Inventory Replenishment Strategies

If you are a US firm that is importing by container from India, chances are your imports come in through New York, Savannah, or Norfolk based on Census Bureau data. This raises the question: from a safety stock standpoint, are you better off using a carrier that is routing 100% of vessels around the Red Sea via the Cape of Good Hope (and adding ~8 days of transit time to what would usually be a ~26 day trip) (https://lnkd.in/egGZQjQR) versus a carrier that is rolling the dice about going through the Red Sea and may have some vessels either pause or have to divert to go around Africa (resulting in an even longer trip than with a planned Cape of Good Hope route)? Looking at some rough calculations using the most complete conventional formula for setting safety stock, the answer is direct routing around Africa is the better scenario for fast-moving ‘A’ items. One table below. Thoughts: •This table shows inputs for three scenarios: a baseline (left), a Cape of Good Hope planned reroute (center) and the Red Sea (current). With the Cape of Good Hope routing, I’ve added 8 days of to the lead time but not changed the variance of lead time. For the Red Sea scenario, I’ve added 2 days to the average lead time (to account for delays and some unplanned around Africa reroutes) but increased the variance of lead time by 0.25 days (to account for added uncertainty). Demand is assumed to be 100 units a day with a standard deviation of 20 units, resulting in a coefficient of variation of 0.2, which is commonly found for fast moving ‘A’ items. •As can be seen, safety stock is largest under the Red Sea scenario. The reason is due to the mathematics for how the standard deviation of demand during lead time (5th row) is calculated: [(Average Lead Time * Stdev Demand^2) + (Average Demand^2 * Stdev Lead Time^2)]^(1/2) What matters in this equation is that the variance of lead time is multiplied by average demand SQUARED. Thus, for any item where the coefficient of variation of demand is well below 1, an increase in the standard deviation of lead time has a much greater impact on the standard deviation of demand during lead time than an increase in average lead time. Implication: More variable lead times associated with Red Sea disruptions result in more safety stock than longer but less volatile lead times for shipping directly around the Cape of Good Hope. #supplychain #supplychainmanagement #shipsandshipping #logistics #freight

Because wrong service levels and inventory targets kill the supply chain... This infographic shows how to set them up in 7 steps: ✅ 1️⃣ Understand Historical Demand Patterns & Segment the Portfolio 👉 use historical demand data and calculate demand variability. Segment SKUs based on their value and demand variability. ✅ 2️⃣ Define the Required Service Levels 👉 decide the service level targets that the business needs. The higher the service level, more is the inventory needed. ✅ 3️⃣ Determine Lead Times 👉 understand inbound, production and outbound lead times. This will impact how much safety stock the company needs to maintain service levels. ✅ 4️⃣ Apply Seasonal Indexing 👉 Use the formula to calculate safety stock: Z×σd×L ❓ Where: Z is the Z-score corresponding to the service level (e.g., Z=1.65 for 95% service level); σ_d is the standard deviation of demand; L is the lead time in periods. ✅ 5️⃣ Set Reorder Points 👉 calculate Average Lead Time X Average Daily Demand + Safety Stock Calculate reorder points (ROP) to determine when to place an order ✅ 6️⃣ Balance Inventory Targets with Working Capital 👉 use the inventory turnover ratio and days of inventory on hand (DOH) to monitor and set reasonable inventory targets without overstocking. ✅ 7️⃣ Create Feedback Mechanisms & Monitor Performance 👉 track service levels and inventory performance weekly. Identify areas where the targets are not met and safety stock levels, lead times, and demand patterns need adjustments. Any others to add?

