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The oil and gas industry joined food service, retail, and other sectors in facing unprecedented challenges over the past few months, but even beyond the impact generated by the almost overnight destruction of energy demand by the COVID-19 pandemic, oil and gas and energy companies also had to deal with a price war that resulted in a historic drop on April 20th, when crude oil was being traded in the negatives.
While there has been a small rebound since, oil and gas producers have a long road ahead in terms of an economic recovery, while also grappling with operating remotely, a phenomenon that was rare for the industry just six months ago. We sponsored our own research, polling 400-plus IT decision-makers (ITDMs) in other industries as well as oil and gas decision-makers (O&GDMs), and found that while more than a third of O&GDMs polled say their industry lags others in technology, nearly all admit that companies that don’t embrace tech advances will not succeed. These companies are now facing the importance of accelerating their digital transformation while striving for a solid data analytics strategy and the adoption of AI to drive workflow automation. This will require significant investment in streamlining data measurement and collection and storage, along with platforms for delivery, visualization, and analysis. In order to do so effectively, companies in the oil and gas and energy sectors should follow three best practices.
Optimize Your Analytics Tech Stack
Arguably the most important aspect of a Data Management strategy is the ability to visualize insights easily and seamlessly. There is a lot of opportunity in oil and gas for further investment, and this is where, in particular, important lessons can be learned from other industries such as finance, transportation, and healthcare.
Beyond its capacity to improve understanding of field asset performance to find better ways of producing, processing, or transporting oil, gas, and byproducts, data has the ability to cut down on manual processes that block progress and can, as a result, save costs and reduce errors and lead to workflow automation. Being able to predict problems and address them before they occur is a huge benefit in terms of cost reduction as well.
Invest in a Single Source of Truth
IT leaders — across industries — agree that having access to consistent insights at all stages of the business lifecycle is critically important. Within the oil and gas industry, it is even more imperative given the proliferation of different data silos within distinct functional units and limited common governance across them.
Establishing a strong foundation of Master Data Management (MDM) and business knowledge integration provides the platform for visualization, analytics, and workflow automation. This enables experienced personnel to spend the majority of their time using the data rather than cleaning it up, leading to innovative solutions to drive operational efficiency.
Embrace the Cloud
In today’s volatile energy industry, the need for cost-saving efficiencies and immediate access to information and insight has never been greater. The key to a long-term fix for this is to take your Data Management strategy one step further — and migrate to the cloud. The benefits are comprehensive; companies that use cloud technology achieve workplace efficiencies and avoid interruption via faster deployment and easier ongoing support. Additionally, because cloud applications share resources, scaling based on fluctuating market conditions is more economical.
Migrating to the cloud also marks the final stage of breaking down siloes in your data, as cloud applications enable company-wide collaboration by providing cross-department access to centralized information to help users make informed decisions.
Companies in the oil and gas industry that will not just survive the current challenges but establish a platform for future growth are the ones that treat data as crucial to their future, not just their recovery. If used correctly, a sound Data Management strategy has the capacity to lower risk, accelerate decision-making, and automate critical workflows.