As business intelligence consultants, we want our projects to succeed. After all, successful projects are profitable projects with happy customers. When we start a BI project with a new customer, we can never be 100 percent certain it will succeed. But, over the years, we’ve identified five indicators that a business intelligence project will fail. Here they are:

1. You Don’t Have a Strategic Reason for Doing the BI Project

Let’s talk about what I mean by “strategic reason.” A strategic reason isn’t what you wrote on a form to get management approval. It’s not something where you calculated (to four decimal points) that Project X will save Dollars Y and therefore provide Payback Z over many months. A strategic reason isn’t that your project will make life easier for a few folks in the back office.

When the reason for a project is strategic, senior management will INSIST that it gets done—even if it means bringing in other people to do it. A strategic reason doesn’t just cover the costs the project but will provide a payback or benefit multiple times the investment.

Recently, I wrote a post on business intelligence ROI where I discussed the strategic reasons behind several real world business intelligence projects. In each case, these projects HAD to be completed. As a result, when obstacles arose (whether technical or political), we could escalate and get the job done.

I’m not saying you can’t get a few reports written or improve a few processes without a strategic reason. You can. But any larger project will die a slow death without it.

2. You Confuse What You Need With What You Want

We need some things. We want much more:

  • I need to make sure my current customers pay on time.
  • I want to have 20 new customers in the next year.

Business intelligence is no different:

  • You need to get your reports done on time.
  • You need them to tie out.
  • You need to make your investors happy.
  • You want every report to be just so.
  • You want dashboards and cool stuff.

Even if you have a strategic reason for a BI project, you can still get trapped in “wouldn’t it be cool?” or “could you just add?” Which means your business intelligence projects never get done because there’s always one more thing.

Focus on needs and you’ll get results.

3. You Won’t Spend the Time to Review Your Own Data

I tell customers it’s our job to ensure your data is consistent. It’s your job to make sure it’s right.

Over time, with some customers, we do develop a basic intuition about what are “reasonable” numbers in their universe. And we try to only present things we’ve reviewed for basic intelligence (if at all possible). However, we’ll never know your business as well as you.

Further, data always changes. Going through the data once is necessary but not sufficient. If you have multiple ERPs with multiple customer lists, for example, you have to commit to keeping them mapped if you want good data.

4. You Don’t Create Business Processes to Ensure Good Data

Eternal vigilance is the price of good data

—Jim Jefferson (IT manager and Thomas Jefferson descendant)

Seriously, even if you do everything right to get your project going, it can still fail over time if people don’t maintain the processes and procedures necessary to keep data clean. Do you allow people to create new entries in the chart of accounts without review? Do you review coding in your various systems—and retrain folks who make mistakes?

5. You Have Bad Source Data

This is last on the list for a reason. For most of our clients, bad source data isn’t the main issue.

Of course, that’s not always the case. We’ve worked with our share of old stuff, including IBM System/36 with internally described files and Access databases “designed” by folks with no real understanding of what a relational database is (see post, The Pivot Table Gateway Drug). It can get ugly. And it’s extremely difficult to estimate how long it will take to get these projects done.

In contrast, the vast majority of our clients installed their systems in the last 15-20 years—so most are using relational databases. While they’re not perfect, they pretty much work. (The systems may not talk to each other. And their staff may not enter data correctly. But that’s another story.)

You’ll note that bad technology isn’t on the list. Maybe that’s because we use Microsoft Tools. It isn’t the fanciest solution, but it works over and over again. But even when we’ve used other (from Business Objects to QlikView), technology hasn’t been the issue.

Is your BI project doomed to fail? Let me know if you’ve experienced any of these business intelligence problems.

 

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