Automation of warehouse resource planning process by using a cloud demand forecasting tool

Abstract

Purpose: Research paper is an extension of the concept connected with demand forecasting function acquisition by logistics operators in the whole distribution network (concept is considered among others in the following papers: (Kmiecik, 2021a, 2021b, 2020). The concept of centralized forecasting assumes that a logistics operator, whose attributes coincide with the features selected through analysis of forecasting-able entities in the distribution networks and flagship enterprises, is able to take over the forecasting function for the whole distribution network. Paper, which is based on the mentioned concept, shows one of the first stages of its implementation. This stage is the implementation of the forecasting tool in the logistics operator's actions to support his operational activities. Currently, the logistics operator doesn't conduct the forecasting activity, but there are attempts aimed at implementation of forecasting tool and increasing the offered services' added value level. Operational activity, which will be first to be supported, is the process of planning the warehouse resources. Mentioned resources concern the human and internal transportation resources, which are needed for fulfilling the processes connected with SKU (Stock Keeping Units) releasing from the warehouse. The main paper purpose to examine the concept the of automated cloud-based resource planning process at the selected 3PL entity which provides logistics services to wide range of manufacturers in the distribution network using the computer simulation model with comparison with the current resource planning process. Design/methodology/approach: Following research paper based on analysis the survey results and analyzing the simulation results. In the survey were tested the warehouse managers which are responsible for resource planning process. The analysis provides the general requirements of managers about resource planning process supported by automated cloud-based demand forecasting solution and information about expected forecasting tool accuracy. In the paper there were also created two simulation models based on BPMN 2.0 standard. First model reflects the current shape of resource planning process and was created to compare to the second, improved model. Improved model includes the examining of automated cloud-based resource planning solution. Findings: The main expectations of 3PL operational managers about usage the demand forecasting tool is to support of warehouse resource planning. They also state that the expected accuracy of such a tool is the weekly MAPE not greater than 5%. The main benefits of proposed solution are the time decreasing, increasing the level of automation, showing the main areas when the agile point of view should be implemented and show the perspective of resource possibility of usage in the different activities (beside the resource planning process). Originality/value: Automation and fully cloud integration will allow to reduce the process time more than 60% (in total and in average one process time). There are also some disadvantages of proposed solution which could be reduced by using other trends connected with Industry 4.0 development and by developing the collaborative strategies of the particular nodes of distribution networks. Keywords: logistics operator; distribution network; warehouse management; demand forecasting; BPMN 2.0 model. Category of the paper: research paper.