Author: Omer Goldberg, Intelichain Product Manager
In today’s supply chain, logistics disruptions, high competition, and omnichannel sales are just part of the challenges businesses must deal with. therefore, it is important to plan and manage supplies to decrease inventory costs, lead the business to maximize its strategy and goals under its current and future constraints.
The goal of the process is to agree on one supply plan that would fulfill the demand for the product/service offered optimally to fit the business goals and strategy.
The supply planning overall process consists of 3 main streams – Inventory, Production, and Procurement. Each organization can manage all or each stream differently depending on its supply chain structure (size and network).
We will focus today on the inventory planning stream – safety stock management.
Chapter 1: Inventory Planning – Safety Stock management
Inventory planning is the process of determining the optimal quantity and timing of inventory to align it with sales. To do that, the business must determine the safety stock level for its products.
So, how should we determine the right safety stock for our products?
There are two main approaches to manage safety stock:
1. Statistical Safety Stock – calculation of safety stock is required service level
2. Coverage Stock – estimation of the stock period (days/weeks/months) by average consumption
Our recommended way to determine the optimal safety stock is by the statistical safety stock, which is data-driven and can be optimized by AI and ML capabilities (for exception we always use the coverage approach).
Wouldn’t we simply strive for the highest service level for all our products?
The main challenge in safety stock determination is the tradeoff between the desire for high service level and the inventory level (which represents inventory costs). The trend between those two factors is exponential as we approach 99.99% service level as shown in the following graph:
Therefore, to calculate the optimal (and feasible) safety stock, it is required to consider 6 main factors:
1. Demand variability – some products/services can be stable; some can be seasonal and some unpredictable. The greater the variance in demand, the higher inventory levels are required to meet high service level.
2. Lead time – the number of days from the moment the company places an order for delivery until the arrival of the product. the longer the lead time, the higher the safety stock that is required to meet high service level.
3. Contribution to business goals – when the demand is higher than the ability to supply, the business must prioritize the products which serve the business goals (Max Revenue / Max Profitability / etc.)
4. Shelf-life duration – expiry date can be a top barrier to the amount of inventory that can be stored without being destroyed
5. Storage capacity – is a barrier to the amount of inventory that can be stored
6. Criticality – some products are excluded from financial / service level optimality due to constraints such as life savings and shall be treated manually
According to the above factors, it can be understood that not all products can be treated in the same way when one wants to determine the service level. In the other hand, it is difficult and inefficient to track, manage and maintain each product individually. In order to manage safety stock in an optimal way, it is required to divide products into different segments based on similar characteristics.
Which type of characteristics can help us define the segment of a product?
Sales Pareto Analysis (known also as ABC analysis) – the sales pareto analysis divides the product mix into 3 types, which represents the contribution to revenue.
‘A’ Products are the leading products with high contribution to revenue
‘B’ Products are intermediate products with mid contribution to revenue
‘C’ Products are “long tail” products with low contribution to revenue
Demand Variability Analysis (known also as XYZ analysis) – the demand variability analysis divides the product mix into 3 types, which represents the stability of demand from month to month.
‘X’ products are low variability products with stable and continuous demand
‘Y’ products are mid variability products
‘Z’ products are high variability products with sporadic and intermittent demand
The combination of sales pareto analysis (ABC) and demand variation analysis (XYZ) will generate 9 segments of products with common characteristics which can be managed easily and effectively. Each segment has its unique characteristics and therefore, unique inventory policy.
For example:
‘AX’ products – are leading products with stable demand. In this case, low variability requires low inventory levels and high revenue requires high attention. Therefore, we want to focus on this type of items and give them the high service level under MTS (make to stock) approach.
‘CZ’ products – are “long tail” products with unpredictable demand. In this case, high variability requires high inventory levels and low revenue requires low attention. Therefore, the inventory costs for those items can be higher than their potential contribution to revenue, so we will recommend MTO (make to order) approach, which means no safety stock for those products.
We at Intelichain have designed a dedicated and practical inventory planning digital platform that leads you to optimize inventory levels for each product segment (applying machine-learning capabilities and best practice methodologies) and considering your constraints while reflecting the business benefits.
