Tools without training are just utensils
My partner Eva loves cookware. Over the years, she has accumulated a serious kitchen. Pots and pans in every size. A whole range of knives including an intriguing collection of paring knives. A food processor, a stand mixer, a hand blender, an ice cream maker, and an air fryer. According to her, she used to have even more specialized tools before she moved to the UK.
She is also a genuinely excellent cook. But what matters is: She was an excellent cook before she owned any of that equipment. She’s been developing and fine tuning her cooking skills for over 20 years. The equipment did not make her a cook, it helped her create dishes that otherwise wouldn’t happen.
I think about that a lot when I talk to analytics leaders about Tableau.
The investment most leaders make
Most organizations that have invested seriously in Tableau have done something similar. They've acquired powerful tools. Licences for hundreds or thousands of analysts. Sometimes a full enterprise deployment with governance frameworks and data connectors and a comprehensive professional services commitment as well. And then they've stepped back, satisfied that the hard part is done, and waited for the insights to follow.
They rarely do. At least not at the level they should.
The tools are only half the equation. The other half is what your people can do with them.
There is a version of Tableau adoption that happens in almost every organization I have worked with. It looks roughly like this. A team gets trained at implementation. They learn enough to get started. They build the dashboards they need to build. The work gets done, stakeholders get their reports, and everyone moves on.
But getting started and getting good are not the same thing. What often follows is a kind of functional plateau. Analysts know how to use Tableau well enough to be productive. They are not struggling. They are building things that work. But they are making sandwiches.
That is not an insult. A good sandwich can be delicious and satisfying. But if your kitchen is stocked for a full restaurant service and you are only ever making sandwiches, something has gone wrong.
The invisible cost of under-investing
The invisible cost of under-investing in Tableau training is not so much that people fail to get value from it. It is that organizations only ever get a very limited amount of value from their investment. It is the work that never got made because no one on the team knew it was possible. The question the stakeholder never thought to ask because the dashboard they were shown did not prompt it. The decision that took three days instead of three hours because no one knew the right calculation to build. These costs are real but they don’t appear on any invoice, so they are easy to ignore.
The easiest things to ignore are often the most expensive.
What is true for Tableau as well as other analytics tools and platforms is that they don’t stand still.
Tableau ships major updates on a regular cycle. The platform your analysts were trained on two years ago is not the platform they are using today. Features that did not exist are now central to how advanced Tableau users work. Capabilities that were workarounds have become native functions. Entire areas of the product have been substantially rebuilt in recent years.
This creates a problem that goes beyond the initial training gap. Even an analyst who received genuinely good Tableau training at some point in the past can reach a plateau because the platform has moved past what they know. Their mental model of how Tableau works is accurate, but it is increasingly incomplete. And an incomplete model is limiting and gets in the way of doing more advanced work.
Analysts need to stay on top of Tableau’s changes and use them to their advantage
Think about cooking again. A chef trained in classical French technique can produce brilliant food. But if they have not cooked with induction heat before, they will burn things. They know their techniques but the environmental parameters have changed. The chef needs to adjust and that takes time and practice.
Your analysts are dealing with a version of adjustment every release cycle. Does your organization give them the space and structure to do it, or is there a quiet expectation that they’ll just figure it out in the flow of their daily work?
Learning to cook, actually learning to cook, does not happen in a single event.
You do not attend a weekend workshop and come back as an excellent cook. You learn one technique, and then you repeat it until it becomes automatic. You apply it to different ingredients in different contexts. You cook under pressure and realize your knife skills are not quite where you thought they were. You cook alongside someone who is better than you and pick up three things you were not expecting to pick up. You get feedback on a dish and understand, for the first time, the difference between technically correct and genuinely good.
Achieving mastery
That is how mastery works in any discipline. It is structured, incremental, contextual, and reinforced continuously over time.
Tableau mastery works the same way. Analysts who develop real depth of skill do not get there from a single onboarding session or an occasional workshop. They get there through repeated exposure to hard problems, structured guidance on technique, feedback on their actual work, and a community of peers pushing them to think differently. They build the kind of fluency where they are no longer looking for a workaround. They are asking a better question.
That depth is what separates an analyst who produces reports from an analyst who drives decisions. The difference is not intelligence or effort. It is the quality of ongoing development behind them.
Developing an Analyst Culture
This is what I mean when I talk about Analyst Culture. I have written about it before, and it sits at the center of how I think about organizational analytics capability. It goes beyond being a training program and is more about the environment in which your analysts develop, share, and grow over time.
Recognition closes the loop. When analysts are given space to contribute and are recognized, they grow faster, stay longer, and bring others with them. Culture becomes real when it shows up in how people are measured and rewarded.
When all three are present, the ROI argument becomes easy because everyone can see the difference it is making.
The organizations I have worked with that have the strongest analytics culture share one thing in common. They built training into how their team operates and invested in ongoing development as a real commitment.
That’s why we’re here
That is exactly what NLT for Teams is built to support.
It is a structured, ongoing development program for analytics teams of 15 to 10,000. Because Tableau keeps evolving, we produce over 120 hours of new content every year from live classes. Analysts have access to structured learning pathways, more than 1,000 templates and resources. Bespoke workshops and a dedicated customer success manager ensure analysts are onboarded quickly and know exactly how to make the most of the program so they can build their own capability over time.
Skill progression is visible within 90 days. Current customers which include Fortune 500 companies renew at over 75% because they see the compounding effect of the skill development in their people.
If you are an analytics leader who has made a real investment in Tableau and you are not seeing the return you expected, the licence is not the problem. The training is.
Book a call and let us talk through what ongoing development looks like for your team.
