Data-Driven Organizations Avoid These 7 Common Pitfalls

By: Paul Fuller | August 9, 2022

All organizations want to become data-driven, but there are many pitfalls awaiting those who plunge headlong into buying new tools and implementing new policies. In our many years of experience helping organizations transform and modernize their data, we have seen many ways to do things wrong. So, before you start your data transformation initiative, make sure you watch for these common data transformation pitfalls.

1. Disengaged Business Owners

This is the worst one; you don’t want to see this. We help put in data platforms, and we were once brought into a project to help resolve some support issues. We quickly learned that the organization had put in the data platform a year and a half beforehand and – by the time they brought us in – nobody had touched it yet.

How does that happen? How do you not take advantage of the investment? It happens when the business views this as an IT thing. When the business is disengaged in the project, then you’re going to end up with disengaged business owners and an unused data platform. You’re not going to be a data-driven culture.

2. Unempowered Product Owners

Another pitfall we see is unempowered product owners. Successful data projects require agile product owners who have the authority to make decisions and aren’t crippled by having to get approval from many people and keep everyone happy. The product owner must know who they need to talk to and are empowered to effectively make the important decisions.

3. Underfunded IT Budgets

For best results, your IT budget should be 2% to 3% of your overall budget. We’ve seen some organizations that are under 1%. With so little IT investment, you’re not going be able to become a data-driven organization. This is going to be an investment. It’s important to stay focused on the goal of driving towards set business outcomes and giving yourselves a competitive advantage to be able to innovate. But, if you’re not going to put money behind it, then it’s not going to happen.

4. Report-Based Thinking

Even when you’ve cast the data-driven vision and you’re evangelizing it, you may still have people who are stuck in report-based thinking. They’re the ones who only want more reports and more numbers. You need to help them get to the point where they’re asking, “What decisions do we need to make with that data?” When you steer them towards those kinds of questions – and away from just spitting out another report – then your pathway to data transformation will be much smoother.

5. The Wild, Wild West

We’ve seen people use Power BI Premium at an organization (which is a significant investment), and they thought that simply turning it on was going to solve all of their performance and accessibility problems.

One organization we went into had multiple instances of Tableau and Qlik and Power BI Premium. When they developed reports, their instances would slow to a crawl because they didn’t have a data governance plan. Without setting one up, your organization will quickly resemble the Wild West. Soon, you’re going to either have security issues (people accessing data they shouldn’t) or the inability to have performant tools to be able to quickly make important decisions.

Therefore, you must think about data governance (but not heavy-handed governance because your goal is to empower your users). Governance, like fences, provide freedom because you can freely explore within set boundaries.

6. IT Reality vs. Business Need

Organizations have to balance the needs of the business and IT. So, while the business may want to implement the latest data technology, who will support it? Sometimes you have to compromise and put certain needs / wants on the roadmap instead of doing them right away. Without prioritizing the most important needs, your data initiative won’t gain the traction and momentum it needs to succeed.

7. End User Communication & Adoption

This can’t be stressed enough. Casting the vision is essential to success because “where there is no vision, the people perish”. It has to be a top-bottom, bottom-up, and top-down approach. You must have champions in your organization who will support it and influence others. You also must have those at the top casting the vision for why you’re going to a cloud-based data platform and how it’s going to help. Once you have the vision cast, users will start adopting it.

“How Do I Overcome Resistance to Becoming Data-Driven?”

We get this question a lot. Start by ensuring you understand the root of the resistance. If a stakeholder is resistant, seek to understand the underlying driver(s). Are they worried about job security? Are they afraid of having to learn a new skill to support a new way of doing things? Or is their ego threatened because they see this as judgment on how they’ve been doing things?

Once you know the root of their resistance, help them understand how the change benefits them personally. For example, say they’re spending two days a week manually generating reports. If you build out a modern analytic strategy that automates the reports, then they get two days back to focus on higher value and more enjoyable activities. Also, make sure to show them the big picture so they understand how the change benefits the organization.

One of the common roots of resistance is the idea of intuition. Many professionals who have relied on their intuition to make business decisions are threatened by becoming a data-driven culture because they think it invalidates their years of experience. So, instead of devaluing their intuition, show them how data analytics provide guardrails for the organization to confirm or challenge ideas. Seeing objective data validating their intuition will not only win over those resistant to becoming data-driven, but it will also help them be more successful in getting others in the organization to support their ideas.

Now What?

Since you now know what not to do, you have a clearer path to success. At this stage early in your data transformation journey, it’s vital to define your vision. Then we recommend creating a proof of concept. We do this for clients, and it’s very helpful to show leadership the immediate value of data modernization. Contact us to learn more about how we can help you transform and modernize your data.

With 25+ years of professional IT experience starting in software development and now in data analytics, Paul thrives on applying the right technological solutions to business challenges in a way that truly serves the business and their users.

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