Consumerization is a difficult concept to apply to the business-intelligence (BI) industry. By its very nature, BI is about business—gleaning business insights from business data. If you consider the consumerization of IT to mean the ability of users to access the same software tools and the same user experiences in the workplace that they do in their consumer lives, it’s hard to see how business intelligence could ever reach that state.
So when we talk about the consumerization of BI, what do we mean? To take a broader interpretation of the term, consumerization means taking the user experience, learnings and delivery mechanisms from consumer-originated technologies and applying them to enterprise software. That means building business software that is simple and compelling enough to allow, in theory, its use by any consumer. It means creating intuitive interfaces that don’t require a training course or a manual to navigate. It necessitates solutions that are quick to deploy and accessible from anywhere, on any device. It also means putting collaboration tools and the ability to create user communities at the core of the software function and workflow.
In short, the consumerization of BI is about making beautiful, frictionless, collaborative and on-demand user experiences.
So how is the BI industry doing against this criterion? On the face, not great. BI adoption rates have been stuck at around 25–30% for the past decade, which means even in organizations where BI tools are available, at least 70% of potential business users don’t employ them. This situation usually translates to a large percentage of the organization working off spreadsheets and “gut feel” to track performance, diagnose problems and make decisions.
So why has BI not been consumerized to the extent of other enterprise-software sectors? The answer lies in the complexity of the problem that BI is trying to solve. Despite a growing number of new, more agile applications that purport to make every aspect of BI accessible to business users, the reality is that BI is an inherently complex process. It requires extracting, integrating, relating and exploring multiple data sets of varying sizes, from different applications and in different formats. It’s about manipulating data, and quite frankly, data is messy. There is no one-size-fits-all business-intelligence solution (although there are, of course, many point-solution apps that address narrow analytic use cases).
Compared with other enterprise-software categories, such as CRM, HR and enterprise social media, BI software is trying to solve a highly complex business problem that requires sophisticated capabilities and a lot of math. The challenge for BI vendors is in hiding away as much of this complexity as possible so that anyone, at any skill level, can quickly gather and mash together their various data sets and then produce accurate reports and dashboards on top of it. Creating this kind of simplified user experience for such a complex process is no easy task, and no single BI company has yet cracked it.
We are making progress though. First, cloud-based BI is taking off in a big way. Investment in traditional, on-premises BI has all but stalled, whereas the cloud BI market is projected to grow at a compound annual growth rate (CAGR) as high as 30%, according to some analysts. The maturation of cloud BI tools has greatly reduced the time, complexity and cost of deploying a BI solution. It’s also brought all the on-demand benefits of cloud computing to the BI world.
Huge strides have also been made towards simplifying the experience of visualizing data. Plenty of single-click visualization tools and drag-and-drop dashboard-building options are on the market. Such tools are close to frictionless and definitely beautiful.
Chief Analytics Officer Spring 2017
15% off with code MP15
Big Data and Analytics for Healthcare Philadelphia
$200 off with code DATA200
10% off with code 7WDATASMX
Data Science Congress 2017
20% off with code 7wdata_DSC2017
20% off with code AIP17-7WDATA-20