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Oracle survey - losses from bad data management

Thursday, January 17, 2013

Oracle asked oil and gas 'C level' executives how much additional revenue they thought they would be able to capture, if they were better at working with big data


Oracle Corporation conducted a survey of "C-level" executives from US and Canada oil and gas companies to ask them how well they thought they were managing and capitalising on the data their companies gather, and at what cost.

Oil and gas respondents were asked to estimate the revenue that they fail to capture as a result of challenges in managing their big data, as a percentage of their total current revenue.

Oil and gas respondents estimated that they were unable to capture 22 per cent of additional revenue per year, which works out at an average of $103.6m per year, by not being able to fully leverage the information they collect.

The average for the entire survey, where oil and gas was just one of 11 industries surveyed, was 13 per cent of additional revenue which could not be capture.

When asked to grade themselves on how well they are managing the information on A, B, C, D or F (for 'fail'), 13 per cent of oil company respondents gave themselves A, 54 per cent said C or below, 27 per cent said D or F.

When the oil and gas industry responses were compared to other industries surveyed, the oil and gas industry ranked 4th out of 11 industry sectors in the percentage of respondents who said that they would score themselves D or F in "preparedness for a data deluge'.

Consumer goods industries said they were most prepared, followed by communications, financial services, oil and gas, life sciences, retail, airlines, manufacturing, utilities, healthcare, and public sector. In the public sector 41 per cent scored themselves D or F.

74 per cent of oil and gas respondents said their organisation is collecting more information today than 2 years ago, and by an average of 96 per cent more information.

For all 11 industries surveyed, 94 per cent said their organisation is collecting and business more business information today than 2 years ago, by an average of 86 per cent more, with the biggest growth coming in customer information, operations, sales and marketing.

When asked if they are frustrated by the organisation's data gathering and distribution capabilities, 32 per cent of oil and gas respondents said they were unable to give their business managers access to the pertinent information they need without IT team support.

29 percent do not feel they have the right systems in place and 23 percent feel they are using systems that are not designed to meet the unique needs of their industry.

Software applications

Oil and gas executives see room for improvement in their industry-specific software applications, with 36 percent of executives looking for more industry-specific project management applications, 32 percent seeking more industry-specific regulatory compliance software and, for the oil field service and downstream sectors, 26 percent are seeking customer relationship management platforms more specific to their industry needs.

Oil and gas executives note that they are making the best use of their data in the areas of financial management (42 percent), production (36 percent) and distribution (26 percent).

The biggest data struggle in the areas of safety (26 percent), project management (23 percent), maintenance/asset management (16 percent) and geological/seismic exploration (16 percent), and for the downstream and oil field service sectors only, market intelligence (26 percent) are the areas in which they are struggling most with their data. Thirteen percent of executives noted they were not struggling with data in any area.

Top priorities include direct access for business managers to business critical information (48 percent), improved training for employees to better make sense of information (32 percent) and acquiring tools to collect more accurate information (32 percent).

The survey was called "From Overload to Impact: An Industry Scorecard on Big Data Business Challenges'. Altogether 333 US and Canadian 'C-level' executives from 11 different industries were surveyed.


Solving the problem

Hossam Farid, vice president oil and gas Industry, Oracle Corporation, emphasises that the 'revenue unable to capture' figure is not about financial losses, but additional benefits which executives believe they could get from the data, if they were on top of it.

One of the biggest obstacles to managing data is the fact that many companies use many different software tools to work with data and they do not integrate, he says.

'For decades, oil and gas companies have been using myriads of product and services to collect, store and process data.

'Data management policies have also been subject to swinging strategies between in-house ownership in massive data centres, and outsourced service to external service contractors.'

'Our ability to generate data [overwhelms] our ability to store it to take full advantage of it, which in fact makes Big Data a liability for many organizations,' he says.

'Our ability to integrate the different pieces of the jigsaw is hampered by the lack of standards and technology openness, making the 360-degree view of the business nothing but a dream for many companies.'

'Our ability to analyze and respond to changing business conditions is still influenced by the rear-view-mirror approach and hampered by lack of tools and technologies, resulting in creating a perception of hard-to-manage, particularly in the case of real-time data.'

As an example, he says, consider that well site data acquisition service providers typically offer proprietary viewer applications to monitor real-time drilling data.

Such viewers work directly off data storage designed and built based on the proprietary technology of each provider.

'In a typical drilling environment where many data acquisition companies are simultaneously involved, the operator's geotechnical teams have to be familiar with each viewer in use, and have to devise different data management and storage strategies for each data type,' he says.

It 'adds more complexity and burden to their daily work, increasing potential risk issues and undermining operational excellence initiatives to reduce operational expenditure and non productive time.'



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