goseconomicmodel(gem)overview(參考版)
2024-10-03 21:07本頁(yè)面
【正文】 GOS Economic Model (GEM) Overview ?Uses the same underlying simulation software (Stella) which was used in developing TNM Economic Model (NBSim) ?Provides a prehensive tool for deriving estimates of GOS Net Benefits (Total Benefits Total Costs) for each Alternative ?Captures multiple Benefit Streams, as specified by the Value Proposition: ? Reduces Duplication of Data ? Increased Availability or Accessibility of Data ? Planned Data Buys (leveraging future data purchases) ? Increased Spatial Readiness (still needs some work) ?Provides the ability to control for uncertainty of certain input parameters and estimates Net Benefit Calculation/Estimation Process ?GEM uses a variety of inputs (., quantitative estimates) to determine the Total Annuals Benefits associated with GOS ?The design of the model’s benefit elements is based largely upon the type of GOS benefits documented in the GOS Value Proposition ?The Cost portion of the model is based upon input from the GOS LCC Analysis ?Major runs of the model will coincide with key FY 2020 GOS Milestones Submission of the BY’06 Exhibit 300 (September 2020) Measuring Spatial Readiness/Spatial Intelligence ?The Value Proposition defines certain key Premises: GOS plays a major role in closing the GAP that exists in federal agencies in terms of Spatial Readiness Spatial Readiness is the essential prerequisite for having Spatial Intelligence Applying Spatial Intelligence leads to better (more informed) decision making and better use of agency resources ?GOS overall benefits cannot be fully realized until the overall Federal Agency GAP has been closed Therefore, GOS’ role in accelerating GAP Closure is the basis in which the federal enterprise achieves Spatial Readiness Federal Agency Assessment (Measuring Spatial Readiness) ?Spatial Readiness is one of several key parameters and estimates which serve as inputs to the overall Exhibit 300 Cost Benefit Analysis Preparation ?The GOS team’s baseline approach to the Life Cycle Cost (LCC) Analysis and CBA is based upon grouping Federal Agencies and Departments into Tiers ?The proposed next step is to follow this initial grouping with a more rigorous approach which takes into account specific criteria for assessing Spatial Readiness ?The proposed approach consists of the following steps: Form a small interagency assessment team Enable team to score agencies independently based upon a specific set of criteria Total team member scores and develop readiness index for each agency **Current Readiness remend that a small interagency team assess and rate each Tier 2 and Tier 3 agency based upon certain GOS specified criteria (., Readiness Matrix) Top Down Approach for Assessing Spatial Readiness Spatial Readiness Inadequate (inability to use spatial data) Low (Required for GOS Compliance) High (Uses Spatial Intelligence) Tier 1 Tier 2 Tier 3 Essential (Ongoing Use of Spatial Data) Representative Agencies’ Distribution for Tier 3 Agency X Smaller Readiness Gap Assumption: Having a large Investment in Geospatial Technology (as a % of an Agency’s IT Infrastructure) means high degree of Spatial Intelligence) Overall Readiness GAP Top Down Approach for Measuri
教學(xué)課件相關(guān)推薦
鄂ICP備17016276號(hào)-1