Data is an enterprise’s most valuable asset. Quality data gives companies a competitive edge. It also drives the development of new products and services, but only when organizations can fully utilize it. Today, however, data access challenges make it harder and harder for them to reach their treasure trove of data. Cybersecurity concerns, government regulations, and data governance all prompt organizations to lock down this precious resource tighter and tighter. As a result, businesses increasingly risk leaving key growth insights on the table.
Bloor Research surveyed 100 data leaders in the US and Europe. Sixty percent of them could not use more than 40 percent of their data because of privacy concerns. As for the rest of the data, 84 percent responded they could eventually access it within a week.
What is causing these data access challenges? The State of Data Analytics: Key Challenges in a Strict Security and Privacy Environment surveyed 100 leaders in the US, France, UK, and Germany. Those leaders cited cybersecurity as a key roadblock to data accessibility. In addition, 67 percent of respondents said governance mandates restricted access to useful data. Another 61.2 percent said data protection reduced the value of their data. Finally, 56.6 percent noted that complex, ad hoc, or manual data access processes created challenges.
Opportunity Costs of Data Deprivation
Useful data is key for future proofing any business today, McKinsey recently reported. “Executives in every industry know that data is important. Without it, there can be no digital transformation to propel the organization past competitors. There are no analytics driving new sources of revenue,” the report continued. “Even running the basic business well isn’t possible.”
However, organizations increasingly struggle to strike a balance. They must make data accessible while keeping proprietary data, confidential resources, and customer personal identifying information safe and compliant. So what do companies lose when data access challenges tie up nearly half of their data in a morass of protection?
The opportunity costs of underutilizing data can be significant. In the Bloor Research survey, leaders most often cited competitive advantage as their reason for using data (56%). Meanwhile, 49 percent said relevant data is key for finding ways to reduce costs. Another 46 percent cited improving efficiency. Finally, 40 percent said data analysis propels the development of new products, services, and revenue streams.
Companies lose more than the insights data provides. They also waste resources trying to access the data and make it useful for analysis. For example, respondents to McKinsey’s 2019 Global Data Transformation Survey reported a figure of 30 percent. That is the share of total enterprise time spent on non-value-added tasks because of poor data quality and data access challenges.
Data Governance Gone Wrong
In the Bloor survey, 70 percent of respondents said they currently have, or plan to invest in, a data privacy solution within the next year. The key, of course, is choosing protection that does not create more impenetrable data prisons. Instead, it should ensure data is a value-added commodity for their organizations.
Quality data governance assures that data is relevant and readily available, McKinsey noted. “The problem is that most governance programs today are ineffective.”
Companies must protect customer information, dodge data breaches, and comply with ever evolving regulatory requirements. Otherwise they face the high cost of data landing in the wrong hands, and of cybercriminals holding the company hostage. Therefore data protection that also provides easy accessibility is a necessity. Only then can organizations use their most valuable asset to its full potential.
Breaking Through Data Access Challenges
Data governance is essential to consistent and proper data handling. It also establishes where specific data exists within the organization. Building reliable governance means ensuring high data quality across the entire data lifecycle. That includes data controls that support business objectives: where data originated, where it is going, and who is using it.
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