How does trusted data help you realize transformation?

As the transformation agenda accelerates, leaders must put the data underpinning key decisions to the trust test.

In brief

• In a post-pandemic working world, businesses face new urgency to transform business models and operating practices.
• Leaders must be confident they can trust the data underpinning critical decisions driving change programs.
• Key questions can help the C-suite put Trusted Intelligence at the heart of transformation.

Every business leader knows the importance of data-driven decision making. But have you considered how data itself is driven through your organization — and how this journey can embed or erode trust in its insights? If you haven’t, you may be unknowingly making crucial decisions based on tainted data rather than the verified, Trusted Intelligence critical to guiding sustainable change and creating long-term value. 

What you don’t know can hurt you

Of course, no leader knowingly uses poor quality data. The problem is it’s not always obvious, at least not at first. Leaders may assume the data they base critical decisions on is to be trusted. But is it?

Let’s consider the journey data typically makes through a company before it reaches the C-suite. It’s generated in one part of the business and often cycled across several departments and multiple hands before reaching leadership. Perhaps, along the way, someone applies the data in a way that it wasn’t designed for. Bias may have been unintentionally introduced. Questions may be raised (but never really resolved) about whether those who owned this data consented to its use.

By the time it reaches the CEO, some of the data may have been excluded, so they only see half the picture (and one that’s been edited, at that). And all of this is before we even consider instances of deliberate data manipulation, or malicious spread of fraudulent information.

This complicated data journey highlights the dilemma businesses face today is not around accessing information — new technologies generate mountains of data every second. The big challenge is to be certain data is accurate, verified and compliant. That’s simply critical if leaders are to be confident of the decisions underpinning transformation programs, and be ready to mitigate against risks.

Otherwise, negative consequences quickly grow and spread once flawed data embeds itself into the decision-making process. Executives may build the incorrect business case for change. A lack of trust in data can deter collaborators, making it harder to solve complex problems and create more innovative products. 

For example, Microsoft’s X-box gaming system is beloved by 1.7 billion consumers but a siloed, manual system of payments to developers threatened to undermine trust within the ecosystem that drives its success. When an EY team worked with Microsoft to develop a transparent blockchain-based solution to the problem, developers could access royalty statements in just four minutes, rather than 45 days, enhancing trust and driving faster innovation of the platform.

Without evidence that holds up to scrutiny, leaders may also struggle to win over their teams. Why do we need to redesign our customer experience? Or use a new IT system? Internal resistance is a major reason transformation fails. The solution? Trusted Intelligence.

Does your data pass the trust test?

This ability to trust the data driving decisions has always been important. Yet it assumes fresh urgency as the transformation agenda accelerates post-COVID. Many operating models were under pressure before, but the pandemic brought some completely undone.

As organizations act fast to make changes, they need to ensure the decisions they make will set them on the right path. At EY, we talk about Transformation Realized — an approach to making enterprise-wide changes that create real long-term value and sustainable growth. It’s based on the belief that value flows from three key drivers — putting humans at center; implementing technology at speed; and innovating at scale.

Put simply, successful transformations must be driven by a desire to improve the human experience, apply innovation to unlock value in new ways and be enabled by the right technology. And trusted, intelligent data must underpin all of these.

Consider this global cycling example. Cycling was a sport with a monetization problem, and a trust gap created through high-profile doping incidences that hindered efforts to solve it. EY with a consortium of professional cycling teams worked to develop an Internet of Things solution to capture vast amounts of real-time, in-race data points from cyclists and aggregate them in a dedicated app delivering a world-first, immersive digital experience to fans.

The solution — backed by transparent, verified, Trusted Intelligence — not only provided new revenue for cycling, but brought much-needed credibility to the sport. And in addition to an immediate pay off, the potential is even stronger for creating greater value over the longer-term.

This experience is a reminder that credible, sustainable transformation starts with first putting the data driving it to the test. Because if your transformation is driven by data, you need to ensure you can trust it to take you where you need to go. 

Key questions for boards and leadership to consider

• How confident are you that your data is:
  • Verified and accurate?
  • Immutable and free of bias?
  • Relevant and contextually complete?
  • Stored, used and reused in compliance with all laws and regulations?
• If unsure, where are the weak points in your data processes?
  • Technology and processes: Is your data governance based on scientific processes (rather than human judgement) and supported by appropriate technology such as automation and algorithms? Can you follow the path of data through the organization?
  • People: Do you have the skills to manage and interpret data? Recruiting the right talent such as data scientists can help translate complex data into tangible business actions. More important though is to make data front and center in the C-suite through appointing a Chief Data Officer (CDO). A CDO takes responsibility for embedding data across the organization – overseeing the governance that ensures data quality and working closely with the CIO and CTO to scale data and technology at speed.
  • Innovation: Are you frustrated that innovation programs don’t achieve a return on investment? Without Trusted Intelligence behind them, change initiatives are often misdirected or undermined by fatal flaws. Rigorous processes, a human-centered approach and strong data leadership are the secret to successful transformation.