Data and analytics initiatives may underpin every digital transformation initiative, but can these programs be trusted? A new survey from KPMG shows that even those running the programs don't always trust them.
Data and analytics initiatives may be a central part of digital business transformations, but that doesn't mean that top executives trust these efforts, even within their own organizations.
A new report commissioned by KPMG and conducted by Forrester Consulting finds that nearly half (49%) of data professionals surveyed said that they believe their C-level executives don't fully support their organizations' data and analytics strategies.
That finding marks a disconnect between the thinking that calls for investment in data and analytics, which KPMG says is "now central to business decision making," and what KPMG says are "significant questions [that] are starting to emerge about the trust that we place in the data, the analytics, and the controls that underwrite this new way of making decisions."
Organizations don't trust their analytics because they don't understand them, Nadia Zahawi, director of Global Data and Analytics for KPMG in the UK, told InformationWeek in an interview. Data and analytics often reside inside a "black box" where the data goes in and the insights come out, but stakeholders don't see the process that happens inside the box.
Indeed, stakeholders tend to have more trust in the data at the beginning of the process, before analytics are applied, Zahawi said.
And yet data and analytics are essential, according to the survey results. A full 70% of respondents said that data and analytics (D&A) are integral for understanding how products are used, and 69% said D&A are integral for understanding existing customers. And 67% said D&A are key for understanding what new products and services to develop.
[It's hard to know who to trust these days. Get help by reading Can You Trust Your Cloud Vendors' Employees?.]
Respondents also said that data and analytics were essential for understanding internal business processes including business performance (cited by 71%), how to drive process and cost efficiency (68%), and how to drive strategy and change (70%).
And data and analytics were also crucial for managing risk and compliance, preventing problems such as fraud (cited by 70%), business risks (67%), and compliance with regulations (70%).
Zahawi told InformationWeek that establishing trust in analytics programs is tied to four "anchors" that are quality, effectiveness, integrity, and resilience. And yet few firms are achieving best practices against all these anchors of trust. For instance, the survey shows that only 10% of respondents say they believe that their organizations excel in the quality of data, tools, and methodologies. Only 13% say they believe they excel in the privacy and ethical use of data and analytics. And 16% say they believe they perform well in ensuring the models they produce are accurate.
Does that mean all the data and analytics efforts out there can't be trusted? Zahawi said that there is a difference between actual trustworthiness and perceived trustworthiness. The lack of transparency around analytics -- the fact that non-data professionals don't know or understand how it is performed -- can lead to a lack of trust. But that doesn't mean the data analytics efforts themselves are not worthy of trust. It means that the non-data pros don't know enough about these efforts to trust them.
And then even if stakeholders decide that they can trust the analytics, is it really worth it? Organizations may also be uncertain about whether the analytics are delivering any sort of return on investment in terms of better decision making for the organization, Zahawi said.
One way to fix the trust issue is increasing transparency in the data and analytics process, Zahawi said.
"Open up the black box and show how data and analytics works," she said. In some cases this added transparency may be driven by regulatory requirements or consumer demand -- for instance in healthcare or autonomous vehicles.
Organizations must improve those levels of trust for their data and analytics programs, according to the KPMG report.
"Trust underpins everything we do as companies, as people, and as society," said Christian Rast, KPMG's Global Head of Data and Analytics, in the report. "Organizations need to start by creating a solid foundation of trust within their D&A so that when the time comes to 'step on the gas,' they can accelerate their initiatives and objectives with confidence."
The KPMG report is based on a survey of 2,165 high-level data and analytics decision makers at organizations with at least 500 employees in 10 countries including Australia, Brazil, Canada, China, France, Germany, India, South Africa, UK, and US. These decision makers are described as those responsible for setting strategy for, or management of, business intelligence, data analytics, data warehousing, and/or data management/big data management initiatives.