New evidence is emerging that organizations across many industries are simply not ready for the challenges of big data. Oracle has released two new reports that add hard numbers to mounting concerns about the problems big companies face when dealing with data.
This week’s report from Oracle polled 333 North American executives to find out how their companies and organizations are handling the onslaught of big data, both in terms of setting up big data infrastructure and then properly analyzing the data once they have it gathered.
The results do not exactly paint a shining picture of readiness. While 94% of the executives surveyed indicated that their organizations were collecting and managing more data today than they were two years ago, most of those same executives gave themselves less-than-stellar grades on how prepared they were to deal with that data.
In fact, a similar percentage – 93% – of those same execs “believe their organization is losing revenue as a result of not being able to fully leverage the information they collect,” the report stated. Private-sector organizations with $1 billion or more in revenue reported that they believe they are losing an average of $130 million annually because of the mishandling of data.
Bad News for Big Bureaucracies
Breaking it down by industry, the results of the survey revealed that the public sector, health care and utilities sectors gave themselves the worst marks, with 41%, 40% and 39% of executives in those sectors giving themselves a D or F for preparedness, respectively.
The number one problem? Translating information into actionable intelligence, with almost half (48%) of respondents giving themselves a C or lower for this problem.
These numbers reflect what many in the data management and analytics industry are increasingly pointing out: Many big companies are starting to build data gathering and storage infrastructures, but they don’t know what to do with the data once they have it.
“A lot of companies don’t know how to find data scientists and don’t understand data science,” Kaggle President Jeremy Howard told me in an interview last week. “These enterprise companies can’t implement a proper data analytical solution because they have no data talent.”
This latest report from Oracle seems to confirm Howard’s hypothesis, but another report from Oracle, released July 10, highlights additional problems organizations may have working with all this data.
Utilities Have Special Problems
Oracle’s earlier report centers specifically on the utilities industry and explains how even though utilities using smart meters are seeing 180 times more data than similar organizations that haven’t adopted smart meters, those same utility companies rate themselves at just 6.7 on a 10-point scale for data readiness.
As with the enterprise-level organizations in other industries, the utility execs also ranked lack of talent and being able to visualize and comprehend data as the top two problems holding them back.
But core management issues also play a big factor. When polled on who owned smart meter data, the utility company respondents gave a wide range of answers – from the metering department to the business analysts. That confusion demonstrates that many of these companies still don’t have a unified data management strategy and are instead confining data in silos where it has limited value.
On a smaller scale, the studies show that utilities, which are being called on to implement smart grid technology to better manage power distribution – are still behind on gathering end user information. And that could end up being a critical hold-up for any sort of elastic/smart grid power system.
On a broader scale, a lack of talent and understanding of what data can bring to the organization is hobbling companies in a variety of industries. That hurts the companies, but it could also set up big data for failure if they can’t achieve the concept’s promised benefits.
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