It’s time to abandon business intelligence tools

Organizations spend ungodly amounts of money — millions of dollars — on business intelligence (BI) tools. Yet, adoption rates are still below 30%. Why is this the case? Because BI has failed businesses.

Logi Analytics’ 2021 State of Analytics: Why Users Demand Better survey showed that knowledge workers spend more than five hours a day in analytics, and more than 99% consider analytics very to extremely valuable when making critical decisions. Unfortunately, many are dissatisfied with their current tools due to the loss of productivity, multiple “sources of truth,” and the lack of integration with their current tools and systems.

A gap exists between the functionalities provided by current BI and data discovery tools and what users want and need.

Throughout my career, I’ve spoken with many executives who wonder why BI continues to fail them, especially when data discovery tools like Qlik and Tableau have gained such momentum. The reality is, these tools are great for a very limited set of use cases among a limited audience of users — and the adoption rates reflect that reality.

Data discovery applications allow analysts to link with data sources and perform self-service analysis, but still come with major pitfalls. Lack of self-service customization, the inability to integrate into workflows with other applications, and an overall lack of flexibility seriously impacts the ability for most users (who aren’t data analysts) to derive meaningful information from these tools.

BI platforms and data discovery applications are supposed to launch insight into action, informing decisions at every level of the organization. But many are instead left with costly investments that actually create inefficiencies, hinder workflows and exclude the vast majority of employees who could benefit from those operational insights. Now that’s what I like to call a lack of ROI.

Business leaders across a variety of industries — including “legacy” sectors like manufacturing, healthcare and financial services — are demanding better and, in my opinion, they should have gotten it long ago.

It’s time to abandon BI — at least as we currently know it.

Here’s what I’ve learned over the years about why traditional BI platforms and newer tools like data discovery applications fail and what I’ve gathered from companies that moved away from them.

The inefficiency breakdown is killing your company

Traditional BI platforms and data discovery applications require users to exit their workflow to attempt data collection. And, as you can guess, stalling teams in the middle of their workflow creates massive inefficiencies. Instead of having the data you need to make a decision readily available to you, instead, you have to exit the application, enter another application, secure the data and then reenter the original application.

According to the 2021 State of Analytics report, 99% of knowledge workers had to spend additional time searching for information they couldn’t easily locate in their analytics solution.

On top of the inefficiencies created by a muddled workflow, add a failed user experience, lack of customization and slow data turnaround, and you have a recipe for disaster. During my conversations with business leaders throughout the years, one theme often boils to the surface: A gap exists between the functionalities provided by current BI and data discovery tools and what users want and need. BI tools lack the user-friendliness and simple navigation, efficiency and customization that make for a great experience. And research backs this up:

  • 42% of knowledge workers lack user-friendliness within their tool.
  • 49% lack the efficiency they need.
  • 40% find their tools lack simple navigation.
  • 34% desire more customization from their tool.

Simply put: BI tools are difficult to use. Many of these tools are not designed for the average business user, leaving many individuals feeling like they need an advanced computer science degree to actually be able to pull insights out. On the other hand, data discovery applications are presented as a more flexible option in terms of data exploration, but they take a one-size-fits-all approach rather than create a self-service experience that fits the end user’s unique skill level. And when we look at all this inefficiency, that’s where we see ROI break down.

Pretty visualizations mean nothing if they don’t provide real value

“We help anyone see and understand their data.” I won’t name names, but this is just one example of the vague tagline many BI and data discovery tools lead with. And, I’ll admit, the promise of gaining insight into and being able to clearly understand your business data could excite any business leader.

Unfortunately, the excitement typically fades after they realize the reports they’re being handed completely fail to add true value to their business decisions. Frankly, they’re just pretty visualizations that are missing the critical insights.

Businesses of today need tools that can produce data that can answer ad-hoc business questions and empower end-user action — letting teams find solutions quickly and take action right there and then.

Sometimes the issue comes from purchasing the wrong tool but, more often than not, it’s just another failing of traditional BI and data discovery tools. Even business leaders with a solid understanding of their data needs may come up short. This is where customization comes into play as a valuable asset. Functionalities like self-service customization and the ability to integrate directly with current applications and processes allow for efficient insights and increase overall value.

My best advice: Don’t get sucked in by the shiny object. Truly vet analytics providers. While there’s not a 100% guarantee any tool will go beyond surface-level insights like downtime and significant data outliers, there have to be better ways to use analytics in today’s fast-paced business environment than what we’re being forced into currently.

BI is expensive — plain and simple

New Vantage Partners published a study that uncovered that 55% of organizations have spent over $50 million on BI, with some even hitting close to $500 million.

I’ve found that when businesses hit a wall with their BI tool, many sum it up to operational inadequacies and adopt add-on solutions, such as data discovery tools, to solve the issue — then continue to repeat that process over and over and over again.

Before they know it, costs are out of control and their tool still isn’t giving them what they need and forcing them to continue existing workflows. BI comes with fundamental issues that continually fail despite tacking on more “advanced” capabilities.

Rather than continuing to rely on traditional BI and spending more dollars on data discovery tools in hopes of solving the issues with it, business leaders should look to the future and move to more effective solutions like embedded analytics. According to Gartner, embedded analytics is “a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.”

This stands out because, rather than requiring another application that forces users to exit their workflow, embedded analytics meets users where they are, creating greater efficiency and the ability to pull more real-time data. This can also be a more cost-efficient option because BI spending can add up fast when working to solve continual issues. Other solutions exist that don’t require additional applications and instead embed within current workflows, producing detailed and predictive reports that immediately showcase value. Find them.

Using traditional BI solutions and data discovery applications when your organization faces rapid digital transformation and needs insightful, real-time data is like mixing oil and water. Instead of throwing more money at your current tool to solve issues you’ll frankly never fix, ask yourself: Is this an operational or fundamental issue?

Industry leaders are demanding more, and rightfully so. It’s no longer acceptable for BI to be put on a pedestal when it continues to fail. Now is the time to abandon BI.