Hey there! 👋 Let's talk about something that's probably keeping you up at night - inventory management. I see so many amazing e-commerce businesses treating their inventory like a coin flip, and honestly, it breaks my heart because I know how much potential they're leaving on the table. 💔 Just last quarter, I had the pleasure of working with a fantastic client who was juggling inventory chaos across multiple channels. Sound familiar? We're talking disconnected systems, endless spreadsheets, and that exhausting cycle of putting out fires instead of actually growing the business. Here's the beautiful thing - the fix didn't require rocket science, but wow, did it change everything! ✨ We set up real-time inventory syncing that actually works. Now when something sells on Amazon, their Shopify store knows about it instantly. When wholesale orders come flooding in, their direct-to-consumer channel automatically adjusts. It's like magic, but better because it's real! We also implemented smart reorder points with safety stock buffers - no more playing the "will we run out?" guessing game. Plus, we strategically positioned their inventory in modern fulfillment centers to create a distribution network that just flows. The transformation was incredible: no more awkward conversations with customers about delays, no more sitting on piles of inventory in one location while being sold out everywhere else. The numbers speak for themselves - 98% order fulfillment with 25% lower carrying costs! 🎉 That's what happens when you stop treating each channel like a separate business and start thinking like the unified operation you really are. At the end of the day, your customers want their stuff fast and hassle-free. They don't care about your backend systems - they just want that seamless experience every single time. I'm curious - what's your biggest multi-channel inventory headache right now? Let's chat about it! #EcommerceSolutions #LogisticsExcellence

There’s a lot of uncertainty about what the global supply chain will look like in the coming months. I’ve felt like we’ve been playing supply chain on “hard mode” for the past 5 years, banging our heads trying to “get it under control.” Ironic, I know, given our namesake, Ministry of Supply. • 2019 - Regulatory: US-China relations and Sec. 301 changes • 2020 - Demand: COVID volatility • 2021 - Supply: Lengthening lead times • 2022 - Demand: Post-pandemic consumer boom • 2023 - Supply: Post-pandemic inventory bullwhip peak • 2024 - Demand: Inflation-induced softening • 2025 - Regulatory: Uncertainty in global production ecosystem We played MIT’s “The Beer Game” back in 2017 at a Ministry of Supply retreat. It’s a classic simulation that teaches about asymmetric information in production and distribution across 4-5 stages. Orders stream in steadily until, suddenly, an order spikes — without fail, people overcompensate. The key to managing this is resisting the impulse to overreact. Two years ago, and we found ourselves with ballooned inventory at 2x our target levels. Our inventory turns had dropped from 3x to 1x per year. The Problem was Twofold: •Rational: Safety stock is hypersensitive to demand volatility and lead times, especially when they length unpredictably. • Emotional: In theory, a rational actor would order proportionately… but we don’t. As my colleague Ian would say, “It’s like riding a wave; you can never see the bullwhip when you’re in it.” The desire to “gain control” over demand volatility and lead time uncertainty leads us to “plan further out.” Thanks to Sean Willems and Steve Graves, who introduced us to a radically different strategy: Don’t fight volatility. Design for it. The Solution: 1. Multi-Echelon Forecast - Split product forecasts. We use “fabric platforms” where shared fabrics are used across SKUs, pooling demand risk and shortening lead time forecasts. 2. Innovate to Standardize Materials - A double-dye cationic process now lets us create our solid and heathered Kinetic suits from a single fabric, pooling demand. 3. Shorten Reorder Cycles - Shifting from 2-4 buys a year to 12 increases PO frequency and shortens lead times, improving accuracy over forecasts. Connected forecasts like Crest, Flagship, and Singuli help place POs quickly. 4. Strategic Inventory Placement - Use safety stocks of raw materials and intermediate parts based on lead times. Undyed fabric is cheaper than a finished blazer and pools demand across products. 5. Communicate Inventory & Sales with Suppliers - Sharing forecasts and downstream sales data lets suppliers help create the materials strategy. Moving from emails to bi-weekly calls has made all the difference. Hope this helps with robustness in an uncertain climate. Thanks to partners Lever Style, Motives, SINGTEX Group , Teijin Limited, Toray Industries, Inc. for being part of this journey.

If you’re not planning peak in May Q4 is gonna hurt! Peak season doesn’t start in November. It starts right now. And if you wait until September to fix your fulfillment issues, you’ll be too late. Too late to rebalance inventory. Too late to clean up your SKU catalog. Too late to secure the labor, space, or carrier capacity you’ll actually need when orders spike. Here’s what the brands that actually crush Q4 are doing in May: → Reviewing last year’s split ship rates and rebuilding their allocation strategy → Locking in carrier volume before rates surge and zones bottleneck → Finalizing packaging changes to cut DIM weight before it’s multiplied across thousands of orders → Cleaning up dead SKUs to avoid paying Q4 storage penalties on ghosts → Stress-testing their 3PL now, not while customers are refreshing tracking pages every 30 seconds Your fulfillment strategy doesn’t need to be perfect in May. But if you don’t have a plan by now, you’re not preparing. You’re hoping. And hope is not a Q4 strategy. You don’t survive peak by reacting fast. You survive by planning early. May is when winners lock in the foundation.

