9 ways you’re failing at business intelligence

Executives know they need high quality data in order to make sound business decisions. But getting accurate data in a timely, user-friendly format remains a challenge. Sure, there is a vast industry of consultants and vendors with business intelligence (BI) expertise.

How do you know if you are being “led down the garden path”? Is it time for an upgrade to your BI or to launch a new training program? To answer these questions, knowing where others have made mistakes is helpful.

“The customer is always right.” It’s a noble sentiment that has done much to improve customer service, especially in retail. But with technology, business users may not always understand what they are asking for. Even worse, they may try to dictate the technical details of the solution.

Implementing what users ask for instead of what they need is a recipe for BI failure. “Successful BI projects require elaborating and managing requirements, as well as the ability to properly validate BI results,” says Wolfgang Platz, founder of Tricentis, which offers a continuous testing platform to companies such as HBO, Toyota and BMW. The “five whys” technique — asking why five times about a single issue to attain greater depth — is one way to understand what users truly need.

“Move fast and break things” is a key idea in the startup world. Established businesses, too, often have a need for speed. But in that quest to go faster, activities perceived as ancillary can suffer, like testing. Viewing testing as deadweight can lead to significant quality issues, especially if you rely on manual testing. Instead, look to testing and related “ancillary” processes as ways to deliver a higher-quality BI experience.

“Restricting testing, especially the only testing being done is manual, leads to a high number of defects in user acceptance testing that ultimately affect delivery times,” Platz says.

Business intelligence tools are excellent at processing, displaying and analyzing data. But what if you are feeding corrupt data in the system? Or better yet: How would you demonstrate to an IT auditor that you have high-quality data guiding your management decisions? Focusing too narrowly on the BI tool and its configuration may mean you will miss these critical details.

“Today, BI isn’t being used only to support better decisions; BI is often embedded into operational processes. If you have errors in your financial or regulatory reporting — which are often supported by data warehouse technologies — BI can help bring those to light. But other processes can still fail. For instance, an insurance company with broker fees that are calculated even just slightly wrong can negatively impact your reputation and then increase customer churn,” says Platz. “Today’s businesses need to have a proactive, automated approach to BI testing to expose data integrity issues as quickly as possible.”

Making mistakes with financial and regulatory data can lead to expensive problems. Poor data quality also wastes money. In 2013, the U.S. Postal Service was unable to deliver more than 6 billion pieces of mail as addressed. That means lost or delayed customer statements, lost marketing opportunities and more.

No technology professional looks forward to dealing with angry users. System failures and frustration points will happen. Your response to those issues will influence whether your BI initiative succeeds or fails.

“The two biggest mistakes I see BI novices make is focusing too much on delivering requests and not involving end business users in the project,” explains Doug Bordonaro, chief data evangelist at ThoughtSpot, which focuses on search-driven analytics for retail, financial services and other industries. “When customers are yelling at you about long delivery times and service level agreements being missed, it’s the obvious place to focus. Getting too involved in daily delivery misses the larger BI picture.