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7 common problems that lead to BI failure

EducationSummary: As businesses create more data than ever before, Business Intelligence is growing. The only problem: Many Business Intelligence projects still fail. In this article, you’ll learn why this happens and problems to watch out for in your BI journey.

photo credit: geralt via pixabay cc
photo credit: geralt via pixabay cc

Business Intelligence adoption is exploding. As data volumes expand, more and more businesses are adopting BI solutions in order to turn this data into meaningful information.

How fast is the BI market growing? As mentioned in this article, Gartner predicts that “the global BI and analytics market will reach $18.3 billion in value this year, an increase of 7.3 percent over last year. The market will grow to $22.8 billion by the end of 2020.”

But, despite all of this growth, there’s still a problem. Many BI implementations still fail, or just aren’t as successful as they should be.

How many?

Depending on which survey you read, the BI failure rate is anywhere from 50% – 80%. Gartner is widely quoted as saying it is 70%.

Why does this happen?

While there’s no single reason that causes failure, you’ll find there are a few common drivers. Today, let’s explore this topic. Here are 7 common problems that lead to BI failure.

1. There’s no target

photo credit: Bogdan Suditu via photopin cc
photo credit: Bogdan Suditu via photopin cc

Imagine you’re in an archery competition. But, as you pull the bow back and aim your arrow, you realize something: The targets are blank. No bullseye. No lines. Nothing.

How will you know if you succeed?

Many BI projects begin this way. They have no clear goal, no definition of success. They start the project without clearly defining their target. They don’t map out exactly what success will look like.

How can you avoid this problem? Agree on clear goals from the start. Now, I’m not talking about vague goals like, “better data access” or “improved decision-making.” Those are great benefits but aren’t specific. The goals must be specific to the problem you are trying to solve.

Without specific goals, you won’t know if you’ve succeeded. Without specific goals, those working on the project won’t be on the same page. If those working on the project aren’t on the same page, your project will likely fail.

2. BI is focused on data, not action

What is the purpose of Business Intelligence? To display data? To take data out of your systems and make it accessible to users?

While that is certainly one goal, successful BI projects go far beyond that. Their purpose isn’t about displaying data. It’s about providing insights. It’s about driving action.

The problem with many BI applications: They display data, but do little else. They’re nothing more than charts on a page. They don’t drive action.

If your BI isn’t delivering insights to your users, what happens? It offers little value. Sooner or later, the novelty wears off, and users stop using it. As explained below, users need actionable data displayed in bite-sized chunks.

“I believe a huge reason why BI projects fail is that the dashboards typically show a large assortment of charts and graphs, but don’t provide actions on what to do next,” says Emerson Taymor, Founding Partner at Philosophie. “In today’s busy and always ASAP workplace, managers & executives need bite-sized ways to take action on these graphs.”

“Just seeing a sea of charts is overwhelming. From there it is hard to take action on a high-level business metric, it is much easier to understand what smaller behavior or mechanic may be changeable (that will eventually tie to that end business outcome).”

3. BI is approached as a one-time project

Many people get involved in the planning, building, and implementation of a BI solution. The IT department, business users, and executives all have input in the process. Sometimes the business even brings in outside consultants to help out.

But, what happens after the solution is rolled out? Is the project over? Not at all.

Here’s where the problems arise. In many businesses, no one takes charge of the solution’s growth and adoption once it’s live.

The businesses focus so much effort on implementation but forget about what happens once it’s built. Who owns the solution once it’s live? Who is in charge of ensuring that it grows and adapts to the business? Who will drive education and adoption? As explained below, much of the real BI effort occurs after the solution is rolled out.

“Most of the BI projects are treated as one time done deal,” says Vipin Tyagi, Senior Director at Axtria. “We all know that change is constant, whether it is Business change, Rules change, or User change. We need to make BI and Analytics part of the operation that covers the change management to keep improving and enhancing existing BI application with respect to changed requirements and functionality. Else, 6 to 18 months down the road, adoption of the application will go down.”

