Delivering on the Promise of Value:
Operationalizing Digital Transformation Strategies
for the Post-Pandemic Era – Part 2
In part 1 of our series, I highlighted how the oil and gas industry is clawing its way back towards resilient profitability as it continues to face multi-faceted challenges despite quickly rising oil and gas prices. We also began to explore the critical role that digital transformation will play in unlocking the next wave of efficiencies and achieving concrete progress on the Energy Transition journey.
Our experience, working with industry leaders to achieve their digital transformation aspirations, over the last five years, has highlighted the fact that key priorities needed to be revisited to reflect the challenges faced, new opportunities encountered and the impact of new digital technologies, as well as having to consider the overall impact of COVID19 to the ways of working (what works gets done, where it gets done and how it gets done). Looking forward, the industry needs to focus on five key elements within the digital transformation framework to extract meaningful value. In part 1 of the series we focused on the digital strategy & business model element:
Let’s now dive into each of the remaining elements, starting with oil and gas (O&G) operations.
O&G Operations: Operations continues to be the area with the most value to be unlocked, and remains a digital transformation focus as relevant and necessary today as it was in the “first wave”. But while the focus on operations has not changed, the elements needed to create a compelling value proposition have evolved, and there are three areas where digital can help companies unlock significant most value in operations in the post-pandemic era:
- Core Process Automation: Deploying technology and applications to simplify archaic and siloed workflows. AI-powered Robotic Process Automation (RBA) is a recent powerful example of how operators have deployed technology to automate some core processes within operations and across finance and cross-functional workflows.
- Cognitive Reasoning: Designing and deploying Artificial Intelligence (AI) or Machine Learning (ML) algorithms to advance the analytics capabilities beyond descriptive (what happened) and diagnostic (why did it happen) to predictive (what is likely to happen), prescriptive (what needs to be done) and cognitive (how should it be done). As an example, a leading operational team implemented an AI/ML solution to optimize the performance of their electrical submersible pumps (“ESPs”, a form of artificial lift used to extract hydrocarbons from wellbores). As a result, the company was able to measurably increase asset longevity and production. Specifically, the machine learns and adapts based on past performance, processes future likely scenarios, and recommends solutions accordingly in a continuous closed loop:
- Smart & Dynamic Operations: Thanks to the increasing availability of, and more affordable access to, sensors, cloud infrastructure and storage, and machine learning, concepts such as Industry 4.0 have become mainstream, resulting in the deployment of digital technologies as part of core operations that improve overall performance by increasing production, reducing costs, reducing emissions, or enhancing collaboration. Going forward, “digital threads” connecting assets, models, and processes provide a single source of truth that can enable true end-to-end asset lifecycle management (from requirements definition through maintenance to asset plug and abandonment). Commodity transportation and logistics is another example where innovative, blockchain-based smart contracts from companies like Data Gumbo can be used to automate the execution of commercial contracts, eliminate the need for manual validation and increase trust and transparency between counterparties. As a result, operators have been able to reduce spend by ~4-11% by reducing unnecessary payment overages, improving payment terms, and reducing invoice processing costs.
In our experience of supporting energy companies achieving their digital transformation goals, we have always emphasized that employees can be either the greatest blockers or the greatest enablers of transformation success. This is more pertinent now than it had ever been in years past, as COVID19 has completely shifted the employee engagement model. Three areas energy companies can focus digital transformation efforts to improve employee experience include:
- Reskilling: The pace at which technology is evolving continues to accelerate. Companies need to invest in reskilling the existing workforce to be able to keep up, particularly as COVID19 permanently changes traditional ways of working. At the same, time energy companies will need to increasingly gain access to digital talent (e.g., data scientists, data engineers) that can assist with reskilling and will be critical to achieving digital transformation objectives. Attracting this talent will put our industry in direct competition with other sectors.
- Digital Augmentation: Augmenting employee productivity and performance through use of AI models or digital technologies such as augmented reality (AR) goggles. As an example, oil and gas companies have deployed such tools to the knowledge management domain, where they have been used to help codify lessons learned and best practices built over years of drilling and completing and operating wells. Doing so has allowed companies to combine numeric models, AI and expert knowledge to develop symbolic outputs that can aid an end user to make optimal decisions.
- Digital Culture: Companies need to take a step-back and ask “is my organization ready for a digital transformation?” and “is my business AI ready?” COVID19 has given leaders the perfect opportunity to assess their current business needs, culture and digital readiness (i.e., the attributes that will be required to be successful in any future digital transformation efforts).
While the O&G industry is traditionally considered to primarily be a B2B industry, the recent energy transition and low carbon shift is forcing O&G players to become more aligned to end-customer requirements. This is true for integrated majors and downstream players on the retail fuel end of the value chain, as well as in emerging businesses like carbon capture and storage. To improve customer experience, there are three areas where I believe companies should prioritize digital efforts:
- Experience Design: On the fuels and retail side, especially as oil and gas companies become energy companies and provide electric solutions in addition to conventional oil and gas products, designing an engaging and compelling customer experience has become even more critical. Companies can partner with innovative design-thinking studios to develop “day in the life of” studies, combined with “journey maps” of various personas to design the ultimate customer digital experience – from fuel/charge stations to mobile app solutions.
- Customer Intelligence: The industry has traditionally struggled with integrating customer data across silos and understanding customer behavior. Looking forward, especially as AI and machine learning solutions gain traction, real-time customer intelligence is enabling highly personalized interactions and making it possible to deliver accurate and targeted system-generated recommendations. As an example, oil field services companies that provide production chemical have developed highly analytical solutions and services based on chemicals consumption, well productivity and weather parameters.
- Emotional Engagement: Being able to adapt to changing customer needs and evolve existing offerings has become a critical success factor for many players serving the oil and gas industry. Companies can improve customer engagement by conducting “Voice-of the Customer” analyses leveraging technology to solicit real-time customer feedback across the value chain. IT functions within oil and gas companies can adapt a similar approach and gather feedback from operational teams in designing and scaling new solutions across the organization. This enables the teams to feel they are being heard, provides IT and digital teams with the requirements/feedback they need to drive efficiencies.
A Well-Structured Foundation
The last, and one of the most critical, element within digital transformation framework is a well- structured digital foundation, including trusted, accurate and accessible data, and defined business processes. In a recent survey led by The Carnrite Group, 33% of participants stated that foundational data architecture and data management issues have hindered the pace and overall ability to achieve their digital transformation vision. We suggest operators focus on three primary foundational elements: 1) Cloud Modernization, 2) Data Lake (e.g., making data centrally accessible across systems) and 3) Data Architecture and Management to enable agility and flexibility for future digital capabilities that are yet to be known.
Digital Transformation Foundational Challenges
Whether you choose a single element within the digital transformation framework to prioritize your efforts in the post-pandemic world or a combination, The Carnrite Group has the experience and the partner ecosystem to assist you to define a digital transformation vision and strategy, prioritize the business challenges and opportunities, and chart a course to create and accelerate value.