Good decision-making is challenging but essential for conserving wildlife populations. Decisions in wildlife management must integrate values with science to achieve desired future conditions. Managers need decisions to be effective at solving the problem, yet efficient and realistic for budgetary, manpower, and social considerations. Decisions need to be transparent and defensible to supervisors, employees, and constituents. Decisions also need to take into account institutional values, uncertainty, and risk tolerance. If decisions are made locally or repeatedly throughout an organization, a consistent decision-making process can be important. Identifying an optimal decision that accounts for all of these considerations, however, is challenging. An informal decision-making process may ignore or leave implicit potential assumptions, uncertainties, values, and priorities that may require explicit consideration in order to identify optimal decisions. Whereas informal decision-making is often adequate for relatively simple problems, a formal decision-making process can have great utility for more complex issues by explicitly integrating diverse, complex, and contradictory considerations that make identification of optimal solutions difficult. Structured decision making (SDM) is a decision analytic method that breaks decision-making into logical components of identifying the management problem, defining objectives for solving the problem, developing alternative approaches to achieve the objectives, and formally evaluating which of the alternatives is most likely to accomplish the objectives. Although application of SDM for a management issue may require potential upfront investments in time, funding, and training, these are generally far less costly than the consequences of a poorly made decision. 

The SDM process deconstructs a decision into logical components. The problem statement describes the management issue to be resolved by making a decision, fundamental objectives represent what ideally would be accomplished by a good decision, and alternatives are the potential actions that could be taken to meet the fundamental objectives. Decision analysis involves evaluating consequences and trade-offs among alternatives to identify the one most likely to yield optimal results.

The Unit has a long history of facilitation in Structured Decision Making processes for federal and state agencies. Past workshops include:

• Mountain goats and climate change
• Mountain lion population objectives
• Mountain lion quotas in Montana
• Elk archery season setting
• Elk brucellosis management
• Elk management in Montana
• Bighorn pneumonia management
• Wolf harvest management
• Chronic wasting disease management

More details about Structured Decision Making can be found at:

Sells, S. N., M. S. Mitchell, and J. A. Gude. 2020. Addressing disease risk to develop a health program for bighorn sheep in Montana in Structured Decision Making: Case Studies in Natural Resource Management, edited by M. C. Runge, S. J. Converse, J. E. Lyons, and D. R. Smith.

Runge, M. C., J. B. Grand, and M. S. Mitchell.  2013.  Structured decision making.  Pages 51-72 in P. R. Krausman and J. W. Cain III, editors.  Wildlife Management and Conservation:  Contemporary Principles and Practices.  The Johns Hopkins University Press.

Mitchell, M. S., H. Cooley, J. A. Gude, J. Kolbe, J. J. Nowak, K. M. Proffitt, S. N. Sells, and M. Thompson.  2018.  Distinguishing values from science in decision making: setting harvest quotas for mountain lions in western Montana .  Wildlife Society Bulletin DOI:10.1002/wsb.861.

Sells, S. N., M. S. Mitchell, V. L. Edwards, J. A. Gude, and N. J. Anderson.  2016.  Structured decision making for managing pneumonia epizootics in bighorn sheep.  Journal of Wildlife Management 80:957-969.

Mitchell, M. S., J. A. Gude, N. Anderson, J. Ramsey, M. Thompson, M. Sullivan, V. Edwards, C. Gower, J. F. Cochrane, E. Irwin, and T. Walshe.  2013.  Using structured decision making to manage disease risk for Montana wildlife. Wildlife Society Bulletin 37:107-114.