a vastly different world than their Baby Boomer parents. They live in a time in which a phone isn’t just a piece of plastic used for making calls, it’s now “smart” and acts as an extension of oneself. A time in which “going shopping” or “depositing a check” no longer requires you to leave home. We are living in a world dominated by the rise of online/mobile and the demise of brick-and-mortar. This changing consumer landscape is being primarily driven by Millennials as they demand more personalized experiences. Read the rest of the blog...

  1. The Evolution of Credit Unions

We all know that our economy and our society is evolving rapidly through data collection and advanced analytics, yet we are surprised by news each day of another business area adopting advanced techniques. Within the world of finance, credit unions are beginning this same evolution. 

We might think “even credit unions” are changing, but with thousands of credit unions and a naturally more collaborative environment, groups of credit unions are combining resources to deploy advanced analytics. Although this will happen naturally, the proposed CECL accounting rules for loan loss reserves will cause a dramatic shift in the use of data and analytics at credit unions, comparable to the changes occurring at larger banks due to CCAR and DFAST. Read more here…

Make sure you don't miss part two! To keep up with more articles like these, subscribe to The Decision Maker, and get it directly to your inbox.

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Topics: Big Data, Data Analytics