A lack of comprehensive data strategies among Global 2000 enterprises is curtailing use of AI tools and undermining business goals, according to research.
Nearly 85 percent of enterprise leaders agree that effective data management significantly drives top line, bottom line, and shareholder value, but they believe “over 40 percent” of their organizational data is “unusable.” This junk data is either “not trusted,” “lacks quality,” hasn’t been updated, or is inaccurate, duplicated, or “inconsistent.”
Improving operational data availability to integrate AI tools is emerging as the “number one” challenge for supporting overall AI technologies, among top execs, with unified data management deemed “critical.”
Analyst house HFS Research, commissioned by enterprise data management firm Syniti, compiled the report: “Don’t drown in data debt, champion your data first culture.” For the above findings in the report, more than 300 Global 2000 business leaders across different industries were interviewed, to find out how their organisations are trying to navigate a complex data management landscape.
“Data debt” can include outdated data structures, poorly documented data sources, inefficient data processing, and improperly secured data.
The report 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 one set of business outcomes.
- Data and AI have a chicken-and-egg relationship. You need to address both together. Better data management is the number one initiative to leverage AI capabilities better.
- Measure the impact of bad data – it’s critical to reducing your data debt. Less than 40 percent of organizations interviewed have methods and metrics in place to quantify the impact of bad data.
- Data is a huge people issue. The shortage of specialized talent is one of the top three challenges in data management.
- Professional services need to be reframed as business data services, with a focus on outcomes, not effort. Nearly 90 percent 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.
“We are now at an inflection point in the evolution of data skills, from generalists to specialists. Data work is unique and complex and requires 100 percent dedicated focus to build specialized skills, training and needed career paths,” said Kevin Campbell, CEO of Syniti. “To achieve real, tangible business benefits from your data, you need skilled data specialists who understand data in context, not business generalists or developers.”
Phil Fersht, CEO and chief analyst at HFS Research, added: “Many business leaders still take a back seat when it comes to 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.”
