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socio-economic data in the study area to help prioritize commodities and"what-if' scenarios for <br /> the optimization. <br /> 1.3 Information Analysis: <br /> Quetica will analyze information collected from interviews and also conduct literature research <br /> to document network constraints reported by the stakeholders and past studies. The information <br /> is used to develop the quantitative optimization objectives and the initial version of the "what-if' <br /> scenarios for the optimization. <br /> 1.4 Discovery Deliverables: <br /> Quetica will document the findings of the Discovery Phase in a report that will bep rovided to <br /> the client project manager. The report will include Quetica's understanding of the current <br /> network, supply chain data inventory, data gap analysis if necessary, and a summary of <br /> stakeholder feedback. We will also prepare and make a formal presentation summarizing the <br /> Discovery Phase findings to Decatur's leadership. <br /> Phase 2• Design <br /> The network optimization model design includes the supply chain network comprised of <br /> commodity flows into and out of the study region Macon County. In addition, Quetica proposes <br /> to include the "through" commodity flows that are originated or terminated in the nearby <br /> counties including De Witt, Piratt, Moultrie, Shelby, Christian, Sangamon, and Logan counties. <br /> Based on Quetica's experience in public and private sector freight planning, these commodity <br /> follows can take advantage of the logistics solutions in the Decatur region to consolidate/de- <br /> consolidate or divert to Decatur region. Quetica will complete the following tasks to design and <br /> optimize the City's supply chain network: <br /> 2.1 Demand Data Collection and Cleansing <br /> Quetica will use its disaggregated FAF 4.3 and import/export data as the primary public data <br /> source and supplement the public data with private sector data collected under NDAs. The <br /> private sector data is typically Bill of Lading data from a company's transportation management <br /> system (TMS) or freight audit and payment system (FPS). Quetica accepts data in various <br /> formats including Excel, Access database, and flat file. The data will be reformatted to load to <br /> Quetica's Microsoft SQL Server database. Quetica will then work with the data providers to <br /> cleanse the data to make sure pertinent data items such as origin, destination,products shipped, <br /> transportation mode, weight, and transportation equipment type used are correct—if not, a data <br /> cleansing process is used to clean up the data. Quetica will then use a data aggregation, <br /> desensitization, and normalization process to aggregate location data to county level, company <br /> specific mode to common transportation mode, company specific equipment type to common <br /> equipment type,product information to commodity code using the Standard Classification of <br /> Transported Goods (SCTG) coding system, and weight and cost data to standard units of <br /> measure. The private sector data will be analyzed and integrated into the public sector data to <br /> develop a more comprehensive view of the supply chain network in the study region. <br /> Last Revised:2017-06-01 <br />