This is the second article in our series about tools that aim to help users make decisions using data. In our first article, Katie discusses why Dashboards Don’t Cut It.
After dashboards, came the advent of self-service tools and with them the promise of alleviating the report backlog. By providing users the ability to make their own reports, IT would be unburdened and free to head down to the beach for some much-needed R&R. In this article, I’ll talk about how and why that reality never came to be based on my experience implementing self-service BI tools for enterprise companies with thousands of users.
Expectation vs. Reality: Necessary governance limits self-service tool power
When self-service tools arrived, they were accompanied by the invariable governance lockdown that prevented users from using most of the self-service features. IT departments worried that users would not know how to use the tools and data correctly and would create inaccurate dashboards without best practices that might hurt their servers. This has resulted in predictably long data preparation processes and careful oversight by IT in most organizations. Even in the best self-service implementations, it’s difficult to prepare for every possible use case and users are frequently in need of time-consuming assistance to use data.
To draw a comparison, consider self-service checkout stations at grocery stores: they are great for quick trips for a few items. However, if a customer needs to have an ID checked, use a coupon, or remove an item from the bagging area, human intervention is often required. These ubiquitous self-service tools are great until there’s a special use case. Like self-service checkouts, dashboards and self-service business intelligence tools may respond to many needs, but there is a gap when it comes to serving special cases or advanced data exploration needs.
Catering products for the many leaves power users wanting
For sophisticated users who are known within their organizations for uncovering answers in data to support important decisions, self-service tools are often unable to provide enough flexibility to furnish the answers they need. When analysts need to quickly answer a question, they don’t have time to wait on the configuration of these tools and the procurement processes that they require, which is why they end up grabbing data and putting it into Excel to explore.
Enterprise self-service tools generally cater to a larger audience and require solutions to be “watered down” to the lowest common denominator of the audience’s data literacy. However, more employees are becoming data and technology savvy as time goes by and organizations are recognizing the need for and funding data literacy initiatives. Advanced users often wish to do their own data analysis and exploration, and current BI tools implemented at the enterprise level are not made to support these use cases.
Providing the tools that sophisticated data explorers need
I have worked on implementing these tools for thousands of users, and for the general user seeking consistent answers, they can be transformative. However, for power users that want to quickly draw data from multiple sources without jumping through hoops, these tools fall short. Many in this group end up going outside of existing tools to analyze and explore their data quickly.
Knarr is here to provide those sophisticated users with a tool that meets them where they are. Incorporating collaborative features so that they can easily share their analyses with team members, providing advanced data exploration capabilities, and allowing for powerful processing and visualization, Knarr empowers those that want to dig into their data in a whole new way, how and when they need to do it. Our tool’s cloud-native architecture and powerful server provide an environment for advanced users to thrive. To learn more about Knarr visit us at https://knarr.io and try the tool for free.