Evaluation of blockchain technology for cycle counting in supply chains with information discrepancies



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Blockchain technology has been proven to reduce information discrepancies in the financial domain. Bitcoin’s success and scalability have pushed Blockchain into the limelight. As such, retail and supply chain firms like Merck and Walmart are investing in Blockchain. Blockchain can give unprecedented visibility to supply chain operations. Inventory Information Discrepancies (IDs) are a hindrance to such visibility. Industry reports and white papers have proclaimed the benefits and quantified values of Blockchain. To date, these claims are primarily based on educated guesses and have not been analyzed by rigorous model-based analysis. This dissertation argues that there may be several gaps in evaluating the value of Blockchain technology, of which some are bridged with solid model analysis for inventories with information discrepancies.

The manager makes inventory inspection and replenishment decisions at the beginning of each period with the traditional method (manual) and Blockchain technology (automated with smart contracts). A single-period cost function is developed and extended to the multi-period problem. The objective is to determine if a Blockchain-smart contract inventory system with discrepancy will perform better than the traditional setting. The numerical study for the two systems shows that despite the discrepancy variability, demand volume, and the number of periods between cycle counts, the Smart Contract-based inventory system performs near-optimal and satisfies service level constraints better than the traditional systems. We also evaluate factors like holding costs, penalty costs, number of periods between cycle counts in conjunction with discrepancies and Blockchain. In particular, Blockchain performs significantly better when the ratio of system penalty cost to holding cost ratio is high. Also, allocating more cycle counts at the downstream partners will reduce the ill effects of discrepancies and reduce the bullwhip effect for a large supply chain. The analysis and insights generated from this study can be used to design guidelines or scorecard systems that help managers design better cycle-count policies with Blockchain. Furthermore, guidelines for practitioners for developing smart contracts are provided in the form of pseudocode. Finally, by comparing the costs associated with the two systems, the true value of accurate inventory information is quantified, which Blockchain systems may provide.

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Blockchain, Errors