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Have you ever wondered how much time your employees actually spend doing their primary work task?  According to the company WorkFront[i], a management software provider, employees reported only spending 40% of their time working on their primary task in 2018.  This is down from 45% reported in 2014.  Workers report that emails, administrative tasks (clocking in, clocking out and completing forms), wasteful meetings and needless interruptions account for the remainder of the time your employees spend at work.  In a credit union, there are obvious positions that must be filled with onsite, permanent employees, but many back-office, support tasks can be outsourced, especially those that require a high level of skill and experience, reducing costs and increasing productivity.  Data Sciences and Analytics are a good example where credit unions can get more for less by outsourcing these functions.

If your credit union is considering digging into its data and using data to make better decisions, you may have considered hiring a Data Scientist or Data Analyst to assist with those projects.  My experience, however, informs me that taking this step first, often fails to yield positive returns in the short-run.  First, the credit union is likely going to need to go outside the organization to find individuals talented in data science.  However, the issue is that these external candidates often do not fully understand the specific needs of a credit union.  They can build data models and create data visualizations, but they are little help in interpreting what the data means or how the credit union should act on it, without additional training from domain experts.  Secondly, they will initially be stalled because the requisite data for analysis is not currently available in a format that is easily accessible.  So, your credit union will spend a great deal of money up front, well in advance of receiving any results, as the Data Scientist or Analyst waits for access to data.  Finally, there may not actually be enough data projects in flight at your credit union to consume a full resource. So, while the credit union can reallocate that resource, it is likely you will be paying a premium price.  Fractional or shared resources, can provide the credit union with a cost-effective alternative and provide equal, if not better, results.

At the minimum, dependent on location and requirements, the credit union will likely pay $50 – 60 thousand a year, plus benefits, for an entry-level Data Analyst.  But, what you really need is a Data Scientist which can cost more than six-figures in many cases.  If Workfront’s research over several years is accurate, you will only be getting half the work you are paying for completed.  However, Fractional Data Science Services, like those offered by CUBI.Pro, can help you get what you need, faster, and for less money than a more permanent investment in a full-time employee.  Here’s why; when you use fractional services instead of hiring full-time, you don’t pay for the overhead associated with a full-time employee.  For example, you only pay for hours that fractional data scientists spend working on your project.  With a fraction Data Scientist, you don’t pay for learning that can quickly be lost when a full-time employee leaves the credit union.  Let’s say you hire a young Data Scientist who then learns more about the credit union business while you are paying them.  There is nothing to stop them from leaving your employment and working at a larger credit union willing to pay them more money, leaving you to start the process all over again.  Finally, when you use Fractional Data Science Services, you can scale your resources as need.  Therefore, you get highly qualified resources, even if you can’t justify a full-time employee.

Fractional Data Science Services provide credit unions of all sizes an opportunity to engage their data and leverage it for better decision making.  At CUBI.Pro, we have worked with credit unions from under $100 million in assets to over $1 billion in assets to achieve actionable results with their data.   If you want faster and less expensive immediate results, you may want to consider Fractional Data Science Services as an option.

[i] Workfront.com

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