Building trust in analytics

Building trust in analytics

Breaking the cycle of mistrust in Data & Analytics (D&A)

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Today, complex analytics underpin many important decisions that affect us as individuals, as businesses and as societies. Biased, gut feel and subjective decision-making is being replaced by objective, data-driven insights that allow organisations to better serve customers, drive operational efficiencies and manage risks. Yet with so much now riding on the output of data and analytics, significant questions 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.

We believe this report provides a very unique view into a fundamental challenge facing most companies today. And we believe it creates a significant opportunity. Indeed, those that are able to overcome the trust gap quickly will be the ones that will be better-placed to make faster decisions, more accurately and with much greater confidence. Those will be the organisations that will win in the future.

The trust gap

Just 34 percent of respondents say they have a high level of confidence in their operational D&A. Around the same number (38 percent) voice a high level of confidence in the D&A that drives their customer insights. Trust is higher in risk and security-related D&A, yet still only 43 percent voice a high level of confidence in this area. If executives believe that D&A is integral to risk and security, customer insight and business operations, what is driving this lack of confidence?

Our experience suggests that there are likely several drivers. Decision-makers may know that they don’t know enough about analytics to feel confident in their use. They may be suspicious of the motives or capabilities of internal or external experts. They may subconsciously feel that their successful decisions in the past justify a continued use of old sources of data and insight.

Read the report for further insights.

Four anchors of trust

We believe that organisations should take a systematic approach to trust that spans the lifecycle of analytics and is founded on four key anchors of trust: 

  1. Quality. Are the fundamental building blocks of D&A good enough? How well do organisations understand the role of quality in developing and managing tools, data and analytics? 
  2. Effectiveness. Do the analytics work as intended? Can organisations determine the accuracy and utility of the outputs? 
  3. Integrity. Is the D&A being used in an acceptable way? How well-aligned is the organisation with regulations and ethical principles?
  4. Resilience. Are long-term operations optimised? How good is the organisation at ensuring good governance and security throughout the analytics lifecycle?

Read the report to understand the anchors, what the gaps are and how they can be closed. 

Seven recommendations

Seven recommendations to help improve trust throughout the D&A value chain.

There are no roadmaps for driving trust, no software solutions or perfect answers. However, our survey demonstrates that there are best practices and practical examples that all organisations can consider and adopt. Based on our experience, here are seven ideas that should help you create your own approach to building D&A trust.

  1. Start with the basics: assess your trust gaps
  2. Create purpose: clarify and align goals
  3. Raise awareness: increase internal engagement
  4. Build expertise: develop an internal D&A culture and capabilities as your first guardian of trust
  5. Encourage transparency: open the ‘black box’ to a second set of eyes. And a third
  6. Take a 360-degree view: build your ecosystems, portfolios and communities
  7. Be innovative: enable experimentation

For more detail on these ideas read the report.

Data and Analytics

Data and Analytics

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