The Decision Maker

Lagging Contenders: How Credit Unions Can Catch Up in Data and Analytics - Part 2

Posted by Peter Keers, PMP on Aug 15, 2017 10:16:00 AM

This is Part 2 of 2 in a blog series on how credit unions can catch up in data and analytics. In Part 1, we discussed which questions credit unions need to be asking to get off the bench, the issue with data silos, and what it will take to move forward with data analytics. In Part 2, we will further discuss the concept of big data, staffing for data analytics, and creating value from the data.

"A recent McKinsey & Company report emphasizes the fact that many industries are achieving only a fraction of their “digital potential”. However, the report observes, “In the United States, the information and communications technology sector, media, financial services, and professional services are surging ahead…”. This means other players in the marketplace served by credit unions have a big head start.

Credit unions that have been sitting on the sidelines can wait no longer. To get off the bench, these organizations need to ask:

  • What are the basic questions about the organization’s strategic direction that cannot be answered today?
  • How can existing data be better “generated, collected, and organized”?
  • What data outside the organization would be useful?
  • What skillsets are missing internally and to what degree can they (or should they) be outsourced?
  • Once “insights” are uncovered from analytics, what are the practical steps to leveraging them to create value?"
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Topics: Financial Services, Big Data & Analytics, Structured vs. Unstructured Data, Value, Digital

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:

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Topics: Data Analytics, Structured vs. Unstructured Data, Data-Driven

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

Posted by Austin Wentzlaff on Aug 4, 2016 11:06:00 AM

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.

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Topics: Big Data, Little Data, Structured vs. Unstructured Data

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You now have more information at hand about your credit union than ever before. But are you using it to "out-think" your rivals? If not, you may be missing out on a potent competitive tool.

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