Power BI Grows Fast. But Has Your Governance Kept Up?

There’s no denying it, Microsoft has really done well with Power BI. A product that only launched a decade ago now sits at the very centre of the business intelligence and analytics world. How do I come to this conclusion? Well, it has topped Gartner’s Magic Quadrant for Analytics & BI Platforms for 17 consecutive years (source: Power BI) and has an estimated 97 percent of Fortune 500 companies using it in some way (source: Power BI). Apart from that, being in this industry for over a decade and an active member of the Power BI and wider data community, its clear to see Power BI takes up quite a lot of the lime light.

So, its clear that organisations and individuals have chosen to adopt or at least explore using Power BI.

Why Everyone Feels At Home So Quickly

After training hundreds of new users over the years, I’ve seen the same light-bulb moment over and over: “Oh, this feels like Excel and PowerPoint!". That familiar Microsoft ribbon, the on-screen interaction and so much more lowers the intimidation barrier and wins hearts fast. I find it promotes confidence to experiment further and experimentation quickly moves to adoption. I really stand by this, so many elements of Power BI Desktop look and feel like products we all know as part of MS Office. The point I am making, organisations see the benefits, the familiarities and are quick to start using it. Plus, there are so many more ways on how Power BI is high on the ease of use factor.

The Two Governance Stories I Keep Running Into

When helping organisations with Power BI data governance for Power BI, I usually find organisations in one of two places:

1. Organic Adoption: Power BI perhaps as a pilot in Finance or Operations, and suddenly every department has a suite of reports floating around. Success, yes, but also an emerging tangle of duplicate semantic models (datasets), mystery refresh schedules, hundreds of workspaces and permissions nobody remembers setting. It's a quick way to bring the typical wild west scenario many BI vendors love to highlight.
2. Cautious Adoption: Leadership narrowed a shortlist of BI tools, chose Power BI and now wants to get the architecture, security and processes right from day one. They are eager to avoid the mess they’ve heard about elsewhere or have already experienced with their current/previous reporting tool.

Now, you’re probably thinking option 2 sounds like the far better place to be. Well, I see why you’d say that, however, there are pros and cons for both.

Organic Adoption: High Enthusiasm, Low Guard-Rails

The upside of an organic adoption is... well, the organic enthusiasm. People already want to use Power BI. That’s priceless in a world where many times the hardest part is often persuading teams to transition away from a tool they are used to for three, four, even five years. With Power BI, the business is pulling, not being pushed, and that momentum is a terrific foundation. It also means people can get to use Power BI, get comfortable with the tool early-on and even generate some quick wins.

But the same freedom that sparks adoption also creates the typical chaos. Because Power BI entered the organisation without any guard rails, users have been building reports, semantic models (datasets) and other artefacts any way they like. Duplicate semantic models, mystery refresh schedules, ad-hoc permissions, basically all those “wild-west” headaches we’ll explore further below are now baked into daily operations. Enthusiasm is high, governance is none.

Cautious Adoption: Structured Roll-Out, Risk of Paralysis

A cautious adoption path averts many of those wild-west challenges which again, we will highlight below, but think processes, data security, architecture. By slowing down, designing architecture and defining security up front, you avoid a painful “retrofit” later. There’s far less unpicking of bad habits, centralising different elements and then pushing everything back out with best practice guard rails. It also means we can try and offer the right level of support to the internal Power BI user community from the start. They pick up the best practices from the beginning which is a huge benefit, as its harder to change bad practices if they are already use to them.

The catch? Progress can take forever. I often see teams planning every scenario to the nth degree, locking everything down and deferring go-live again and again. That over caution frustrates would-be creators and users, who then create their own workspaces or stash data in siloed spreadsheets. In trying to prevent chaos, you risk driving it underground. I have seen this many times. So, it should not come as a surprise, but balance is crucial. Move fast enough to keep the business engaged, yet deliberate enough to embed solid governance from day one. A rollout and data governance plan is needed, but so is balance.

So, What Are Some Of The Common Challenges?

