Building trust in analytics

With our algorithm visualization solution, Deep Algo is at the forefront of the Algorithmic Transparency.
Today, we are happy to share with you KPMG’s latest report : Building trust in analytics.

Data and Analytics holds the power to unlock untold value. But first you need to trust what the analytics are telling you.
KPMG’s latest report explores the value of trust in the D&A equation. The report includes practical tips and ideas to help break the cycle of D&A mistrust.

>> KPMG’s report

Building trust in analytics

You can’t make sound business decisions if you don’t trust your data and analytics. Yet only around a third of all organizations have a high level of confidence in their customer insights or the analytics they receive on their business operations.
In this report, KPMG International explores the current trust gap affecting organizations around the world.
Based on a global survey of more than 2,000 organizations, the report shares insights and recommendations on suggested processes, practices and governance for building trust in D&A using KPMG’s four anchors of trust, a framework for assessing quality, effectiveness, integrity and resilience.
Should you trust your analytics?

“As analytics increasingly drive the decisions that affect us as individuals, as businesses and as societies, there must be a heightened focus on ensuring the highest level of trust in the data, the analytics and the controls that generate desired outcomes.”

– Christian Rast, Global Head of D&A, Partner, KPMG in Germany

Executive summary

Data and analytics (D&A) increasingly shapes our world.
Complex analytics are delivering better, faster decisions and this is driving rapid investment across all business sectors.
Today, the impact of analytics goes far beyond organizational boundaries and underpins many of the most important decisions that we make as individuals and societies.
The trust gap
Given the power that it holds, trust in D&A should be a nonnegotiable business priority. Yet our survey reveals that this may not be the case. In fact, 60 percent of organizations say they are not very confident in their D&A insights. Only 10 percent believe they excel in managing the quality of D&A.
Just 13 percent say they excel in the privacy and ethical use of D&A and only 16 percent believe they perform well in ensuring the accuracy of models they produce.
Despite this clear worry about the trustworthiness of their D&A, 77 percent of organizations still say that their customers trust their organizations’ use of D&A. Yet fewer than half are sure that their organizations actually track their customers’ views on the use of D&A.
Our study also shows that levels of trust are lowest at the end of the D&A lifecycle, suggesting organizations may be struggling to implement D&A effectively and link it to positive business outcomes. The result is that few organizations understand whether their D&A models are
actually achieving what was intended.

Strengthening the anchors of trust
We believe that organizations must think about trusted analytics as a strategic way to bridge the gap between decision-makers, data scientists and customers, and deliver sustainable business results.
In this study, we define four ‘anchors of trust’ (quality, effectiveness, integrity and resilience) which underpin trusted analytics. And we offer seven key recommendations to help executives improve trust throughout the D&A value chain.
We believe that strengthening the anchors of trust means identifying and closing the gaps in D&A and managing it across the organization. It is not a one-time communication exercise or a compliance tick-box. It is a continuous endeavor that should span the D&A lifecycle from data through to insights and ultimately to generating value.