One of the most common challenges I see as a consultant is what I call the “adoption gap”. This is the cycle when a company invests in a new data visualization tool to move away from Excel and a few months later, usage drops. Another tool is introduced , and eventually, the team reverts back to Excel anyway.
This cycle is not only expensive, it’s also exhausting for the people expected to constantly adjust to new tools. And more often than not, the tool itself isn’t the problem. The problem is the adoption strategy!
In a recent webinar, I explored why this happens and how we can bridge the gap between building dashboards and actually getting them used. Here are a few key ideas that have helped me move my clients’ dashboards from “nice to have” to something stakeholders use daily.
KNOW YOUR AUDIENCE
Why We Resist
It’s easy to assume that once a dashboard is built, adoption will follow naturally. In reality, this is rarely the case.
One framework I’ve found particularly useful is the Diffusion of Innovation Theory. While it was introduced in the 1960s, it still explains very well how people adopt (or don’t adopt) new tools in business settings.
Two aspects of this theory are particularly relevant to dashboards:
1. Relative Advantage
People tend to adopt something that improves how they already work. Or in other words, people are looking for an advantage, relative to how they worked before. But the reality is that people are often still faster in Excel. If a dashboard doesn’t make their job easier or faster, the incentive to adopt the dashboard is simply not there.
2. Complexity
Even a powerful dashboard will be ignored if it’s difficult to navigate. If users need extensive training just to answer basic questions, they are much more likely to fall back on familiar tools aka Excel.
The takeaway: Dashboards need to offer a clear advantage over other tools and be intuitive to use.
Moving Through Transition Processes
Another important insight from the above mentioned theory is that not all users approach new tools in the same way.
Users can be be classified into different groups:
Innovators and early adopters: These users are curious, happy to explore something new, and willing to navigate initial bugs. They may also sign up for beta versions.
Late adopters: These people prefer stability and wait until a tool has proven itself. They usually let other people try the new tools first, and then adopt later on.
Laggards: These people only adopt when they absolutely have to or it becomes unavoidable.
This distinction is important to keep in mind. As dashboard designers, we are often on the earlier end of that spectrum. But our end user can be all along this spectrum, in the worst case they can be on the opposite end and resistant to adopting a new technology. This gap can feel frustrating and is most often where adoption challenges come from. So how can we bridge this gap?
Change Doesn’t Happen Overnight
Adoption is a process. Most people move through stages of emotions when confronted with something new and each person progresses through these stages at various paces. We'd want to focus on helping people move across these stages rather than miraculously expecting them to already be ready and committed to the new technology.
1. Denial: Initially, there may be denial or skepticism, especially if the relative advantage is not evident. Maybe the dashboard will disappear like other initiatives?
2. Frustrations: If the dashboard sticks around, the denial often turns into frustration as existing workflows get disrupted. This frustration is especially high if the dashboard is not intuitive to use
3. Experimentation: Over time and with targeted support, users slowly begin to experiment with the new tool and discover the value for themselves.
4. Commitment: Eventually, if the experience is positive, the users become committed and get used to new workflows.
Thus, the role of the dashboard designer is not simply to build the tool, but to guide users though this process. Even small things, like short walk-through videos or an ‘Export’-button, can help make this transition smoother.
2. DESIGNING FOR ADOPTION
What versus Why Requirements
Now that you understand your stakeholder, it's time to design for them. One of the biggest shifts I’ve seen in successful projects comes from moving beyond "What requirements". Most dashboards are built based on a very concrete list of requirements, like KPIs, filters, and breakdowns. These describe WHAT stakeholders want to see, but not WHY they need it.
For example, if someone asks to see profit by region, that’s useful. But if the underlying goal is to identify underperforming regions to reallocate resources, then your dashboard should highlight regions with negative profit or less profit compared to other regions. When you design for the WHY, the dashboard becomes more than a summary. It becomes a tool for decision-making and that’s when your users will start to see real value.
Intuitive Design
Good design plays a major role in closing the adoption gap. A useful analogy is how we use smartphones. We don’t read smartphone manuals, but instead we rely on the design of the interface to guide us. Dashboards should work the same way. This often means simplifying rather than adding.
Remove visual clutter (also called “Chart Junk”) such as gridlines or redundant labels.
Intentional and consistent color use. Don’t color every single bar or line in a different color. Instead only color the key insights that you want your user’s eye to be drawn to, e.g., the negative profit.
Leverage familiar visual cues, but be aware of existing associations, e.g., green representing good and red representing bad (at least in Western cultures).
Use clear instructions in the subtitle or close to the chart, when interactions aren’t obvious.
In my experience I found that the more executive the audience, the simpler the dashboard needs to be. Executives don’t have time to explore. They need to understand the key message almost immediately – ideally within 5 seconds.
Data Storytelling
Effective dashboards don’t simply display or summarize data: They tell a story.
This isn’t about manipulating data, but about making it easier to focus on what really matters to the user. Layout, size, and color can all help direct the eye and save time. From there you also want to direct the flow of information across the dashboard.
Here is an example: Let’s say I have a line chart that shows a spike in Google searches for the key word “Roman numbers” in February 2026. I would then ask myself why this could occur. My next chart then shows the keywords that are usually paired with this search and it turns out that most people look for “Roman numbers superbowl”.
So if you observe a pattern or insight, repeatedly ask yourself “why?” and use the subsequent charts to dive deeper into the analysis. This will transform your dashboard from static reports to investigative tools and from a data summary to a data story.
FINAL THOUGHTS
The adoption gap is rarely closed with better dashboards, but a combination of understanding the needs of your users (What vs Why requirements and adoption tendencies), supporting them through the change process, and building intuitive dashboards with a clear relative advantage over existing tools.
If you want to see more hands-on examples of data storytelling and good versus bad dashboard examples, you can find the full webinar recording here:
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