Six Things Standing in The Way of Data-Driven Decisions
Posted by Ben Shuey on January 10, 2023
It’s a near-universal desire of credit unions to make well-informed decisions that create loyalty-building member service and optimize performance.
So then, why isn’t every credit union – or company, for that matter – data-driven? Often, the same challenges get in the way: a credit union with all the right tools, but without the right people and processes, will still find it difficult to achieve its goals.
Patrick McElhenie, chief sales officer at Trellance – a GoWest Solutions partner – identified six of the most common data challenges he sees.
Data is not an organizational priority
Without credit union leadership and key decision-makers in every department acting as champions, it will be difficult to convince the rest of the organization of data’s importance – and even more difficult to inspire them to adopt new data-oriented processes that may be needed to succeed.
There isn’t a data culture
Most credit unions are accustomed to gathering opinions or deferring to senior leadership when it comes to making key decisions, and it’s not hard to see why. A data-driven culture doesn’t happen by itself and it takes work to get there. To look to data for answers, it must be readily accessible, accurate, and actionable. Cultural shifts that make data central to operations and help everyone understand their roles as data stewards have to rise in importance.
There is no clear data strategy in place
If you simply start by capturing all the data you can, you’ll soon be drowning. Begin instead with a plan. The plan can be organization-wide or focused on a single project. A project-based approach can be built upon incrementally until eventually, the entire credit union is in harmony about how data will be used.
There are data silos
Without standardization and consistency, sharing information across the organization becomes difficult and data integrity suffers – making drawing accurate conclusions harder. Ultimately, data silos undermine the spirit of data-driven decisions, which is to align internal teams and make determining the best course of action simpler and clearer.
Bad data is getting in the way
The cost of bad data is very real. Not only is there a bottom-line effect on revenue, but the compounding effects lead to poorer-quality data analytics, which lead to poorer-quality decisions, which ultimately come back to hurt the bottom line. It’s a circle that won’t end until the root causes of bad data are addressed. It’s not enough to fix mistakes every time you see them – find out why they are happening in the first place.
A lack of training
It’s common to see credit unions invest heavily in technology and tools that they don’t have the knowledge to use effectively. Whether data specialists are brought in-house or help is sought from outside experts, it is important to have support from technicians skilled in data management, statistical models, data analysis, visualization, and data security.
By being aware of these six major pitfalls, it’s possible to quickly recognize, rectify and even prevent what stands between your credit union and a data-driven roadmap to success.