What’s your self-service data analytics strategy?
I received an email a few weeks ago from a prospect whose title was “Sr. Director of Self-Service Analytics”. It piqued my interest enough that I immediately went to LinkedIn to see how many other people in my network had an analytics-related “self-service” title. The search netted 23 people – amazing, I thought. It also reminded me just how far the analytics movement has come in such a short period of time.
Self-service data analytics provides the convenience, timeliness, and control the line of business demands. It’s clear to me why Gartner changed their focus on their latest BI & Analytics Magic Quadrant to look at the market from a self-service perspective. Truth is, the last two enterprise data analytics deployments I was involved with here at Alteryx were budgeted by the business, not IT. That’s not to say we didn’t work with IT during the process, but their role was in supporting the deployment, not driving the requirements. That’s typical of the shift that I, and my colleagues, are witnessing in the market.
It’s no surprise that the self-service data analytics movement is winning over the minds of forward-thinking executives. For years, companies have invested millions of dollars to ensure their own customers can “self-service” themselves with the products and services they offer to the market. It only makes sense that these same companies now take this strategy that has generated millions of dollars in additional revenue, an improved customer experience, and better margins, and apply that same philosophy to how they run their business internally.
The old approach that included a centralized team that performs most of the analysis on behalf of the line of business has proven not to scale, and frankly it’s not what the business wants. It works well for the specialized projects that require data science expertise. However, the core business analysis tasks, which are the majority of asks by the line of business, should be left to the analysts in these line of business departments.
How is your company embracing the self-service data analytics revolution?
Chief Data Security & Privacy Officer at Michigan Department of Corrections
9 年Self Service data analytic and enterprise data sharing are the key players today.
Self-Service covers a wide spectrum. I think that the issue/challenge is less about IT's role, but the involvement of skilled data scientists/analysts that can partner, as needed, with LoB users. Creating visualization outputs is one thing. But it's another thing to create models. IMO, we're a a ways from mass self- service, full-spectrum analytics. You'll always need really good, and today, rare, people to validate models- be they centralized, or in the LoB's. Perhaps the key is to be really specific about the exact meaning of self-service.
Sales Executive
9 年I like the second paragraph that highlights the shift from IT controlled software decisions to business unit lead initiatives. ... But isn't this how it should be?? Business users are closer to customers and operational efficiency gains that can transform a business- give the business user complete (governed) autonomy over questions they can ask of data and watch as the value starts to surface. Pervasive insights across the enterprise needs IT support too though. Get IT back to improving the speed and performance of the flow of information systems and you have a solid marriage between IT and knowledge workers.