Like most organizations, the Louisville and Jefferson County Metropolitan Sewer District (MSD) prepares facility plans and watershed action plans with 20 year planning horizons. Multiple factors are considered, such as population projections, land use, environmental conditions, capital
and operation and maintenance requirements, political issues, projections of economic conditions, etc. which are then converted to point estimates based on a series of assumptions. But what happens if the base assumptions change? How confident is your organization about a single point
planning horizon and its ability to dynamically decide the most cost-effective, low risk, long-term implementation plan for providing service to its customers? This is the question that the Louisville MSD has responded to through the development of a multi-variable risk model. The
project resulted in a systematic approach to planning considering the uncertainties of the future. Utilization of the multi-variable risk model has allowed MSD to assess the performance of a wastewater service area configuration over a range of views of the future. In addition, the model configuration
allows MSD the flexibility to dynamically update input parameters as growth, economic, technical and environmental factors change. This is a valuable tool in that MSD can continue to utilize this model and understand the impact of change on their business strategies over time. Decision
modeling allows organizations to move away from attempting to determine a single correct view of the future with a single correct response. Instead, the organization can quantify the impact on the performance of a strategy if the opposite of what they believe actually happens. In general,
traditional approaches to decision making by the industry have led to unclear processes, bias, information overload, underestimating or ignoring risk, unknown costs and hasty, indefensible, isolated decisions. Louisville MSD's development of a multi-variable risk model has allowed them
to view the performance of multiple strategies under optimal and less than optimal conditions to define the most cost-effective, low risk, fact based, credible implementation path for the future.
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