In every line of business, there’s an opportunity for self-service analytics. Although the industries vary, the bottom line doesn’t change. What organizations all share are the impacts of high levels of self-service analytics and what they have to offer. In our two previous blog posts on self-service analytics, we laid out the benefits to organizations and all the do’s and don’ts when implementing a self-service analytics tool. In today’s post: how to get maximum results from self-service analytics.
Aberdeen set out to survey the self-service landscape. During this research, it examined the differences between high self-service organizations and low ones. Feel like you’re not getting the most out of your self-service tool? Here are some ways to amp up your analytical insight.
1. Spreading self-service analytics like wildfire
Implementing an analytics tool isn’t a cure-all in and of itself. It opens the door for opportunity, but like a new life form, it needs to be nurtured and cared for. Organizations with low-levels of self-service must invest time into their analytics tool so they can eventually onboard more users. Maturing a company in self-service analytics doesn’t happen overnight, but the more energy put into perfecting user education will speed up the process and have you running with the big dogs in no time. Empowering more users will give employees faster access to the answers they need, and will reduce the need for IT services, allowing IT to work on more strategic analytical projects.
2. Gaining back user trust in underlying data
There will always be skeptics when employees are handed numbers without seeing where the data came from. Insecurities in underlying data will lead to questions of uncertainty and cause workers to not want to claim ownership of their analyses. High self-service organizations generate confident users because they can wrangle data with their bare hands, freely explore the accessible information and uncover hidden insights. The more eyes a company has looking at its critical data, the more ways it will be dissected and cross tabulated with additional data sources. Users will be determined to find their own answers and take pride in their analyses.
3. Getting the most out of your users
One of the most critical mistakes organizations make when it comes to self-service analytics is to abandon ship. After you’ve put the time and effort into establishing strong training programs to develop users with outstanding analytical knowledge, don’t leave them hanging out to dry. If users are struggling to generate analyses they will eventually become frustrated and make mistakes, or give up and strictly rely on others to get their numbers. This defeats the purpose of self-service analytics. Once you take those three steps forward – avoid taking five steps back. Engage with users and make sure your organization is setting them up for a win.