Paying yourself first is a common recommendation made when considering your personal finances. Many experts recommend a 30/70 split of your income, with 30% of your income being saved for long term financial goals, and 70% being used for current needs, life style, and living expenses. This approach invests in your future needs, establishes capital which could be used during times of hardship, invested to generate passive cash flow, or even financially leveraged to increase buying power. In short, a small effort today to ensure you are positioned to not only protect yourself in the future, but also allowing you to capitalize on future opportunities as they arise. Wise words, but this is not a post on personal finance. Continue reading
Do you NEED data insights today? What about tomorrow, will your credit union cease to operate tomorrow without data insights? Next week? What about next month? It can be easy to talk yourself out of change when you are meeting the status quo today, your board is satisfied today, and your examiner is happy (enough); it’s easy to justify that it’s not broken, so why fix it. Continue reading
Recently I completed an analysis for a credit union where we mined credit report trade-line details for outside loan capture opportunities. We reviewed 90 days of full credit report pulls, analyzing the trade-line details for insights into members’ financial needs being fulfilled by other financial institutions and for opportunities to take ACTION. The bulk of our data mining came directly out of CU*BASE tool #976 – Where you Member’s Borrow. We did make the decision to bring in other ancillary data sources for additional insights, but the detail available directly out of the dashboard saved hours of custom query writing and data aggregation. Continue reading
Do it yourself, or do it together? Seems to be a popular question in my life these days. Whether it’s maintenance around the house, obedience training for our new puppy, or even mowing the yard; the decision to buy or build is often at the center of it all. This decision typically boils down to time and resource availability making these decisions difficult to act on without knowing your available resources. Continue reading
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. Continue reading
Asterisk Intelligence has built a business around generating actionable insight from data. As simple as that may (or may not) sound, I often find myself explaining the difference between these two elements, data and insight. This distinction may seem trivial, but in actuality it is a very important aspect of our business and needs to be understood in order to fully grasp the mission of our team and the products we create.
As a “Data Geek” the concept of New Year Resolutions always gets my thoughts going. I find myself wondering how large the enrollment spike was at my local gym, and even more interestingly how long those January memberships stay active. Or perhaps the tobacco industry, I wonder if, and how badly, they feel the impact of New Year Resolutions in their income statements. As for online retailers such as Amazon, it would be fascinating to analyze their product returns since the holidays; I can’t imagine the logistical nightmare that must be! Continue reading
The task of transforming the culture of your credit union into that of a data centric organization can often leave one’s head spinning. How do I start? How do I measure success? How am I going to afford that? Generally speaking, I believe these barriers can be summarized by “over complication”. It is this mentality that prevents most projects from leaving the ground. Continue reading