Enterprises looking to scale the benefits of their analytics programs are frequently looking to self-service options. Equip business users with the tools they need to get their own insights, whether it's dashboards, reports, or something else. Set up a system where these users are empowered to leverage the organization's data without needing to go to a data scientist or IT.
There are plenty of good reasons to pursue such a strategy. The data science talent shortage is a big one. Self-service analytics promises to alleviate the stress of that shortage by bringing insights and tools to the masses and removing the bottleneck of requests for tasks that can only be performed by rare and highly-paid data pros.
But putting the tools in place is just the first step, and it doesn't guarantee success of a self-service analytics program. The truth is that "analytics" can be a scary word to some people in the business domain who don't have a background in math or statistics. They may be intimidated by a new tool that at first glance looks complicated and unfriendly. They may prefer to make their decisions the way they always, have -- with their gut, or maybe with their own personal Excel spreadsheets.
So how do you spread analytics benefits throughout a user organization when users may be reluctant or resistant? Is there anything you can do beyond creating a center of excellence? Organizations are employing several tactics to encourage users to try self-service analytics tools, and we heard several of these at the Gartner Data and Analytics Summit 2018 in Grapevine, Texas this month. Here are six things you can do.
- Lean on your platform vendor for support and help. Data management and analytics platform vendors can provide help with training, videos, webinars, and access to all different levels of support. Use and promote these resources to your users to get them comfortable with the technology and master how to use it.
- Start off with a small number of users. Nissan began with 30 desktop users (out of the 100 Tableau desktop licenses it had initially purchased) and 20 server users. This is the part of the project where your organization is learning about the technology and how to best use it, build on it, and how your business users will get the most value from it.
- Create an internal web site for all your data and analytics projects to cover all the technologies users will encounter. Such a site will give users a central place to go to for access to resources that can help. For instance, you can use this site to list training videos, links to Q&As and step-by-step instruction guides, and forms to request licenses, to provide a central place for users to find answers to their questions, training resources, access to license request forms, and more
- Gain buy in from business users by making them admins. Nissan named two site administrators for each business domain (such as finance, manufacturing, and sales and marketing). One of those administrators was actually a business user, and the other was from the IT organization. This two-administrator approach let Nissan get the expertise of the business domain and backed it up with the infrastructure knowledge of the IT administrator.
- Consider holding an event. At the 6-month mark of its deployment, Nissan sponsored a Data Management and Analytics Expo -- an onsite conference designed to introduce the platform to the business, provide education, and encourage networking between business and IT users. About 70% of attendees were from the business side of the house, and the other 30% were from the IT organization. After the Expo, Nissan went from 30 desktop users to 120 desktop users. Server users went from 250 to 900.
- Create user groups for your data and analytics platform. Just about all of the successful implementations presented at the Gartner Data and Analytics Summit had included user groups as part of their deployment strategy. For instance, Rockwell Automation set up such a group for business users in its Microsoft Power BI deployment. Southwest Airlines participated in Alteryx user groups, and Nissan created user groups for its Tableau deployment.