Business Leaders Still Have Trust Issues with Data (Part 2)
Last month, I discussed the importance of the trust factor in moving forward in a data-driven enterprise. Without trust, any data analytics effort will fall by the wayside.
I want to update my post with some good news and some bad news. First, the bad news: many CEOs haven’t learned to trust the data coming out of their analytic applications. The good news is that they recognize the importance of data analytics, and are not holding back from actively investing in these initiatives.
Such are the findings from a survey of 400 top executives conducted by KPMG, which found that only one-third of CEOs trust the insights coming from their data analytics applications, while close to one-third have limited trust or actual distrust of its use. Privacy is also an issue. Eighty-four percent of top executives are concerned that their customers may be more worried about their privacy than their organizations are.
While still wary of what analytics may be telling them, CEOs named data and analytics as a top-three investment priority for the next three years. A total of 24% indicate they are investing more in their data analysis capabilities, a priority that’s ranked third behind new product innovation and cybersecurity.
Make no mistake, data analytics is on top of mind for business leaders. They plan to dive into ever-expanding data resources to develop new products and services as well as drive efficiencies and strategy. “For CEOs the goal is clear: to create a more intelligent, data-driven experience for their customers, their innovators, and their partners,” the report’s authors state.
Before committing the futures of their businesses to data-driven insights, however, CEOs want to know that they are working with the right and most timely data. Seventy-seven percent, in fact, said they have concerns about the quality of data on which they base their decisions. In addition, less than one-third (31%) feel their organizations are leaders in data analytics.
Much of the leeriness about data quality is a result of the continued existence of silos across enterprises, as well as slow progress in bringing together disparate systems. “Data quality is a fundamental issue and challenge for every company,” says Cliff Justice, innovation and enterprise solutions leader with KPMG. “Companies that are on standardized ERP systems can compile data more easily, while companies that are very fragmented may have issues.”
There is also a need to “change our understanding of what constitutes data,” Justice continues. “It is no longer only a tabular structure of rows and columns that are machine readable. Eighty percent of data resides in e-mails, social media conversations, or images, the so-called dark data. Cognitive systems can access and interpret this unstructured data, which allows for making more data-based decisions derived from a much bigger pool of data.”
The ways organizations are using data and analytics include developing new products and services (51%); driving process and cost efficiency (50%); finding new customers (49%); driving strategy and change (48%); managing risk (46%); analyzing how products are used (45%); and analyzing customer preferences (44%).
(Disclosure: I have been involved in the authorship of other KPMG reports as part of my work with Forbes Insights.)