BIinnBusinesses aren’t taking advantage of the digital revolution. In less than 30 seconds, they can access more data than was available for the first 4,000 years of human history. Unfortunately, they aren’t taking full advantage of it.

This isn’t because they don’t value business data. Not at all. A recent study from Gartner found that business intelligence was a top priority for CIOs heading into 2017.

However, they make a variety of business intelligence mistakes that can become very costly. Here are some of the worst mistakes you can make.

Failing to Set Business Goals

Scott Schlesinger, North American Senior Vice President and Head of Business Information Management, Capgemini, told CIO that businesses can’t simply collect data and use it when necessary.

“One of the biggest [mistakes in] pursuing an analytics initiative is jumping in too soon without clearly defining what it is the company wants to accomplish,” Schlesinger explained. “Companies will not be able to generate any real ROI if they don’t outline the business case first and determining why and where leveraging big data makes the most sense in their operations.”

Gathering raw data is pointless, since it’s so difficult to access in a format you can use. A smart business intelligence strategy relies on structured data that is categorized according to your business needs.

Your business needs must be clearly established before gathering data. These needs can include:

  • Developing a better understanding of your customers
  • Addressing competitor strategies
  • Studying new markets that you hope to penetrate

Goals need to be clearly articulated, so data can be structured around them.

Failing to Identity Abnormal Activity

Human beings suffer from a number of decision-making heuristics. One of the biggest mistakes they make is searching for patterns that may not exist. Eddie Schwartz, chief information security officer for RSA, states that information officers need to be trained to identify unusual activity in their data.

“When we have those deviations, it’ll call attention to itself and say, ‘Listen! This is different than normal behavior,’ and those differences, when we combine them with things that we know, like indicators of compromise, like other types of potentially known bad behavior, or other things we know about our enterprise, it can yield fantastic results.”

A lot of factors come into play here. The analytics staff needs to be properly trained in analytics. They also need to trust that the data they are collecting is high quality and reliable. This means they need up-to-date software to design circuits that are used to process data efficiently.

Failing to Secure Data Properly

For most organizations, their data volume is growing steadily every day. They often look for the cheapest storage options to accommodate it. Unfortunately, the most affordable data storage options are often the least secure. This can lead to serious security breaches.

Steve Farr, senior manager for product marketing at TIBCO Software states that brands need to consider the legal and reputation risks of poor data governance. They need secure storage hosting and an internal security plan to keep it protected.

The security compliance program needs to be implemented consistently. Schwartz states that many organizations only use firewalls and other precautions after security breaches have already taken place, which obviously nullifies their value.

Keeping Department Managers in the Dark

Your organization can’t rely solely on your IT team to handle your business intelligence responsibilities. Managers from every department need to do their part.

Too many companies fail to communicate the importance of sharing data with their colleagues. They often view themselves as their own organization, since they often have limited contact with other departments.

This is one of the reasons organizations need to hold interdepartmental meetings on a regular basis. Every manager needs to learn the importance of data and incentivized to share it with their colleagues.

Becoming Distracted with Features

New BI analytics applications have powerful features, including search capabilities and charting tools. While these tools can be very valuable, they can also be very distracting.

Brands need to understand the actual purpose of these tools, rather than adapting them out of a sense of obligation. They must also understand the limitations of the most popular business analytics tools. They often lack the ability to integrate data, which means employees need to handle that task on their own.