A global survey of 196 organisations by Gartner shows 91 per cent of respondents have not yet reached a 'transformational' level of maturity in data and analytics, despite this area being a number one investment priority for CIOs in recent years.
"Most organisations should be doing better with data and analytics, given the potential benefits," says Nick Heudecker, research vice president at Gartner.
"Organisations at transformational levels of maturity enjoy increased agility, better integration with partners and suppliers, and easier use of advanced predictive and prescriptive forms of analytics. This all translates to competitive advantage and differentiation."
The global survey asked respondents - all members of Gartner Research Circle - to assess their organisations according to Gartner's five levels of maturity for data and analytics (see figure below). It found that 60 per cent of respondents worldwide rated themselves in the lowest three levels.
An overview of the maturity model for data and analytics
Explore how location data can provide new insights to better understand and engage customers, or even track assets
The survey revealed that 48 per cent of organisations in Asia Pacific reported their data and analytics maturity to be in the top two levels. This compares to 44 per cent in North America and just 30 per cent in Europe, the Middle East, and Africa (EMEA).
The majority of respondents worldwide assessed themselves at level three (34 per cent) or level four (31 per cent).
Twenty-one per cent of respondents were at level two, and 5 per cent at the basic level, level one.
Gartner says the 21 per cent of respondents at Level 2 maturity means that, despite some bright spots, most organisations are at a moderate level of data and analytics maturity.
Just 9 per cent of organisations surveyed reported themselves at the highest level, level five, where the biggest transformational benefits lie.
"Don't assume that acquiring new technology is essential to reach transformational levels of maturity in data and analytics," says Heudecker. "First, focus on improving how people and processes are coordinated inside the organisation, and then look at how you enhance your practices with external partners."
The research looked through the ‘3Vs’ of big data - volume, variety and velocity - a concept coined by Gartner analyst Doug Laney in 2001.
About 30 per cent of organisations said that they could easily handle data volume and variety, but only 24 per per cent of respondents said they could handle high-velocity data.
Gartner expects the gap between the 3Vs will disappear as organisations gain new skills and deploy infrastructure to handle streaming data.
Improving process efficiency was by far the most common business problem that organisations sought to address with data and analytics, with 54 percent of respondents worldwide marking it in their top three problems. Enhancing customer experience and development of new products were the second most common uses, cited by 31 per cent of respondents.
The survey also revealed that, despite a lot of attention around advanced forms of analytics, 64 per cent of organisations still consider enterprise reporting and dashboards their most business-critical applications for data and analytics.
Similarly, traditional data sources such as transactional data and logs also continue to dominate, although 46 per cent of organisations now report using external data.
"It's easy to get carried away with new technologies such as machine learning and artificial intelligence," says Heudecker. "But traditional forms of analytics and business intelligence remain a crucial part of how organisations are run today, and this is unlikely to change in the near future."
Organisations reported a wide range of barriers that prevent them from increasing their use of data and analytics.
There isn't one clear reason, says Gartner. Organisations tend to experience a different set of issues depending on their geography and current level of maturity.
However, the survey identified the three most common barriers as: defining data and analytics strategy; determining how to get value from projects; and solving risk and governance issues.
"These barriers are consistent with what Gartner hears from client organisations who are at maturity levels two and three," notes Jim Hare, research vice president at Gartner. "As organisational maturity improves to enterprise level and beyond, organisational and funding issues tend to rise."
Consider the cost benefits of switching providers, especially if another provider’s automation capability can significantly improve analysts' productivity
Gartner recommends organisations to focus on establishing a data and analytics strategy that includes building the right culture, starting at the C-level.
“Look to link data and analytics initiatives to strategic company initiatives, such as digital business transformation, where analytics is at the centre,” says Gartner.
It also calls on organisations to avoid being immersed on consolidating data and analytics environments just for the sake of pushing things to the cloud.
“Instead, deploy data and analytics initiatives based on both data gravity (where your data pulls you) and where your business needs will be best met,” says Gartner.
Gartner recommends organisations to add additional context to their data sets by incorporating open or commercial data.
“Explore how location data can provide new insights to better understand and engage customers, or even track assets. Often, the location data readily exists but was ignored because the value of the data was not well-understood.”
Another step is to ask the organisation’s data and analytics providers about their about their plans to add more automation capabilities to their products.
"Consider the cost benefits of switching providers, especially if another provider’s automation capability can significantly improve analysts' productivity,"advises Gartner.
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