HPE study finds most organizations still can’t extract value from the data they have

While the large majority of organizations in the survey agreed it was important for organizations to control their data to extract value from it, few of them did so, with only 3% reaching the desirable highest level of maturity.

Even though the value of data – the new oil – has been trumpeted for some time in the IT community, a large new global study from HPE has found that talk continues to be the rule rather than action. While over 60% of respondents said it was strategically important for their organizations to control their data and the means to create value from data, the average ability to create value from data  was only  2.6 on a five-point scale, and with only 3% reaching the highest maturity level.

“The goal was to find out if organizations are ready to extract value from the data they have,” said Dr. Eng Lim Goh, SVP and CTO for AI at HPE. “8685 decision makers in 19 countries across many industries responded, including the public sector, which was well represented at 15% of the total.” The survey was conducted by YouGov on behalf of HPE.

The survey is based on a maturity model HPE developed that assesses an organization’s ability to create value from data based on strategic, organizational and technological criteria.

“There are five levels of response,” Goh said. “At the highest level, data economics, data strategy is part of corporate strategy, with real-time data push and pull that uses AI and advanced analytics to drive outcomes. Only 3% of organizations met this criteria today. On the other hand, the lowest level, which we call ‘data anarchy’ has each silo is doing its own thing, with no data strategy at a corporate level.” 14% of organizations are at that lowest level of maturity, Level 1.

In between is Level 2, ‘data reporting, where use of data is generally confined to spreadsheets and BI tools, and which is practised by 29% of organizations. 37% percent are on level 3, ‘data insights’, and 17% are on level 4, ‘data centricity’.

“The average level across the world is 2.6,” Goh said. “Above 300 employees, the average is 3.0, while the average is 2.3 for organizations below 250 employees.”

Other metrics from the study indicated that data strategy is not a key part of corporate strategy (87%), there is no strategic focus on data-driven products and services (72%), there is no cross-organizational budget for data initiatives (70%) and there is no machine learning or deep learning but only the use of spreadsheets or canned reporting and BI (48%).

“These data tell us that there’s a lot of work to be done,” Goh said. “Only 8% of the respondents say that they can unify all data in real time. Data value creation requires unified data access across the edge to the cloud.”

Goh also pointed out that these data also fly in the face of the respondents’ own views about the importance of control of the data to properly extract value from it.

“How important is control over the data?” he asked. “28% strongly agree, 34% agree and 22% somewhat agree that control is an important factor to extract value from data. Lack of control hurts the ability to get value from data.”

This is reflected in data showing that 34% of respondents have no overarching data and analytics architecture at all, with data being isolated in individual applications or locations. Only 19% have implemented a central data hub or fabric that provides unified access to real-time data across their organization, and another 8% say this data hub also includes external data sources.

“Organizations must put data at the centre of their digital transformation strategy, and this requires a hybrid edge-to-cloud architecture,” Goh concluded.