Gartner: Organizations are Slow to Advance in Data and Analytics
February 12, 2018
Share this

A worldwide survey by Gartner, Inc. showed that 91 percent of organizations 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 organizations should be doing better with data and analytics, given the potential benefits," said Nick Heudecker, Research VP at Gartner. "Organizations 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 survey asked respondents to rate their organizations according to Gartner's five levels of maturity for data and analytics (see Figure 1), and found that 60 percent of respondents worldwide rated themselves in the lowest three levels.


The survey revealed that 48 percent of organizations in Asia Pacific (APAC) reported their data and analytics maturity to be in the top two levels. This compares to 44 percent in North America and just 30 percent in Europe, the Middle East, and Africa (EMEA).

The majority of respondents worldwide assessed themselves at level three (34 percent) or level four (31 percent).

21 percent of respondents were at level two, and 5 percent at the basic level, level one.

Only 9 percent of organizations 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," said Heudecker. "First, focus on improving how people and processes are coordinated inside the organization, and then look at how you enhance your practices with external partners."

Improving process efficiency was by far the most common business problem that organizations 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 joint second most common uses, with 31 percent of respondents listing each issue.

The survey also revealed that, despite a lot of attention around advanced forms of analytics, 64 percent of organizations still consider enterprise reporting and dashboards their most business-critical applications for data and analytics. In the same manner, traditional data sources such as transactional data and logs also continue to dominate, although 46 percent of organizations now report using external data.

"It's easy to get carried away with new technologies such as machine learning and artificial intelligence," added Heudecker. "But traditional forms of analytics and business intelligence remain a crucial part of how organizations are run today, and this is unlikely to change in the near future."

Barriers Preventing Increased Use of Data and Analytics

Organizations reported a broad range of barriers that prevent them from increasing their use of data and analytics. There isn't one clear reason; organizations 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 organizations who are at maturity levels two and three," said Jim Hare, Research VP at Gartner. "As organizational maturity improves to enterprise level and beyond, organizational and funding issues tend to rise."

In terms of infrastructure, on-premises deployments still dominate globally, ranging from 43 to 51 percent of deployments depending on use case. Pure public cloud deployments range from 21 to 25 percent of deployments, while hybrid environments make up between 26 and 32 percent.

"Where the analytics workloads run is based a lot on where the data is generated and stored. Today, most public cloud workloads are new and we won't see the percentage of cloud use rise until legacy workloads migrate en masse," said Hare. "This scenario will happen eventually, but given the extent to which modern data and analytics efforts overwhelmingly use traditional data types stored on-premise, this shift will likely take several years to complete."

Methodology: The Gartner research was conducted via an online survey in the second quarter of 2017 among Gartner Research Circle members — a Gartner-managed panel composed of IT and business leaders — as well as an external sample source. In total, 196 respondents from EMEA, APAC and North America completed the survey. Respondents spanned 13 vertical industry categories, and revenue categories from "less than $100 million" to "$10 billion or more."

Share this

The Latest

October 10, 2019

The requirements of an APM tool are now much more complex than they've ever been. Not only do they need to trace a user transaction across numerous microservices on the same system, but they also need to happen pretty fast ...

October 09, 2019

Performance monitoring is an old problem. As technology has advanced, we've had to evolve how we monitor applications. Initially, performance monitoring largely involved sending ICMP messages to start troubleshooting a down or slow application. Applications have gotten much more complex, so this is no longer enough. Now we need to know not just whether an application is broken, but why it broke. So APM has had to evolve over the years for us to get there. But how did this evolution take place, and what happens next? Let's find out ...

October 08, 2019

There are some IT organizations that are using DevOps methodology but are wary of getting bogged down in ITSM procedures. But without at least some ITSM controls in place, organizations lose their focus on systematic customer engagement, making it harder for them to scale ...

October 07, 2019
OK, I admit it. "Service modeling" is an awkward term, especially when you're trying to frame three rather controversial acronyms in the same overall place: CMDB, CMS and DDM. Nevertheless, that's exactly what we did in EMA's most recent research: <span style="font-style: italic;">Service Modeling in the Age of Cloud and Containers</span>. The goal was to establish a more holistic context for looking at the synergies and differences across all these areas ...
October 03, 2019

If you have deployed a Java application in production, you've probably encountered a situation where the application suddenly starts to take up a large amount of CPU. When this happens, application response becomes sluggish and users begin to complain about slow response. Often the solution to this problem is to restart the application and, lo and behold, the problem goes away — only to reappear a few days later. A key question then is: how to troubleshoot high CPU usage of a Java application? ...

October 02, 2019

Operations are no longer tethered tightly to a main office, as the headquarters-centric model has been retired in favor of a more decentralized enterprise structure. Rather than focus the business around a single location, enterprises are now comprised of a web of remote offices and individuals, where network connectivity has broken down the geographic barriers that in the past limited the availability of talent and resources. Key to the success of the decentralized enterprise model is a new generation of collaboration and communication tools ...

October 01, 2019

To better understand the AI maturity of businesses, Dotscience conducted a survey of 500 industry professionals. Research findings indicate that although enterprises are dedicating significant time and resources towards their AI deployments, many data science and ML teams don't have the adequate tools needed to properly collaborate on, build and deploy AI models efficiently ...

September 30, 2019

Digital transformation, migration to the enterprise cloud and increasing customer demands are creating a surge in IT complexity and the associated costs of managing it. Technical leaders around the world are concerned about the effect this has on IT performance and ultimately, their business according to a new report from Dynatrace, based on an independent global survey of 800 CIOs, Top Challenges for CIOs in a Software-Driven, Hybrid, Multi-Cloud World ...

September 26, 2019

APM tools are your window into your application's performance — its capacity and levels of service. However, traditional APM tools are now struggling due to the mismatch between their specifications and expectations. Modern application architectures are multi-faceted; they contain hybrid components across a variety of on-premise and cloud applications. Modern enterprises often generate data in silos with each outflow having its own data structure. This data comes from several tools over different periods of time. Such diversity in sources, structure, and formats present unique challenges for traditional enterprise tools ...

September 25, 2019

Today's organizations clearly understand the value of digital transformation and its ability to spark innovation. It's surprising that fewer than half of organizations have undertaken a digital transformation project. Workfront has identified five of the top challenges that IT teams face in digital transformation — and how to overcome them ...