The list of 10 watch-outs that follows is based on my experience. Some of these are mistakes I've made and learned from, others are mistakes I have observed.
- You do need a good model. I've seen a lot of inventory models, some are more "unique" than useful. This is an area with a solid analytic/statistical framework available that has been real-world tested. Here's a link to my online calculator [How much inventory do you really need] or check out this Wikipedia entry for a basic introduction http://en.wikipedia.org/wiki/Safety_stock You are not going to build something with common-sense or street-smarts in Excel that can come close. Do the necessary learning, hire someone that already has it or buy into one of the commercially available packages.
- Better models yield better results. If inventory really matters to you, you may want to invest in a more rigorous level of modeling. A basic, statistical model will generate results if used well. A model that better fits your reality will let you cut deeper/faster. For a simple example check out: [Inventory modeling is not "Normal"]. Some other areas that may warrant extra work/investment:
- fitting the most appropriate distributions of uncertainty
- capturing demand uncertainty effectively
- handling multi-level distribution networks
- 5 points of improvement in forecast accuracy?
- a 25% reduction in lead-time from production?
- replenishing once a week rather than once a month?
- a delayed deployment strategy for hard-to-forecast products
- reducing service levels by 0.5 points
- stratifying service targets for different groups of products (typically based on volume and/or demand uncertainty)
- allowing service levels for individual product:locations to float in a wider range and using optimization to minimize the overall inventory while maintaining the aggregate service level target
A successful inventory modeling/optimization project does need a good model but it also needs great execution.