Above I mentioned some of the common challenges that come when not having the right level of governance and guardrails in place. Below is a more detailed list:  

• Endless semantic models (datasets), reports, dashboards, workspaces
• Thousands of ungoverned reports all with repeating and conflicting data
• No processes on how to get license, access to workspace, request report, add workspace to capacity, etc.
• Reports are just used to export data to excel
• Reports are not providing genuine insights for supporting decision-making process
• Data visualisation principles are not being followed
• End-users don't have a go-to place to ask questions and find answers
• End-users not been provided the support needed to learn the tool, best practices and data culture
• The core reporting team loses control and is overwhelmed
• Data strategy does not align to governance strategy and governance plan
• No single version of the truth, with conflicting numbers between solutions
• Confusion on who is the owner of the tool, the solutions, the artefacts
• No clear governance framework for workspaces, apps, app audiences, permissions, sharing
• Everyone is sharing/publishing with everyone, with no guardrails in place
• No behaviours and best practices have been set or promoted internally
• Not everyone is on-board, some using Power BI, others self-adopt other tools
• No oversight on who is doing what, no auditing, no cost management

Power BI Governance & Rollout Considerations

Until now, we discussed how Power BI’s ease of use and familiar interface contributes to higher adoption. This is great! However, without the right level of governance, those “wild-west” challenges we listed above will become a reality. Fast growth is great, until security issues arise, we find conflicting numbers, people start losing trust, publishing processes can’t keep up, sharign with external users is enabled freely.

So, below are some key elements that should be considered to help reduce the above chaos. This is not a full list of all the considerations, however, these elements have a big impact on the above challenges and many extend to Microsoft Fabric, which introduces its own governance requirements.

Before we dive in, be sure to watch our Power BI Governance video at the end of this blog, where I’ll guide you through our proven, end-to-end Governance approach.

Also, highly recommend you explore Microsoft’s Fabric Adoption Roadmap (formerly the Power BI Adoption Roadmap), it’s been rebranded but still provides all the Power BI guidance you need. I have read this time and time again over the last couples of years, and would recommend anyone implementing or rolling out Power BI to do the same.

1. Secure Executive Sponsorship

Over the years, I have seen how difficult it is to roll out Power BI, or any analytics tool, without an executive sponsor. When a senior leader, someone with authority, actively backs Power BI by approving budgets, cutting through red tape and reinforcing the message in company updates or company newsletters, it instantly elevates the rollout and usage from an IT objective to a business objective. It ensures everyone know this is not simply the IT or BI team promoting something, but instead its a business initiative everyone needs to get behind.

2. Phased Self-Service Roll-Out

I have seen a few complain about self-service and say self-service is dead or it never worked. Not true! I have worked in various organisations where self-service Power BI worked great. With that, I have also seen why many people might say self-service is dead.

What was the difference between the organisations that made it work vs those that fail? Giving full access to users without the right level of support and guidance. The point is, we must trust our users with data, we must democratise our data, but it should be done in an environment where we set the relevant guardrails and do it right. If a large group of users did not know how to create reports previously, unlocking large volumes of data and making it accessible to them does not change the fact that they still cant create reports.

So, rather than opening the self-service floodgates to every department at once, start with a incremental approach, start with a single business area. Use that first business area or department to learn, see what went well, what didn't go well. For example, did the PBI framework (workspaces, apps, audiences, security) we go for work as expected? Once you’ve ironed out issues and implemented solutions, expand to the next area or department. For more details, check out our other blog: Power BI Governance: Balancing Control and Self-Service for Adoption

3. Establish a Power BI Centre of Excellence (CoE) for the Business

The Power BI Centre of Excellence (CoE) helps organisations progress their Power BI adoption journey. I find that PBI CoEs vary in their definition, approach and structure, and to me this is fine.

