Commissioned by Informatica, the IDC CDO study, Driving Business Value from Data in the Face of Fragmentation and Complexity, surveyed more than 899 members of the office of the CDO, across 10 countries including Australia, France, Germany, Japan, the UK and the US, to discover some of the challenges and priorities of the Chief Data Officer.
Informatica, an enterprise cloud data management leader, has announced the findings from the second annual IDC Global Survey of the Office of the Chief Data Officer (CDO) examining the CDO’s challenges, priorities and key performance indicators while stewarding enterprises to success in a digital-first world.
“The changemakers of tomorrow in Digital Transformation will have to move beyond just data integration to data intelligence, but 37% of data leaders are spending most of their time grappling with data complexity as opposed to driving true transformation with data,” said Jitesh Ghai, Chief Product Officer, Informatica. “This year’s annual CDO study reveals that data fragmentation will be the biggest barrier facing data leaders next year, and the key characteristics of those leading data-led transformations and achieving business value versus those that are still struggling to make sense of all their data.”
Three key themes from the 2021 Global CDO study include:
Data fragmentation and complexity distract from innovation
Enterprise infrastructure will be cloud-first and multi-hybrid for many years, with systems spread across on-premise and multi-cloud environments. The findings showed that:
- Nearly 80% of organisations surveyed store more than half of their data in hybrid and multi-cloud infrastructures
- 79% of organisations are using more than 100 data sources, with 30% using more than 1,000 sources
- 37% of data leaders are barely keeping the lights on when it comes to data management as opposed to driving strategy or innovation with data
But it is this fragmentation, with data spread across multiple sources and many clouds, that is making it much more difficult to discover, manage and derive intelligence from the data. Highlighting the chasm in delivering business value between data leaders and laggards, the study found that enterprises with a high level of data maturity generate 250% more business value than those only beginning their data-led transformations, where most of the time in data management is spent keeping the lights on.
Operationalising AI to automate data management is critical to success
Only AI can deliver the speed and scalability demanded by modern enterprises and the study found that data-mature organisations were 3x better at operationalising AI to automate data management activities than their less mature peers.
- Innovation with data starts with enabling access, yet only 31% of organisations provide AI-powered self-service access to all the data needed by different teams
- Organisations in APAC lead the way with 37% automating data management across the business
- North American organisations follow closely behind with 33% and EMEA businesses slower to adopt automation with only 25% deploying it in all areas of the organisation.
Data leaders were also seen to be leveraging AI-driven insights and process optimisation to improve efficiency as well as the availability and use of data to users within the business.
Cloud-centric models and integrated data management approaches
The study highlighted how critical data management is to Digital Transformation, noting that organisations with strong data leadership are 3x more likely to be well underway with Digital Transformation. With cloud central to that, migrating to the cloud was a primary objective for 34% of respondents.
- Over the past year, most organisations increased the data functionality hosted in the cloud by 10-20%. However, a quarter of EMEA and North America enterprises saw a 30% uptick.
- This momentum is set to continue, with 30% of organisations noting that migrating data management functions to the cloud is a priority.
- 75% of organisations don’t yet have a complete architecture in place to manage an end-to-end set of data activities including integration, access, governance and protection.
The way organisations resolve fragmentation and complexity issues separates leaders from laggards, with leaders adopting an integrated approach to data management with standardisation and automation as core facets.