4. Lack of communication

photo credit: nuggety247 via pixabay cc
photo credit: nuggety247 via pixabay cc

Communication. It’s one of the most common reasons why BI projects fail. Without constant communication between the users and the IT department, a BI solution will probably fail.

How does this happen? Sometimes, the BI solution gets selected without input from the users. Other times, users are only involved at that start of the project. Still other times, there’s miscommunication. The users don’t explain their needs well enough, or the IT department doesn’t understand what they want.

How do you avoid this? As explained below, successful BI projects need constant communication throughout the project.

“With Business Intelligence there’s sometimes an assumption that the technology alone is enough to build a project but without a clear adoption strategy from the outset, success is not guaranteed,” says Tom Feltham, Marketing Operations Director at ExploreWMS. “When communication between those affected by the implementation of BI technology across departments breaks down, it is common for silos to occur. “

BI projects are by nature data-centric and problems arise when non-technical staff are unable to engage at the adoption phase. The effort of building a data warehouse needs to be worth the return on investment in terms of user numbers and this isn’t always the case.

Before implementation, there should be a fully developed company-wide BI strategy in place with interdepartmental members at the helm to improve lines of communication across the organisation. In addition, it’s important to establish a plan for a review process as users will inevitably need to make changes to replace or eradicate functions according to their needs.

If BI fails, it’s more often than not the processes behind the technology rather than the technology itself. By improving communication between BI professionals and non-technical business users, organisations will be able to adapt a BI project in a way that better suits their needs.”

5. Lack of buy-in

Companies who are most successful with software implementations share many common characteristics.

One of the biggest ones: They have top-down buy-in. Everyone involved in the BI process–from the decision-makers to the users–is on board. Their decision makers understand the goals and will do what it takes to complete the project. Their users understand the benefits.

What happens if you lack full buy-in? The project will likely fail. Before beginning any BI project, get key personnel on board. Make sure they understand the benefits of the project and are committed to seeing it through. This buy-in will get the BI project through the tough times, and help ensure its success.

“Business Intelligence projects fail when key personnel don’t buy in,” says George Anderson, Communications Manager at Corevist. “Business Intelligence success, like anything else, is management success.”

6. Measuring the wrong (or dirty) data

photo credit: ATMDepot via pixabay cc
photo credit: ATMDepot via pixabay cc

Imagine that you just bought a shiny sports car. It’s expensive, and has all the bells and whistles. But, instead of filling it with gasoline, you fill it with dirty water. Is that car going anywhere? Of course not.

The same thing happens with Business Intelligence. An organization licenses a best-of-breed solution. But, then they fill it with unorganized, dirty data. Or, they fill it with clean data that has no business being measured.

As explained below, if you want your Business Intelligence solution to succeed, it must start with your data.

“In my experience, data integrity is one of the largest factors in failed BI projects,” says Rick Hurckes, Services Director at mrc. “Business Intelligence is only as good as the data that goes into it. You can’t have a successful BI implementation when the underlying data is compromised.”

7. Users don’t like the solution

Suppose you’ve done everything correctly so far. You’ve set a clear target. You’ve secured executive buy-in. You’ve cleaned your data.

Even after all of that, the BI tool can kill the whole thing. If users either don’t like the chosen tool or find it confusing, they likely won’t use it.

Why does this happen?

Oftentimes, the IT department takes the requirements from the users and then finds a solution that checks all of the boxes. However, they don’t involve the users in the decision-making process.

What happens? The users are handed a tool that meets all of their requirements but is difficult to use. Maybe it’s confusing, too technical, or the users just don’t like it. Whatever the reason, problems like this will kill a BI project.

How can you avoid this issue? Involve key users during the solution selection process. Make sure that the chosen solution meets the approval of the users before licensing it.


While the list could certainly be longer, these are just 7 problems that lead to BI failure. Would you add anything to this list? If you would like to add anything to this list, I’d love to hear it. Feel free to share in the comments.

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