What’s key is that they help organisations further their adoption by promoting and establishing an internal community, putting in place the relevant guardrails, promoting best practices, empowering users and being more business-focused. This is not a deep dive, but I must repeat the importance of empowering end users and being business-focused. One thing I would always call out when establishing a Power BI CoE, do not make this a place for data professionals to simply set rules. Yes, it should be driven by the core reporting team, but focused on the business. Starting off with members from a single team is usually a safe approach, but the true value comes when extending this to various business users.

Again, see the MS Fabric Adoption roadmap to explore the various approaches that exist, and please do not let this just be a forum for data professionals and IT people.

4. Build a Power BI Community Portal

A community portal is essential for empowering users with ongoing support, knowledge sharing and engagement. It gives everyone reliable answers and a connection to the broader Power BI community, encouraging best-practice usage. By offering FAQs, starter templates, guidelines, to-do guides and details on internal events, the portal helps users navigate Power BI more effectively while easing the load on your core reporting team. Also, it makes people feel part of a community, it creates buzz, it shows this space is active. I can write so much on this subject, so will be releasing some videos/blogs on this.

A community portal must have a dedicated owner or it will fail. Engagement is key, especially early on. First impressions matter, if someone asks a question and receives no reply, they won’t return. And if others see unanswered questions, they’ll be discouraged from asking at all. The portal should be managed by its owner and initially by the core reporting team. However, over time, other business users will step in to respond and spark new discussions. As your Power BI champions and CoE grow, give them access to update and promote the portal and make it a standing agenda item for COE meetings. This ensures the portal remains a vibrant, reliable resource.

5. A Single Version of the Truth

Nothing erodes trust faster than conflicting numbers. Also, a lot of the challenges I highlighted above are directly impacted by not having a high integrity set of models that are well maintained and managed. Depending on your organisation, these should be made available for use by the organisation when moving to self-service. We should have some form of "gold" layer where we host models built on governed data sources and that are maintained by the right selected people or team. Here we take advantage of features like endorsements, discoverability and sensitivity labels.

When reports reference these certified semantic layers, users gain confidence that every dashboard reflects the same underlying reality and that confidence fuels further adoption. This is especially important when operating in a self-service space.

6. Document Processes & Best Practices

Even the best guardrails fail if nobody knows they exist. Create a living playbook, online or as a PDF (you can see how this goes back to you Community Portal), that walks users step-by-step through common tasks: requesting a licence, creating a workspace, hosting a workspace on a capacity SKU, tagging a dataset as certified and more.

Think regulatory compliance and what we should be promoting and trying to set as standard behaviour. Think sensitive data, data access, data integrity. Keep each procedure straightforward, with screenshots or flowcharts where helpful. Regularly review and update this playbook in partnership with your CoE so it stays aligned with platform enhancements and evolving business need. I also call out neccessery training around this further below.

7. Invest Training - Empower End Users

Governance isn’t just about policies, it’s about PEOPLE. Offer targeted training for report authors, semantic model designers, report consumers and of course your MS Fabric admins. A developer workshop might dive into best-practice for data modelling and deployment pipelines, while a report consumer session focuses on navigating reports, using dashboards effectively and drill downs. If you want a deep dive into the types of training, check out our other blog What Is Power BI Training?

In addition to the above, its important we promote and drive a culture where everyone is aware of the governance policies and data quality to some extent. So, not only train users on the tool, but have we provided some level of training on this specific area? It does not have to be complicated. Users should be encouraged to support by maintaining accuracy and integrity in their own work. This shared responsibility ensures that data governance framework is integrated across the organisation.

Also, governance should not be a one way street. To make governance stick, we must listen to our users, gather their feedback, understand their pain points and tweak our policies to fit. Involving them in the conversation not only sharpens our governance framework but also makes them feel heard and invested. This collaborative approach builds ownership and keeps governance practical - it also tied back to a lot of other aspects described above such as the CoE, Portal, etc.

Need Help with Power BI Governance?

Watch our video to see how our proven approach builds a secure BI environment, establishes guardrails that empower end-users and offers strong data controls to ensure data is accurate and consistent. Ready to level up your analytics? Book a free consultation call here.

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