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Oil and gas companies are struggling with data integration. Is analytics the answer? What steps can companies take to turn data into insight and action? This report provides insights from a survey of energy companies and provides a roadmap on how to create an analytically powered organization.
Energy is an industry dominated by engineers and scientists, working in disciplines that embrace facts and figures to reach conclusions and make informed decisions. Yet a recent Accenture survey of analytics practitioners indicates that only one in five energy-industry respondents report using an integrated, organization wide approach to analytics.
With the rise of big data and a wide range of new technologies, analytics have reached the tipping point.
This report explores the barriers blocking companies from generating improved outcomes from analytics and provides case studies of how organizations have leveraged analytics for tangible gains. It also offers a road map to gauge maturity on the journey to becoming a business where analytics drive competitive essence.
Energy companies have been measuring and monitoring production for years, using sensors and machine-to-machine communications. Many tools to boost performance, however, were not designed for analytical optimization. In addition, ad-hoc adoption has led to bolt-on tools and standalone analytics, which have not been integrated with the overall enterprise architecture.
To better understand progress to date, Accenture surveyed 35 analytics practitioners in oil and gas companies as part of a global research effort interviewing 600 executives in total across multiple industries. The survey addressed questions such as:
Summary of key challenges with analytics in oil and gas companies:
Four major technology developments are creating a tipping point, with new possibilities to enable faster, smarter business decisions:
Convergence of information technology (IT) and operations technology (OT)Data from machines is generated, captured and integrated into IT systems for analysis, often in real time.
Mobility and technology consumerizationMobility and user-friendly IT provide remote access to data, affording improved visibility and faster response.
Disruptive architectures, including cloud computingCloud provides cost-effective options to access large-scale computing and storage capability, as well as tools, all essential for analytics. Also, "on demand"is reshaping the IT operations model with the option for analytics-as-a-service.
Big data analytics and in-memory computingThe application of advanced analytic techniques to very large data sets isaided by in-memory databases that greatly reduce query time.
Three recommendations for becoming analytically-powered:
Visualize the value and design for analytics outcomes
Adopt an end-to-end process view, integrating enterprise and operations analytics
Promote a cultural shift to an analytically astute, insight-driven enterprise
Contact our authors to discuss your Analytics Journey:
Jeffrey MiersManaging Director, Energy—Analytics, North America
Kevin DonaldsonManaging Director, Energy—Analytics, Europe, Africa and Latin America
Senthil RamaniManaging Director, Analytics—Technology, Asia Pacific
Richard HolsmanManaging Director, Energy Technology Lead
December 3, 2013
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