Building trust in analytics | KPMG | BE

Building trust in analytics

Building trust in analytics

Data and Analytics (D&A) holds the power to unlock untold value. It can be used to manage risks, costs and growth. However, it appears that today’s organizations’ lack confidence in generating trusted insights from D&A. Mainly gaps in capabilities around quality, effectiveness, integrity and resilience drive the cycle of mistrust. In order to address this fundamental challenge, seven recommendations are formulated for building trust in D&A — a continuous endeavor that should span the D&A lifecycle from data through to insights and ultimately to generating value.

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Director, Technology Advisory

KPMG in Belgium

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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, particularly in areas that drive new growth. First of all, D&A helps to better understand customers, as it is integral to understand how products are used, who your existing customers are and which new products and services you should develop. Furthermore, D&A could be useful to improve productivity, by giving insight in business performances, how to drive process and cost efficiency and how to drive strategy and change. Lastly, insights from D&A can also help to manage risk, fraud and compliance.

On the contrary, there are clear commercial risks if customers, investors or regulators do not believe D&A is being used in a way that is considered valuable or appropriate. This survey, with replies received from 2,165 decision-makers representing companies with at least 500 employees, for example shows that 70% of the respondents agree that by using data and analytics, they expose themselves to reputational risk (e.g. data breaches, mis-selling of products and services).

The trust gap

Given the power that it holds, trust in D&A should be a non-negotiable 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.

Moreover, our survey found that trust varies across the D&A lifecycle. Interestingly, trust is strongest at the beginning of the cycle (at the data sourcing stage), but falls apart when it comes to implementation and the measurement of its ultimate effectiveness. This means that organizations are unable to attribute the effectiveness of D&A to business outcomes which, in turn, creates a cycle of mistrust that reverberates down into future analytical investments and their perceived returns. Furthermore, we also compared organizations with different levels of D&A maturity to investigate whether greater maturity seems to increase trust or indeed whether trust drops when faced with the realities of complex D&A implementation. Despite different levels of investment, our survey suggests that more sophisticated D&A tools do little to enhance trust across the analytics lifecycle. The trust gap cannot be closed by simply investing in better technology.

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 context, we define four ‘anchors of trust’ which underpin trusted analytics:

  • Quality: In order to drive quality in D&A, organizations need to ensure that both the inputs and development processes for D&A meet the quality standards that are appropriate for the context in which the analytics will be used.
  • Effectiveness: When it comes to D&A, effectiveness is all about real-world performance. It means that the outputs of models work as intended and deliver value to the organization.
  • Integrity: In the context of trusted analytics, we use this term to refer to the acceptable use of D&A, from compliance with regulations and laws such as data privacy through to less clear issues surrounding the ethical use of D&A such as profiling.
  • Resilience: Resilience in this context is about optimization for the long term in the face of challenges and changes. Cyber security is the best-known issue here, but resilience is broader than information security. Failure of this trust anchor undermines all the previous three.

We believe that each anchor of trust is relevant throughout the D&A lifecycle, from data sourcing, to data preparation and blending, to analysis and modeling, to usage and deployment and finally through to measuring effectiveness and back to the beginning of the cycle.

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 organizations 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:

  • Get the basics of D&A trust right: assess your trust gaps and identify priorities
  • Purpose: clarify and align goals, measure performance and impact
  • Raise awareness: increase internal engagement
  • Expertise: build internal D&A culture and capabilities as your first guardian trust
  • Transparency: open the ‘black box’ to a second set of eyes – and a third
  • 360 degree view: look at ecosystems, portfolio’s, and communities
  • Innovation: enable experimentation, build an innovation lab

 

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.

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