Data Debt Emerges as Core Business Issue for Enterprises
A new report finds that nearly 85% of enterprise leaders agree that effective data management significantly drives top-line, bottom-line, and shareholder value.
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A lack of comprehensive data strategies and data debt among Global 2000 enterprises is curtailing the use of AI tools and undermining business goals, according to HFS Research Don’t Drown in Data Debt; Champion Your Data First Culture.
In partnership with Syniti, the report interviewed over 300 Global 2000 business leaders across industries to study how organizations are navigating a complex landscape of data management challenges and how those hurdles could impede their ability to fully leverage operational efficiency and drive business growth.
The report revealed that nearly 85% of enterprise leaders agree that effective data management significantly increases top-line, bottom-line, and shareholder value. Meanwhile, enterprises perceive that over 40% of their organizational data is unusable and either untrustworthy, lacks quality, outdated, inaccurate, duplicated, or inconsistent.
Additionally, the report found that improving operational data availability to integrate AI tools is emerging as the #1 challenge in implementing AI technologies. Enterprises believe that unified data management is critical. Aligning data initiatives with business goals reduces inefficiencies and maximizes data utility.
The report recommends that enterprises adopt a Data First culture, implement comprehensive data management strategies, and shift towards outcome-driven partnerships with service providers to prevail.
The report specifically recommends five strategic principles that will enable meaningful progress in addressing data debt and championing a Data First culture:
- Data isn’t just IT’s problem; it’s a core business issue. The strategic goal for data management is to facilitate seamless end-to-end business processes, supporting the “OneOffice” experience, where people, intelligence, processes, and infrastructure come together as one integrated unit with unified business outcomes.
- Data and AI have a chicken-and-egg relationship. You need to address both together. Better data management emerges as the #1 initiative to leverage AI capabilities better.
- Measure the impact of bad data; it’s critical to reducing your data debt. Less than 40% of organizations interviewed have methods and metrics to quantify bad data’s impact on their organizations.
- Data is a huge people issue. The shortage of specialized talent is one of the top 3 challenges in data management.
- Professional services need to be reframed as business data services—focusing on outcomes, not effort. Nearly 90% of enterprises rely on third-party providers for data initiatives. However, focusing on effort rather than results leads to inefficiencies. Enterprises must demand providers prioritize meaningful results to drive true value.
“This research proves what we have believed for some time, that the fundamental problem with past data approaches is in the skills needed and applied,” said Kevin Campbell, CEO of Syniti. “We are now at an inflection point in the evolution from generalists to specialists; data work is unique and complex and requires 100% dedicated focus to build specialized skills, training, and needed career paths.”
“To achieve real, tangible business benefits from your data, you need skilled data specialists who understand data in context – not business generalists or developers. It’s also gratifying to see this research validate that our Data First approach is crucial to driving successful transformations, whether that’s achieving the benefits of applying GenAI or transforming the underlying business functions and systems,” added Campbell
“Our research proves that a Data First culture means data isn’t just IT’s problem; it’s a core business issue. Many business leaders still take a backseat when setting key data objectives, causing data to remain siloed across departments and resulting in misaligned expectations across IT and business professionals. The focus for enterprise leaders must be on developing strategic talent that understands the business context behind the data,” said Phil Fersht, CEO and Chief Analyst of HFS Research.
