Inventory Optimization
Here's a pattern that shows up in almost every SME warehouse: roughly half the SKUs account for 80% of the cash tied up in inventory, yet most companies manage every item the same way, whether it's a $50/year fastener or a $2M/year component. ABC analysis, Economic Order Quantity and safety stock calculations replace "we always order 100 of these" with actual numbers for how much to order, when, and which items deserve the closest attention.
Decision it enables: how much of each product to order, and when; to decrease excess safety stock and free up real cash, without increasing the risk of stockouts on the products driving revenue.
Read the blog post →OTIF and 3PL Tracking
Your 3PL says 96% of deliveries are on time. Your sales team keeps hearing about the order that arrived four days late, and the one that arrived on time with half the quantity missing. Who is right? Right now, probably nobody can tell you, and every late or short delivery costs you the same thing: a customer who remembers it at reorder time. Tracking on-time-in-full (OTIF) at the order-line level, and separating what your warehouse shipped late from what the carrier delivered late, puts a euro figure on every failed delivery and shows exactly where it went wrong: which site, which carrier, which product. And the result is usually a relief rather than a shock. A handful of root causes — a stockout on one SKU, one carrier lane, customs on one route — typically explain 80% of the money at stake. That is a list a small company can actually work through.
Decision it enables: which carrier lane to renegotiate or re-tender, which SKU needs safety stock, and which warehouse dock to go and look at; with a scorecard built from your own data instead of the 3PL's, so the conversation is about facts rather than opinions.
Read the blog post →Quality Control with Lean Six Sigma
Most small manufacturers check quality against the spec limits: if the part is in tolerance, it ships. The problem is that a process can drift for days while still passing spec, quietly building up scrap and rework costs. Statistical process control — X-bar and R charts, p-charts and capability analysis (Cp/Cpk) — separates normal, everyday variation from genuine process shifts, so a filling line running a few grams high gets caught the same day instead of showing up weeks later as a 2% defect rate.
Decision it enables: when to stop and investigate the process versus leave it alone, and whether scrap and rework costs justify investing in better equipment.
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