First of all, it is necessary to define the scenario boundary of the case before starting any analysis work. Many warehouse operation personnel directly copy the conclusions of public cases without checking the basic operation attributes of the project, which often leads to poor adaptation of the final implementation scheme. You can first sort out the basic attributes of the case, including the type of warehouse, the average daily number of operation shifts, the daily average pallet handling volume, and the baseline data of the material handling equipment used before the deployment of lithium-ion forklifts. For example, the case data of a 24-hour multi-shift fast consumer goods distribution warehouse has limited reference value for a small e-commerce warehouse that only operates for 8 hours a day, and the scenario mismatch will make the follow-up data comparison lose practical significance.

Secondly, it is necessary to split and verify the core operational data of the case in multiple dimensions. Instead of paying attention to the single reduction rate of operating cost mentioned in the case, you can disassemble the data into multiple measurable indicators, including the average monthly energy cost of the equipment, the maintenance cost of the supporting charging facilities, the proportion of non-operation downtime of the equipment per month, and the time cost that the on-site operators spend on the charging and maintenance process every week. You also need to pay attention to the soft feedback of the on-site team, such as the improvement of operation comfort, the reduction of on-site noise, and the change of labor protection related costs, to avoid drawing a one-sided conclusion from only a few hard data.

Thirdly, you need to evaluate the long-term adaptation performance of the case after long-term operation. It is necessary to confirm the actual operation cycle of the lithium-ion forklift deployment project, rather than only referring to the 2-3 month pilot test data. You can pay attention to the data such as the actual battery attenuation rate after one or two years of operation, whether the charging facility layout occupies the original normal operation passage space, and whether there is congestion in the energy replenishment scheduling during the peak operation period. These long-term operation details are often not mentioned in the preliminary project promotion content, but they are the key factors affecting the continuous operation effect of the warehouse.

By sorting out the scenario boundary, verifying the multi-dimensional operation data, and evaluating the long-term adaptation performance layer by layer, you can extract practical and valuable experience from a large number of real deployment cases, effectively reduce the unnecessary trial and error cost in the process of promoting lithium-ion forklift application in your own warehouse.