Learning Objective: After this session, attendees will have another tool in the toolbox to guide their decisions to brownfields redevelopment and community enhancement. Using predictive analytics, users will be able to rely on their local and intimate knowledge combined with documented redevelopment costs to prepare realistic economic development expectations.
Abstract: Predictive analytics has come a long way and it’s now being applied to community revitalization decisions. Using Monte Carlo cost simulation guided by journals and EPA databases and guidance documents, communities can harness readily available data to predict the economic benefit of brownfield redevelopment using customized knowledge of their locale. This method can set up decision points for each community and guide them in pursuit of funding and financing.
This technique incorporates redevelopment costs along with post-development taxable status and income that allows communities to quantify the risk and reward of redevelopment. Armed with this information, communities can build their case to justify development of blighted areas for loan underwriters, grant reviewers and state/federal fund disbursers.
Utilizing documents from published journals to EPA resources, includes ACRES downloadable data, a deep dive into community redevelopment can be performed to determine the risk and reward of similar situations. Economic and social factors including present value, current/proposed zoning, chances of site access, public opinion, possible tax income, interest rates, inflation, discount factors and additional funding sources (insurance, additional grants and loans, municipal reserves, etc.) can be included for financial confidence. From the technical side, costs associated with typical Phase I/II’s and cleanups, feasible deed restrictions and varying contaminants can also be incorporated.
Once a community has preliminary plans for revitalization, conversations between different municipal entities (mayor/council, operations, economic development, utilities, etc.) can be held in order to coordinate and set up the model inputs and outputs. Once the comprehensive community plan is understood, information is entered into the simulation and set up in a way to provide the most valuable data output. Key decision points will be identified and ultimately provide the community with guidance on the economic impact of those decisions. If necessary, FASB and GASB standards can be incorporated to 1) provide familiarity, 2) ease post-simulation redevelopment tracking, and 3) provide defensible backup for community decisions.
