The benefits of a multi-echelon approach to inventory are always convincing. So then why is multi-echelon inventory adaption so slow to catch-on? Dr. Bram Desmet explores single-echelon vs. multi-echelon inventory approaches, and some of the reasons behind the slow rate of multi-echelon inventory adoption.
Have you just started a customer-product segmentation project? Sales is king, but you need to define a strategy and carefully plan which customers and products to grow, and which opportunities are the right ones to seize. Read this post from Bram for many useful ideas.
Recently, I experienced an earthquake during my trip to Taiwan. I am not sure but I think this was the first one for me. As it happened, you could feel a little back and forth movement. It lasted for a few seconds and then it was gone. While it caused some excitement (and concern) from us visitors, our Taiwanese colleagues shrugged and one of them even made a comment that this was our welcome to Taiwan.
If you are running a manufacturing or distribution business, you have to deal with inventory. In supply chains, inventory acts as a shock absorber just like the ones in your car. If there were no shock absorbers in your car, you would feel every bump in the road. Similarly in a supply chain you would have a very bumpy ride without inventory to absorb at least some of the variations. So, not all inventory is bad.
In one of my previous posts, I wrote about using coefficient of variation (CV) as a predictor of forecastability. In this post, I will talk about how it can be used to indicate a sensitivity of lead time towards the safety stock calculations. To quickly remind the reader first: The formula for CV = StdDev (σ) / Mean (µ)
Last post, I discussed in some detail the concept of cycle service level and how it works in the retail or a B2C environment. This week, let me take up the case of a business in a B2B environment. Typically, in a B2B environment, the orders are placed in bulk over the phone or the web. The customer typically is another business requiring large amounts of products to feed into their production process. An order is also usually made of multiple line items where the customer asks for multiple products on the same order.
Most businesses would put high customer service as one of their top business priorities. While there are many different things that make up the overall customer experience, one of the key performance indicators (KPIs) that companies measure is the timely delivery of goods to the customer. In safety stock calculations, this is typically an input called the service level. In this blog post, I will explore this a bit.
In the simplest inventory situation, the only variability is in the quantity of demand for a single day. There is no trend up or down or seasonal effect. The demand today is independent of the demand for tomorrow. Additionally, we will assume replenishment time is zero. That is when we place an order for additional material it arrives immediately – sort of like we have a Star Trek transporter. However, we can only reorder every N days, where N might be 3, 4, 20, etc.
In one of my previous blog posts on inventory, I used the info-graphic above to show the evolution of software to calculate safety stock. Since then, I have been asked the following question by several supply chain colleagues: How should one decide if their business needs Multi-Echelon Inventory Optimization (MEIO)? This is my attempt at answering that question.
My first memory of inventory is from a conversation I had with my Dad when I was probably 10 years old. I remember him telling me to go to a particular store because the owner kept a lot of inventory on hand. He equated that to the owner being a wealthy man, who obviously knew how to do business.