Refining Data with Common Bonds

In my earlier post, Refining Insight from Data, we spoke about refining raw data into actionable insight.  As analysts, it’s these insights and business recommendations which prove the value of data driven strategies and justify our expense line items.  However, there is an entire upstream workflow which dictates the reliability of the insights we generate.  Good insights require a good data refinery, which becomes easier with organized and structured metadata, and the quality of this metadata is completely dependent upon the quality of your raw data, garbage in – garbage out after all.

As analysts, we are constantly cycling through this workflow, however if we’re not careful we can find ourselves working as data processors instead of analysts.  We must always be aware of where we are spending our time.  Spending too much of our time processing and cleansing data, generating metadata, and building the absolutely perfect refinery, ultimately is taking away from our core function as data analysts…. ANALYZING DATA!

CU*BASE has an under-utilized, pre-built data refinery called Common Bonds, tool number 232.  This should be a familiar tool in your arsenal of refineries. This tool allows you to upload any list of account numbers to be refined in 1 of 4 different dimensions, their account composition, membership traits, credit history, and tiered service comparison.  To be clear, you could quickly generate a list of all members between the age of 18 and 25 using query, then process the list through Common Bonds, and within seconds have access to hundreds of refined data points on this segment.  Everything from product and service participation, open dates, tenure, credit scores, aggregate savings and lending balances, and so much more.

Custom Built vs Pre-Built?

Without a doubt, there are certain advantages to building a home, choosing the best location, floor plan, and even picking out your favorite kitchen sink and back splash.  But for any number of reasons, time constraints, cost, or lacking a creative vision; we often purchase pre-built homes for their convenience and speed to market.  At times we may need reminders that we are analysts, we are paid to generate data driven insights, not to be data processors.

As you continue to establish your role as an analyst and iron out your own niche at your credit union I encourage you to pay attention to how much time you spend as a data processor, versus performing data analysis.  Leveraging pre-built refineries such as Common Bonds is an excellent approach to balancing this relationship and maximizing the value you provide to your credit union.

4 thoughts on “Refining Data with Common Bonds

  1. Great reminder, Thomas. Curiosity is an analysts best friend and its biggest curse. Curiosity can takes analysts down unnecessary paths that lead to wasted time and conclusions that lack any sort of value or action. Over-refined and over-manipulated data also tends to lose its integrity.

    At times analysts think their job is to answer complicated questions and achieve deep insights. While in really it’s simply solving problems – only way to solve a problem is to act on it with actionable data backed recommendations. We can’t drive action if we are buried in data processing.

  2. Oh man, it makes me sad that Common Bonds is under-utilized! As an analyst it is in my top 5 for sure.

    This year at UA we are working on defining and better understanding our target audience. By taking valuable insights gained from the Common Bonds screens, for instance that a large percentage have loans for recreational vehicles (mostly ATVs, boats, motorcycles…). We then used that information to develop products and services uniquely fit to their needs. We can also reduce the amount of marketing to each member, and focus only on products that will be most interesting to them.

  3. This absolutely rings true to me. One thing we ran into as we worked to build a data culture at Honor was that once people realize the value and availability of data in our system, they suddenly want ALL OF IT. This is a good thing, and something you certainly don’t want to discourage, but I found myself unknowingly walking my team into a a situation where we spent a lot of time data processing, and being left with little capacity to perform any type of analytical work. One of the single most valuable tools that the system has for us is Common Bonds. It’s such a robust and straight forward tool that it allows anyone, as Thomas mentioned, to find countless valuable data points on a segment of members in just a matter of minutes. This enables my team to spend time focusing on analyzing the data and finding that invaluable actionable insight, rather than trying to compile all of these data points for the analysis, which is crucial as we balance a variety of other day-to-day duties.

    The need for data processing in the credit union world is absolutely there, but the need for actionable insights is there too. I can’t speak for other credit unions, but on my journey with Honor as we built up our BI team I found it to really be a chicken and egg type of situation. Once people have actionable insight, they want to see reports to keep a pulse on it. Once people see reports, they want an analysis done to deep dive the situation and figure out what can be done to impact the numbers they are seeing. There is a balance there that must be struck, and for many organizations I suspect it will be a balance amongst only one or two people (that’s how it was for us at first at least). It becomes crucial to educate your organization and sell them on why they need both sides. Data without action is useless. Action without data is dangerous. Find the balance, sell the value you can bring to your credit union, and then use the tools available to us – Dashboards, Common Bonds, Report Generators, Query, Analytics Booth – and become the expert on how to deliver each as efficiently as possible with what time and capacity you have.

  4. Zak hits on a situation I’ve been seeing- having to explain to staff what my role is. I’ve gotten a few “please send me this data, thanks”… to which I’ve had to respond that I will put their request on my To Do list, and when I am able to pull and analyze the data, I will. I think this is extremely important so we can prioritize our time and our projects to best suite the credit union’s needs. We also need to be experts at data analytics, ethical analysis, and follow up on actionable items and tracking the success of those actions. Getting everyone to recognize the value of data is one thing, the bigger task may be proving the value of truly analyzing and not just processing

Leave a Reply

Your email address will not be published. Required fields are marked *