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.
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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.
Summary
In a working world changed forever, transformation is no longer optional. But as businesses make fundamental decisions about their future direction, is the data behind these decisions sending them down the wrong path? Leaders have access to more information than ever, but data’s journey from ingestion to implementation can erode its value and trust in the decisions it underpins.