10 BI Mistakes That Could Be Killing Your Analytics Projects

Avoiding common business intelligence pitfalls can help companies create a successful data-driven environment to inform faster, more efficient decision making.

Business intelligence is meant to improve workflows, but with any new addition to office life, there may be some bumps along the way. This is natural in a progressive BI adoption strategy. New habits can be hard to adopt, no matter how enticing the carrot at the end of the stick. The best way to keep employees focused on the end goal, though, is to prime the pump for the ultimate reward. Appeal to employees’ rational sides.

Every BI implementation should start with a BI road map of stages that ultimately end at the goal of a fully data-driven organization. Gather input from each department that would benefit from BI—which, executed properly, could be every department within the organization. Map out a step-by-step process that clearly lays out how each department will incorporate BI into their daily workflows from a practical standpoint, balancing both centralized and decentralized BI.

One of the most common pitfalls many companies fall into when starting off with BI is attempting to measure too many metrics. With so much information suddenly at decision-makers’ fingertips, BI users fall into the slippery slope of trying to monitor everything simply because they can. Establish the most important key performance indicators (KPIs) and create dashboards and analyses that reflect those, and only those. The right BI tool allows further drilling, digging and experimentation.

BI will never reach critical adoption across the company if end-users are not carefully considered. Analytics is not one-size-fits-all. Users across departments and roles will consume BI differently both in form and functionality. Some technically minded users will need access to the tools to create reports and analyses from scratch and access to data both inside and out of the organizations. But not every user needs advanced analytic functionality—and many shouldn’t even have access to those tools.

One of the primary benefits of a business intelligence and analytics strategy is to break down the silos that naturally exist in companies. But when working in isolation is ingrained within a company culture, it can be hard to break old habits. Some companies make great strides with their BI and analytics implementation and adoption, only to let that information live solely within departments. This is not how a data-driven environment is cultivated.

The popular myth that humans only use 10 percent of their brains may have been busted, but it’s no myth that most everyday BI users only scratch the surface of the capabilities of their analytics platform. That’s okay for many users who only need those key dashboards or reports to skim over each day, but it shouldn’t be the case for a company as a whole. You shouldn’t have to hire consultants or wait for IT each time users need a change to a report or have an idea about incorporating external data. Take the classes that will put you in the best position to harness the power of BI.

Self-service is good, right? Yes, and no. Modern BI models have made leaps and bounds with self-service capabilities in recent years. It’s fairly easy for users to get under the hood of the car, so to speak, which also means it’s fairly easy for something to go wrong. There are myriad ways bad data can end up floating around a data warehouse. Incorporating depositories such as in-memory, data lakes and other external data sources can add real power to a BI solution’s capabilities, but it can also spell real trouble. It’s critical to establish robust data governance.

BI myopia is a problem that strikes organizations of all sizes. In many cases, this comes in the form of license creep—not planning for the correct amount of users over time—and scope creep, also known as the never-ending project. But companies also fail to plan for the aging layers of their business intelligence application over time. In other words, pace layering.

Just as a failure to prime the pump is one of the first mistakes that can be made in a BI implementation, a failure to actively incentivize BI adopters can dim the importance of an analytics-driven environment. When employees can see the direct results of their own personal BI use, such as increased conversion rates, they’ll more concretely grasp the importance BI brings to everyday business tasks. Departments should call out BI success stories in group meetings to incentivize employees and share successes.

BI will never make its way into the daily workflow of decision makers throughout the company if it isn’t accessible from applications in which they already work. For many users new to the concept of BI, analytics can seem like a complex and intimidating tool to add to the to-do list. And as every manager knows, the more complicated a task becomes, the less likely it is going to be executed well or at all. Applications like embedded and mobile BI remove the traffic lights holding up BI adoption. Unobtrusive analytics capabilities take employees out of the busy city streets to a BI joyride in the wide open highway.