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.