In a Wednesday report, SnapLogic revealed that by using data more effectively, enterprises expect to increase annual revenue by an average of $5.2 million.

According to the report, the average business plans to invest $1.7 million in preparing, analyzing, and operationalizing data over the next five years. This figure is nearly doubled from the current average amount invested, $800,000. The report noted that with the increased investment, businesses could expect to benefit from a potential 547% return.

Despite the potential for increased revenue through data technology, the average organization only uses 51% of collected and generated data, the report noted. Only 48% of decisions are made based on data.

SEE: Data classification policy (Tech Pro Research)

But, what data makes the biggest impact? The report found three types of data that are most valuable to businesses.

  1. Customer data (69%)
  2. IT data (50%)
  3. Internal financial data (40%)

The report noted that dealing with manual data entry can cost companies time and resources. Respondents reported that they spent 20% of their time working on getting data ready to use. This presents a serious opportunity for automation. Firms should consider which of their manual data processes are most time-consuming, and look to machine learning and similar tools to automate them.

While 98% of respondents reported that their organizations are planning for, or are in the process of digital transformation, only 4% are ahead of schedule.

“Legacy systems, tedious manual labor, and the sheer volume of information are preventing organizations from maximizing their data-driven potential,” SnapLogic CEO Gaurav Dhillon said in a press release.”The enterprises that act now to spread data literacy throughout their business will be the ones to thrive.”

The big takeaways for tech leaders:

  • By investing in better data management, companies can expect a increase their annual revenue by an average of $5.2 million.
  • The types of data proven to be most valuable to companies are customer data, IT data, and internal financial data.