The Decision Maker

Data Use Cases for Credit Unions: Chapter 1

Posted by Lou Grilli on Apr 29, 2019 11:53:00 AM

Data Use Cases is an ongoing series showcasing real use cases of success that credit unions have had using data analytics to solve real world problems. Data analytics was once the sole domain of giant tech companies – Amazon’s suggestions “If you bought that you might like this”; Facebook’s algorithms that determine which of your friend’s posts you most want to see on your timeline; Google’s ability to propagate data about you so that when you search for something like “hotels in San Francisco” you start seeing ads for restaurants in San Francisco on other sites. With the proliferation of data across multiple systems, the increase in computing power at a decreasing price, and tools to extract and harness data, the science of data analytics to create solutions to business problems, also known as business intelligence, is being increasingly used by credit unions to make better decisions. And it’s not just the biggest credit unions introducing business intelligence through data analytics to their staff. Credit unions with under $500 million in assets are realizing that use cases for data analytics drive ROI, better member experiences, and increased product penetration across their member base. Almost ironically, it is the smaller credit unions that absolutely need to embrace the use of data analytics – they are the ones that need to remain competitive or be merged out of existence.

Data Just For Data’s Sake – NOT!

It’s important to keep in mind that no company, regardless of what industry, invests in data analytics just for the technology. The cost of the tools, the hardware (or more commonly, the cost of cloud storage), investment in staff such as business analysts and possibly a data scientist, consulting services to help get started, can represent not just a significant up-front investment, but an on-going cost that must be justified. The justification comes in the form of use cases – individual examples of data-driven decision-making that makes a difference in how members are rewarded, or sold-to, or what products are offered, or just making a member feel more connected to their credit union through targeted, meaningful campaigns. In fact, for a credit union that’s just embarking on the data analytics journey, the best way to start is with the end in mind. Pick a single use case, a single vexing problem to solve, ideally one that has a fairly high payback if solved correctly. There are many articles that talk about the intangible benefits of business intelligence. But credit unions, especially their CFOs, want to see a return on their investment. The following paragraphs are a few real use cases that credit unions have shown to prove out their investments.

Read More

Topics: Business Intelligence, Data Analytics, Data-Driven

The Comfort of Data-Driven Analytics Decisions for Your Credit Union

Posted by Nate Wentzlaff on Nov 29, 2018 12:22:22 PM

As the next generation begins making financial decisions, credit unions will be able to comfort them with data- and analytics-driven product recommendations.

In the realm of financial institutions, the credit union still offers more than its competition. Whereas credit unions were hampered by limited technological options in the past, new developments in data collection, integrations, and analytics are helping them compete with banks.

Recently, my wife and I were shopping for a mattress. We began the process by “trying out” mattresses by how they felt. My wife thought she preferred firm mattresses, while I thought I preferred soft ones. As we tried mattress after mattress, my wife would ask me, “what do you think about this one,” to which I would usually reply, “It feels pretty good to me.” We became frustrated by our search until we found a mattress store that comforted us with data.

The mattress store (Becker Furniture World) is locally owned with only 8 locations (does this sound familiar to your credit union?). They approached mattress shopping from a data-driven way. By using an analytic data model (developed by Sleep to Live Institute), they are using analytics to aid customers in their mattress investments through data sensors and user input. The data comforted us enough that we decided to purchase one of the mattresses it recommended.

Data Acquisition from Users

When we walked into the Becker Furniture World, it was different than all the other mattress stores. There was a futuristic-looking canopy near the front of the store. We asked a store associate what the machine was and were informed that it collected data from our bodies and sleeping patterns to recommend the best mattresses. Before entering the contraption, we entered in personal data about ourselves using ranges for age, weight, and height, along with other qualitative data including where we currently have pain and our sleeping preferences.

After entering in our personal data, we both laid down on the bed (hooked up to data sensors). This data was then sent to the Sleep to Live’s data pool, and a report was printed for us. The report displayed statistics about us and recommended mattresses throughout the store.

Read More

Topics: Big Data, Analytic Data Model, Data-Driven

7 Ways to Make the Most of Credit Union Member Data

Posted by Steven D. Simpson and Paul Ablack on May 16, 2017 11:01:00 AM

Leaders and business intelligence at credit unions are putting a tremendous focus on ways to use advanced data analytics to identify trends, detect patterns and glean other valuable findings from the sea of information available to them. Without question, member data is valuable. But the greatest value lies in the ability to empower each line of business to achieve strategic initiatives and performance goals. When this empowerment is coupled with improving member service, a proven, repeatable best practice results.

Read More

Topics: Membership, Data Analytics, Leadership, Data-Driven

Looking to the Future of Data Warehousing

Posted by Mark Portz on Jan 30, 2017 11:01:00 AM

In the fourth Data Analytics Series BIGcast, From Questions to Answers: Becoming a Data-Driven Organization, John Best speaks with Brewster Knowlton of The Knowlton Group about data-driven decisions, data warehousing and successful data integrations.

The Six Characteristics of a Data-Driven Organization

According to Brewster, there are six characteristics to determine whether your organization is really data-driven:

Read More

Topics: Analytic Data Model, Data-Driven, Podcast

8 Steps to Make Data Analytics Work for You

Posted by Peter Keers, PMP on Jan 17, 2017 11:01:00 AM

Credit unions interested in advancing their data analytics efforts will find a wealth of information in a recent article in the McKinsey Quarterly. Simply entitled, “Making Data Analytics Work for You – Instead of the Other Way Around” (Mayhew, Salah, and Williams), the article provides an easy to follow list of steps for any organization to get the most out of their investment in data analytics.

The authors emphasize that improving corporate performance is the only meaningful reason for organizations to pursue data analytics. As a result, they state two important principles:

Read More

Topics: Data Analytics, Data, Data-Driven

The Comfort of Data-Driven Decisions

Posted by Nate Wentzlaff on Dec 13, 2016 11:02:00 AM

 

As the next generation begins making financial decisions, credit unions will be able to comfort them with data-driven product recommendations.

Recently, my wife and I were shopping for a mattress. We began the process by “trying out” mattresses by how they felt. My wife thought she preferred firm mattresses, while I thought I preferred soft ones. As we tried mattress after mattress, my wife would ask me, “what do you think about this one”, in which I would usually reply, “It feels pretty good to me”. We became frustrated by a complicated search for a large budget item until we found a mattress store that comforted us with data. The mattress store (Becker Furniture World) is locally owned with only 8 locations (does this sound familiar to your credit union?). They approached mattress shopping from a data-driven way. By using an analytic data model (developed by Sleep to Live Institute), they are using analytics to aid customers in their mattress investments through data sensors and user input. The data comforted us enough that we decided to purchase one of the mattresses it recommended.

Read More

Topics: Data Analytics, Data-Driven

The Purpose of Analytics

Posted by Nate Wentzlaff on Nov 1, 2016 12:04:37 PM

As credit unions continue to invest in analytics solutions, they should focus on the purpose of analytics; Making data-driven decisions to better serve members.

Big data and analytics are a couple of the most used buzzwords throughout the credit union movement.  You can’t avoid these terms no matter where you try to hide. Many vendors promise analytics that will be a panacea to the movement. They continue to make bold claims that are sure to perk an executive’s ears (and drive sales for the vendor). Although there are many powerful products available to credit unions, they must understand the purpose of analytics before they begin their journey.

Read More

Topics: Data Analytics, Machine Learning, Data-Driven