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EPRI Paper: Business Model Development: Information Inputs for Decision Making

TL;DR

The energy sector is in the early stages of a profound transformation toward a decarbonized future. In a new technical paper, "Perspectives on Transforming Utility Business Models: Paper 5 - Business Model Development: Information Inputs for Decision Making", the Electric Power Research Institute (EPRI) argues that the "art and science of decision making" has moved to the center of this journey.

The paper posits that effective decision-making is no longer just an operational requirement but a strategic imperative. As utilities navigate a "VUCA" (Volatile, Uncertain, Complex, and Ambiguous) environment, their success will depend on the flow of the "right data and information to the right people at the right time."

The Strategic Context: Scenarios for Transformation

EPRI outlines four scenarios that describe how utilities might respond to the changing landscape, defined by their approach to innovation and the external business environment:

  • Utilities Lead: Utilities proactively respond to drivers, assuming a leadership role.
  • Utilities Disrupt: Utilities aggressively seek value in transformation.
  • Utilities Follow: Utilities respond incrementally to mandates.
  • Utilities Retreat: Utilities retrench to traditional strengths.

To move from "Following" to "Leading" or "Disrupting," the paper emphasizes that utilities must harness diverse information sources - ranging from consumer trends and policy goals to geopolitical shifts and financial market data.

The Hybrid Decision-Making Model

A key finding of the report is the necessity of a Hybrid Model. While the volume of data available today is overwhelming, technology alone is not the solution. EPRI advocates for combining:

  1. Technological Capabilities (AI/ML): To process vast datasets, make sense of uncertainty, and predict future trends.
  2. Human Intuition: To ensure the "right data of sufficient quality is used" and to apply sound judgment, particularly regarding ethical and strategic trade-offs.

Case Study: Linear Infrastructure Planning

The paper explicitly identifies Linear Infrastructure Planning as a critical area where this data-driven approach is already being applied. It notes that the deployment of energy infrastructure is "technically, environmentally, and socially complex."

In this context, the paper cites Optioneer by Continuum Industries as an example of a tool enabled by extensive data and AI that is supporting required decision-making. According to EPRI, the application of such tools delivers specific strategic benefits:

  • Speed of Design: Tools enabled by the right data allow design to be undertaken more quickly.
  • Enhanced Consultation: By revealing options earlier, consultation with local stakeholders can begin sooner and be more effective.
  • Collaboration: The approach enables better communication internally and with external specialist consultants.

The report notes that this data-centric approach aligns with the recommendations of the UK's Linear Infrastructure Planning Panel and the Electricity Network Commissioner, specifically regarding the need for sophistication in the use of data to accelerate infrastructure delivery.

The Risks of Inaction

EPRI devotes a section to the risks associated with failing to evolve decision-making processes. In the absence of good data and processes, utilities face significant threats, including:

  • Stranded Assets: Failure to adapt to market conditions may result in investments becoming economically unviable.
  • Regulatory Non-Compliance: Inadequate alignment with evolving environmental standards.
  • Reputational Damage: Poor decision-making regarding community engagement can erode the "social license to operate."

Conclusion

The paper concludes that while technology is a necessary enabler, business model innovation is equally critical. Utilities must establish robust data strategies that govern how information is acquired, integrated, and used. By adopting a systematic approach to "Information Inputs" - and leveraging AI-enabled tools like Optioneer to process them - utilities can navigate the uncertainty of the energy transition and secure a sustainable future.

Source

Electric Power Research Institute (EPRI). (2024). Perspectives on Transforming Utility Business Models: Paper 5 - Business Model Development: Information Inputs for Decision Making. https://www.epri.com/research/products/000000003002030494%201