The U.S. energy opportunity: Technology's role

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Grant Thorton LLP 2014 survey of upstream U.S. oil and gas companiesDownload the full report (PDF).

Energy companies often generate a high volume of quality data, but managers need better information management to glean the kinds of insights that can strategically support the business.

As geo and seismic systems have advanced in their ability to enable field personnel to evaluate production sites, the collection and management of that information has remained a challenge to many IT groups. Additionally, focus is shifting from core accounting and transactional systems to large scale analytical capabilities and business insight reporting.

Examples of energy company information needs Energy companies need insights on a variety of fronts, including:
  1. Portfolio management. Energy companies face challenges when making certain investments work (e.g., the expansion into natural gas). Information management can help clients remain agile in an uncertain environment.
  2. Cost management. Understanding the relationship between operations and maintenance, general and administrative expense and other myriad costs associated with an enterprise is key to creating maximum value for clients. Peer measurement can assist in this effort.
  3. Margin management.Managing complex funding hedges, production sharing contracts and direct costs are areas of unrealized opportunity for the industry.
  4. Capital management.Energy companies are highly capitalized and rely on long-term projects and outlooks. Creating an effective project management process and set of systems to support capital management are vital. To gain insights, companies need to invest in systems that:
  • Integrate volumetric and operational data with financial data
  •  Reduce/eliminate data reconciliation between systems
  • Integrate financial-driven hierarchies with operational reporting 
  • Provide a data warehouse 
  • Establish risks and controls 
  • Enable data governance 
  • Include IFRS and GAAP reporting requirements
  • Identify differences and uses of Enterprise Performance Management Architect with Data Relationship Modeling 
  • Enable working capital and profitability analytics