Have you heard the latest saying making its way around offices worldwide? “If it can’t be measured, you won’t get budget for it.”

This new mentality means everyone is laser-focused on results. Workers who may not have given data a second thought only a year ago are now using analytics tools to measure results and make data-driven decisions.

Sales reps want to track their daily activity levels against goals; hospital administrators want to monitor readmission rates against industry standards; and truck drivers want to analyze their fuel efficiency. Nearly everyone across every industry and role now needs to review, create, and analyze dashboards and reports. Wouldn’t you think, then, that most organizations would see heavy use of analytics from its workers? But according to the 2015 State of Self-Service Analytics Report from Logi Analytics, only 22 percent of business users were actually leveraging the self-service tools available to them – highlighting a large gap between analytics expectations and reality. If you want your workers to make data-driven decisions, you can’t just provide them with an analytics tool and assume they’ll use it. Focus instead on the complete analytic experience: If workers have easy access to dashboards that have been tailored to their needs, your user adoption will skyrocket.

Consider the Spectrum of Analytics Users
Why is it that, even if they have them on hand, the majority of users won’t leverage analytics tools? It’s because many analytics tools are built with the assumption that every user has the same role, skill set, and analytics needs.

If you’ve ever bought a pair of gloves that promise “one size fits all,” you know it never really does. The same is true of analytics software: A one-size-fits-all approach pretty much guarantees your adoption rates will stay low. Yet many organizations continue to purchase an analytics tool and provide it at the same level to all users, then wonder why user adoption is low.

To avoid the same fate, start by taking a step back and thinking about the users in your organization. Consider how a nurse would use analytics versus a hospital administrator; a sales manager versus an operations manager; or a production manager versus a financial analyst. For instance, a data discovery tool is likely going to be too complicated for the CEO who just wants to review a dashboard with the highest-level KPIs. On the other hand, offering simple dashboards will not be enough for a data analyst who prefers to interact with and analyze huge sets of data to uncover new insights on his own.

Workers at different levels won’t have the same skill sets, and they’ll want to take different approaches to data and analytics. In order to succeed with self-service analytics as an organization, it’s essential to provide the right tools to the right people in the right ways. The better you understand the varying needs of your end users, the better you can serve their needs with tailored self-service capabilities—leading to higher adoption rates and more-informed decisions.

How Scalable Solutions Help Analytics Succeed
As a quick solution to get everyone on the analytics bandwagon, some organizations have chosen to set up different, team-specific solutions for various user groups. Maybe some data analysts decided to go around IT to purchase a data discovery tool, or perhaps IT added a new modern tool in addition to its traditional solution. Whatever the cause, this often leads to a whole different issue: siloed point solutions that don’t work together and are difficult to maintain.

You’ll always have users on both ends of the spectrum—from those who want simple dashboards with a little interactivity to data-savvy users who demand drill-down analysis. By selecting a comprehensive self-service product suite that provides a range of capabilities that can be tailored to different roles and skills, you can match capabilities to your users. This also ensures the tools work together to create an agile analytics cycle.

Adoption and success in data analytics is never going to happen overnight. But if you give your users an analytics experience that matches their skills and needs, you will notice an increase in adoption. People will seek out the data they need to do their jobs and you’ll be on the path to a high-performing, data-driven culture.

This article originally appeared on G2Crowd.