A Priority System for Allocating an O&M Budget

Beginning in the late 1990’s, Northern States Power (Electric) began exploring formal tools for improving the allocation of its annual operating budget of over $250 million. The goal was to establish a fair, efficient, and effective process for allocating funds across territories and departmental functions. After trying several approaches, NSP created a resource allocation system based on multiattribute utility analysis. The system was used until NSP became part of Xcel Energy in 2000. Characteristics of the system and lessons learned are presented. Introduction Northern States Power (now called Xcel Energy) is an electric utility serving over one million customers in Minnesota, North and South Dakota, Wisconsin and Michigan. In 1997, the electric business unit, NSP Electric, created a centralized Asset Management department with responsibility for the annual operating budget of more than $250 million. A major challenge was establishing a fair, efficient, and effective process for allocating operating funds across territories and departmental functions. Despite previous attempts to use priority setting tools, key managers would invariably make decisions after lengthy discussions and based largely on intuition. The process was painful and departments with the most eloquent speakers often came out ahead. As issues became more complex (e.g., invest in information technology vs. system hardware) and as stakes continued to grow (corporate pressure to lower costs regardless of external cost drivers such as storm damage and rapid customer growth), the task became even more daunting. A better process was needed. Methods Used and How They Were Applied Starting in 1997, the Asset Management department undertook an effort to create a formal resource allocation system. The development effort was assisted by my coauthor (to help ensure a logical, defensible design) and stakeholders from the affected departments (to improve buy-in and to ensure that all concerns and issues would be addressed). The selected approach was based on multi-attribute utility analysis. Multiattribute utility analysis, also called multiobjective or multi-criteria decision analysis, is a formal theory for making complex decisions that impact multiple objectives PT Graduate programs at many universities teach this method. It TP 1 PT The data contained herein has been approved for public release by Northern States Power (NSP). The information was originally prepared in support of NSP’s submittal of the described priority system to the Institute for Operations Research and Management Sciences (INFORMS) “2000 Competition for Best Application of Decision Analysis.” The priority system was selected as a finalist and presented for judging at the November 2000 INFORMS meeting in San Antonio, Texas, where it was awarded “runner up” status. TP 2 PT See R. Keeney and H. Raiffa, Decisions with Multiple Objectives, Wiley, New York, 1976.” A detailed reference emphasizing applications to government decision making appears on the United Kingdom ODPM website. Follow the links on the ODPM website ( HTUwww.odpm.gov.ukUTH) to “Multi-Criteria Analysis Manual.” A Priority System for Allocating an O&M Budget 2 c 2004 Lee Merhofer Consulting Myers Martin Consulting, LLC www.prioritysystem.com has been used to support numerous high-level government and business decisions and is recommended by a Department of Energy Standard on prioritization. TP PT NSP used the resulting priority system over 3 years (the budgeting cycles of 1998, 1999 & 2000) until the company was merged into Xcel Energy. The purpose of the system was to identify allocations of the operating budget that would increase system reliability and customer service while at the same time eliminating budget gaps. More specifically, the system was used to evaluate and recommend allocations of the operating budget across 10 broadly defined delivery products (called “portfolios”). The system operated as follows. To provide alternative allocation scenarios, each portfolio team proposed multiple five-year funding cases. Three cases were required. Case 1 assumed a “bare bones” funding level sufficient only to protect health and safety. Case 5 held funding to 1999 levels for five years. Case 9 was a “maximum” funding level encompassing every activity that could be undertaken effectively. In addition, portfolio teams created intermediate funding cases so that increments between cases were no more than $2 million (Figure 1). To provide a basis for evaluating the funding cases, a team of senior managers established 7 fundamental objectives. The objectives included both financial goals (e.g., revenue and cost impacts) and non-financial goals, such as improving customer service (e.g., reliability, meeting commitments, and billing) and creating a platform for future success (e.g., enhancing corporate reputation and increasing employee effectiveness) (Figure 2). TP 3 PT See HTUhttp://risk.lsd.ornl.gov/CRE/DOEguide.pdfUTH. Figure 1: Each portfolio team identified the activities to be conducted under 3-9 alternative five-year funding scenarios. Cases 1, 5 and 9 were required; others were optional. A Priority System for Allocating an O&M Budget 3 c 2004 Lee Merhofer Consulting Myers Martin Consulting, LLC www.prioritysystem.com Note that safety was not explicitly represented as an objective. Safety was viewed as a constraint for decision making—regulations and NSP policy (and the definition of the minimum funding case) ensured that an adequate level of public and worker protection was provided under all funding cases. Management and staff developed the measures and scales for evaluating funding cases against each objective using a formal process involving influence diagrams. An influence diagram PT is a graphic device for identifying key influencing factors (Figure 3). TP 4 PT M. W. Merkhofer, “Using Influence Diagrams in Multiattribute Utility Analysis – Improving Effectiveness through Improving Communication,” Chapter 13 in R. M. Oliver and J. Q. Smith (eds.) Influence Diagrams, Belief Nets and Decision Analysis, Wiley, New York, 1988. Figure 2: Objectives established for budget allocation decisions. Better, Faster, Cheaper