Meanwhile, energy companies are finding that many of their competitors also are pursuing technology-enabled changes that enhance their effectiveness and efficiency. In Grant Thornton’s experience working with energy organizations, a substantial majority have started their digital transformation, and many others say they plan to start soon. The remainder are in danger of being left behind by competitors with superior capabilities.
One of the main problems that digital transformation can help solve for energy companies is the fragmentation of their systems. During the enterprise resource planning (ERP) boom of the 1990s, many energy companies made significant improvements through implementations that centralized systems of record, supported business processes and delivered some automation.
But for many of those systems, it’s difficult to gain access to the right data, and the reporting tools are lacking. The systems impede the organization almost as much as they enable it.
For many energy companies, their current state is dealing with “technology disrupting you, rather than you using technology to disrupt markets”, John Stilwell, a Principal who is National Energy Lead — Advisory, for Grant Thornton, said at the last AICPA Oil and Gas Conference. Tools developed over the past 20 years provide energy companies with an opportunity to improve processes and develop efficiency that would have been unthinkable a generation ago. Leaders in the industry are making investments in augmented analytics, artificial intelligence, natural language processing and machine learning.
Grant Thornton’s clients typically are considering 10 to 15 different technologies over a horizon of five to 10 years. The top technologies they are considering in the near-term are:
✓ Big data and analytics: Considered as foundational, the energy sector has been focused on maximizing on the investment in transactional systems like ERP and manufacturing executing systems for the past two decades. Selecting a cloud analytic technology that qualifies as a Tier One platform and creating an enterprise program for analytics is a standard first step. The volume of data within the energy industry requires discipline around data governance and management. Understanding this technology is not a point-in-time solution, but a continuously evolving program with multiple content releases a year, is the key for success as energy clients respond to an ever-changing competitive landscape.
✓ Cloud computing: Energy clients are focused on transitioning enterprise applications to cloud software as a service model. This can include an “edge-in” approach that starts with applications with less risk to daily operations and allows for agility in a changing marketplace. The journey to the cloud reduces risk and overall cost of ownership, while maximizing the ability to be on the most recent releases and software innovation. Cloud transition strategies have been in place over the past decade and are inherent to current and future application strategy. The energy industry has been a key adopter of the cloud technology trend, and it continues to make investments in software as a service.
✓ Robotic process automation (RPA): Energy clients are using RPA to build “bots” — a software technology that makes it easy to build, deploy and manage software that replaces human actions with digital systems and software. The energy industry has made massive investments in ERP and other transactional systems, and RPA delivers the next level of efficiency on these systems of record. RPA bots typically work on transactional systems and automate tasks under predefined process rules. Bots are deployed on a program basis and often include a detailed business case and benefits realization.
✓ Manufacturing execution systems: Energy clients are focused on extending their enterprise applications beyond the back office. With a high degree of sophistication on operations, supply chain and asset management, the energy industry demands technology that can not only manage complex processes, but also provide data analytics on performance management. These computerized systems are used in key manufacturing and supply chain processes to track and document the transformation of raw materials to finished goods. Manufacturing execution systems are the foundational steps to an internet of things program for the energy industry, providing greater visibility into equipment and processes and minimizing maintenance costs.
✓ Artificial Intelligence (AI): Recent democratization of AI technology has been grabbing headlines, while clients in the energy industry have invested heavily in this technology over the past several years. AI has numerous use cases for the energy industry ranging from smart grids to management systems and failure predictions. AI is the culmination of foundational investments in big data, cloud and manufacturing execution systems. AI in energy and utilities can be used in many forms but is typically centered on optimizing the sector for modern challenges. With the vast amount of data existing in the energy sector, converting it into a strategic asset with AI and machine learning is key to unlocking value.
“Focus on disruptive forces that are most impactful to your organization,” Stilwell advised.
He suggested that energy companies start their digital transformation journey with a six- to eight-week project for leaders to set priorities and create a roadmap. During the process, a strategic framework and a program charter are built.
That leads to specific technology perspectives and recommendations along with implementation plans. Change management implications should also be addressed, and estimates should be made for both costs and return on investment.
This exercise is the beginning of a three- to five-year program that divides specific technology opportunities into immediate, medium-term and long-term priorities.
“You make sure you have the foundational requirements covered, then look to the future toward some key areas that will be more difficult to implement, but that we know will make a positive difference,” Stilwell said.
The amount of foundational work that needs to be done will depend on the digital maturity of the organization at the start of the process. For example, energy companies whose functions already are in the cloud might move more quickly to work on long-term goals.
One example Stilwell cited was a client that needed a fair amount of foundational work. That client needed some common services, including:
With the foundation in place, organizations then pursue the changes that can help them maximize their market disruption.
Both internal and external-facing technology platforms should be considered.
“You also take into account the ability of certain areas or departments and the extent of their people’s aversion to change,” Stilwell said. “Not everybody is ready for RPA. Some people might only be able to handle simpler improvements.”
Ultimately, energy companies that take their strategic priorities and use them to establish a direction for their transformation put themselves in position for innovation and efficiency that can give them an edge in the market.
“You’re not going to be the nail anymore, you’re going to be the hammer,” Stilwell said. “You’re the one that’s going to apply the disruption to your industry and your competitors.”