Business leaders, no matter their function — from sales to IT — have a simple shared goal: they want to know what is happening in their company and why. And they want that information readily available, on tap whenever they need access. For smaller businesses, this information can be easier to come by. But for enterprises, understanding the basics of “the what and the why” can be extremely challenging.
The reason is complexity. At the same time that enterprises have become increasingly sophisticated, they’ve become increasingly intricate. There are usually myriad technical systems deployed across the business, but they often don’t integrate well. This leads to siloed data and to insights that aren’t that insightful. Different functions prioritize different information, which creates isolated viewpoints into the state of an organization. Soon, everyone has different answers to “the what and the why” questions.
Analytics to the rescue. Business intelligence (BI) platforms are supposed to bring halcyon days of understanding for every enterprise, deliver significant competitive advantages, and drive key decision-making. They are meant to offer a single source of truth for every business leader, no matter the function. But the reality is somewhat different. A recent survey found that although 84% of organizations have deployed advanced analytics capabilities, fewer than 60% have experienced success or real results from the investment. Many are struggling to find sustained value.
Let’s examine why this is and what can be done to fix it.
Often, the people who select the BI platform aren’t the people using it. For example, if business users were charged with selecting an analytics platform, they would likely draw up a different set of priorities than if IT were making the selection. While everyone’s intentions are good, without taking the time to understand the needs of each function, a natural disconnect occurs when implementation rolls around. There also might be a data and IT skills gap, which can lead organizations astray, making it difficult to pick an analytics tool that works for all skill levels and all business problems.
Taking the time to know your users — every single role and group who will use the platform — is critical to making the best selection. Different parts of the organization might resist this. IT will likely be charged with implementing the platform, and involving other groups in the assessment and evaluation may seem to them needlessly time-consuming.
But the downside can be debilitating. After a significant investment in resources, nothing is worse than hearing back from business leads that they’re not getting what they need, and it’s hampering their performance. Companies that take the time to involve every part of the business with a user-first approach will reap huge benefits. They make sure every group is invested and knows how to make the most of a BI platform.
Once you align the needs of business users and IT, the next step is to do a rigorous analysis of how each BI platform defines “end-to-end.” Many analytics platforms purport to be comprehensive, but after some digging, some capabilities seem whiz-bang, but others are lacking.
Take data visualization. While gorgeous graphs and pictures are engaging, they’re only as useful as the data they represent. They may just be serving you data you already know about in a slightly more dressed-up way. Make sure you don’t just assess a BI platform on how good its interface or visualizations are, but how much analytical depth it offers.
Some platforms aim to simplify everything so much that they end up not being able to answer complex business questions. You’re left trying to understand what actions to take, without having any meaningful analysis to rely on. On the other side of the spectrum, there are platforms that are too complicated for most people to actually use. Sure, your data scientists take to it, but everyone else gives up. Testing a platform with all of your users is critical before deployment.
Because so much depends on a robust, comprehensive BI platform, you need to make sure the data you’re relying on is also robust and comprehensive. Governance capabilities are a critical component of any platform: you need to be able to manage data from a centrally administered repository so that analysis can be reproducible and defensible. It’s essential to be able to trace the origins of the data easily, as well as the techniques used to examine it, and know who prepared the analysis.
Seeking a happy medium, so you deliver the depth of understanding both business users and IT require, will set your company up for success. Each function has big “what and why” questions to ask, and your analytics platform should not just be able to answer them, but answer the next one, and the one after that.
By taking into account users from across the spectrum of your organization, and rigorously examining analytics platforms to find one to match all of their needs, you can deploy a solution that doesn’t just make each group happy, but drives your business forward. Bridging this gap can be daunting, but the payoff is worth it.