Let’s face it: we live in a world where a strong data and analytics competency is becoming a “must have” for successful companies. Despite the growing significance of analytics, the majority of banks and credit unions are not “data-driven” organizations.

We’ve uncovered a number of common reasons why investment in data and analytics has been pushed off or outright rejected. Despite these challenges, most of the common reasons against data and analytics are driven by inaccuracies or misinformation.

In this post, we will address the common pushbacks against data and analytics projects and how to overcome those challenges.

Becoming Data-Driven Costs Too Much Money

I’ve heard too many times that it costs “millions and millions of dollars to build a data warehouse”. This is true…if you are a larger company building a data warehouse from scratch. For most banks and credit unions, this statement is a gross exaggeration.

There are several organizations out there, like OnApproach, who have pre-built data warehouse platforms. These “pre-built data warehouses” save you a large amount of time, effort, and money. While some customization might be required to meet the specific needs of your organization, most banks and credit unions should opt for a “pre-built” solution. These “pre-built data warehouses” typically cost much less money than building a warehouse yourself.

Data warehouses costing “millions and millions of dollars” simply isn’t the case for most banks and credit unions.

Data Warehouses Are WAY Too Big of A Project…

This is also true…if you try to do everything at once. Data and analytics development should be an iterative process. If you tried to integrate all of your data sources into a data warehouse at once, it would undoubtedly be an overwhelming project. In all likelihood, building a data warehouse this way would fail. If, however, you take an iterative approach to developing your data and analytics platform, these projects are much more manageable.

Would you acquire four organizations at the same time? Of course not. Don’t bite off more than you can chew, build out your data warehouses iteratively, and these projects won’t be too overwhelming to handle.

There’s Not Enough Time to Focus on Analytics

The average $1 billion credit union we work with has somewhere between 45 and 65 third-party applications or data sources. Because of how disparate the data has become, we tend to uncover thousands and thousands of man-hours that could be automated with a better data and analytics platform. What could you do if we gave some of your staff half of their time back?

The logic that “we don’t have enough time to focus on analytics” fails when you consider how much time you could get back by investing in analytics!

The way we’ve always done it works…”

Continuing to “do things the way they’ve always been done” is a recipe for failure. With how much has changed from even ten years ago, failing to change nearly ensures your organization’s demise. Using gut instinct to make business decisions might have worked twenty years ago but not today. The rise of non-traditional competitors – like peer-to-peer lenders and 100% digital banks – was made possible by analytics. To continue to compete against these new challengers use their playbook against them and leverage the power of analytics.

Failing to incorporate analytics into your organizations’ decision making (i.e. “doing things the way you’ve always done them”) will prove to be a poor decision.

We don’t have the right culture

Most organizations that are not data-driven do not have data-driven culture. This is expected, right? Yet, how could your staff develop data-driven mentalities without having the necessary support for data and analytics to drive that cultural shift?

As part of any data and analytics initiative, you should consider how you are going to develop and foster a data-driven culture. In previous posts, we’ve provided some helpful tips on preparing your employees to become data-driven” that you should consider.

Once you begin developing your data and analytics program, you will be able to – with the right action – create and foster a data-driven culture.

Comment and let us know some of the pushback you’ve experienced when trying to leverage data and analytics!

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