TY - CHAP
T1 - Redesigning the Current Inventory Management Process for an SME
AU - Montt, Cecilia
AU - Lillo, Paloma
AU - Quezada, Luis
AU - Oddershede, Astrid
AU - Valencia, Alejandra
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - Companies have different types of processes in their logistics chain. Thus, the added value delivered to each link generates a fundamental competitive tool, such as excellence and differentiation in the delivery service, coupling with technology and anticipating what customers need or expect, which means that companies must have an efficient inventory and resource management. On the other hand, companies need to procure goods and services for the development of their activities. These supplies are accumulated in the companies and must be managed for their correct handling and conservation. The problem that the SME has is that when customers buy in the store, in several cases, there is no product so sometimes the sale is lost, or they wait and return the day that the product is in the store. So in this work we study the case of an SME, companies that need inventory management to avoid losing customers. In this case, the inventory and sales process is modeled and simulated using Bizagi Modeler, where it was possible to obtain the breaks. Demand forecasting was studied with neural networks. Since the behavior of the demand is variable during the year, mainly December, February, Mother’s Day and others, which causes peaks in demand, to analyze this behavior we used the Periodic Review P Model, where we obtained the quantity to be requested to the supplier in different periods of the year, which increases sales, since 100% of the demand is covered. The results of the simulation with BIZAGE with the current and proposed situation show that in the proposed situation the loss of customers is between 0 and 0.5%. In relation to costs and profits, these were obtained with model P, although the costs increase by about 5% since a larger inventory is maintained than in the current situation, but customers will be 100% satisfied, which leads to an increase in profits of between 15 and 20%.
AB - Companies have different types of processes in their logistics chain. Thus, the added value delivered to each link generates a fundamental competitive tool, such as excellence and differentiation in the delivery service, coupling with technology and anticipating what customers need or expect, which means that companies must have an efficient inventory and resource management. On the other hand, companies need to procure goods and services for the development of their activities. These supplies are accumulated in the companies and must be managed for their correct handling and conservation. The problem that the SME has is that when customers buy in the store, in several cases, there is no product so sometimes the sale is lost, or they wait and return the day that the product is in the store. So in this work we study the case of an SME, companies that need inventory management to avoid losing customers. In this case, the inventory and sales process is modeled and simulated using Bizagi Modeler, where it was possible to obtain the breaks. Demand forecasting was studied with neural networks. Since the behavior of the demand is variable during the year, mainly December, February, Mother’s Day and others, which causes peaks in demand, to analyze this behavior we used the Periodic Review P Model, where we obtained the quantity to be requested to the supplier in different periods of the year, which increases sales, since 100% of the demand is covered. The results of the simulation with BIZAGE with the current and proposed situation show that in the proposed situation the loss of customers is between 0 and 0.5%. In relation to costs and profits, these were obtained with model P, although the costs increase by about 5% since a larger inventory is maintained than in the current situation, but customers will be 100% satisfied, which leads to an increase in profits of between 15 and 20%.
KW - BPM
KW - Inventory management
KW - Neural networks
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=85166103068&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-18641-7_58
DO - 10.1007/978-3-031-18641-7_58
M3 - Chapter
AN - SCOPUS:85166103068
T3 - Lecture Notes in Production Engineering
SP - 629
EP - 635
BT - Lecture Notes in Production Engineering
PB - Springer Nature
ER -