I've seen it happen countless times. A brand with 35.6% profit margins and 153.7% year-over-year growth suddenly finds itself cash-strapped. How is this possible? After managing $200M+ for top eCom brands, I've identified the core issue: Inventory payment cycles are completely misaligned with Amazon's payment schedule. Here's the brutal math: → You pay for inventory 2.5 months before it sells (1 month production + 1.5 months shipping) → Amazon pays you every 14 days after sales → Each reorder grows larger to support increasing sales This creates a fundamental cash flow challenge that most sellers don't anticipate. In one case study, a brand generated $1.96M in total profit over 2 years but ended with a negative cash balance of -$15,446. The faster you grow, the worse it gets. When I bought Walkize (now a multi-million dollar brand), I immediately implemented these cash flow strategies: 1. Map your cash cycle Document every step from inventory purchase to payment receipt 2. Create rolling cash flow forecasts Project 6-12 months with weekly detail 3. Calculate capital requirements Add 20-30% buffer to projections 4. Secure financing before needed    Explore inventory financing, lines of credit, or Amazon Lending 5. Establish contingency triggers    Define minimum cash thresholds Remember: Profit doesn't equal cash. The critical metric is the ratio between your growth rate and your cash conversion cycle. For every 100% annual growth, plan for 50-100% more working capital. What's your cash flow strategy for scaling your Amazon business?

Ever struggle with unpredictable demand and supply constraints? 🤔 I believe Sequential Decision Analytics (SDA) can make a real difference. 📦 Scenario: You’re managing inventory for multiple products. Traditional methods rely on static plans based on fixed forecasts. But what happens when demand spikes unexpectedly or a supplier delays shipments? 🔍 SDA Approach: Instead of building one rigid plan, you create a sequence of decisions that adapt over time. 1️⃣ Capture the State: Gather everything you know—current inventory, pending orders, supplier reliability. 2️⃣ Decision Policy: Decide how much to reorder, whether to reallocate stock, or adjust lead times. This policy doesn’t just react to what’s happening now; it anticipates future changes. 3️⃣ Sequential Planning: Plan each step with the long-term goal in mind. Adjust your strategy as new data arrives, like shifts in demand or supply issues. It’s not about real-time reactions but about making informed, sequential choices. 🔄 Learning and Adaptation: Refine your policy as you learn. If a supplier is consistently late, factor that into future decisions, so your plan gets better with each iteration. 🎯 Objective: Optimize long-term profitability and service levels, not just by minimizing cost in a static model but by balancing risks like stockouts and overstock over time. With SDA, you're not just guessing or reacting; you’re building a resilient, adaptive strategy for your supply chain. What are your thoughts on this framework and approach? 🤔 #OperationsResearch #SupplyChain #InventoryOptimization #SequentialDecisionAnalytics

Managing inventory on Amazon doesn’t have to be complicated but having a simple and effective reporting system is crucial to ensure you stay in stock and avoid unnecessary costs. 💯 For Amazon-focused businesses and agencies, the emphasis is on optimizing inventory already in Amazon’s fulfillment centers (FBA) and ensuring the right products are sent in at the right time. 🔑 Here are three key elements every inventory management system should include: 𝟏. 𝐄𝐬𝐭𝐢𝐦𝐚𝐭𝐞𝐝 𝐑𝐞𝐨𝐫𝐝𝐞𝐫 𝐃𝐚𝐭𝐞𝐬 The cornerstone of any good inventory system is understanding when to reorder. This requires tracking: ▪️ Current Inventory Levels: How much stock is already in Amazon FBA. ▪️Sales Velocity: The rate at which your product is selling on Amazon. ▪️Transfer Times: How long it takes for inventory to ship from your warehouse to Amazon’s fulfillment centers. By combining these data points, you can calculate an estimated reorder date and ensure timely replenishments. This avoids costly out-of-stock situations that can hurt sales and rankings. 𝟐. 𝐓𝐢𝐞𝐫𝐞𝐝 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐂𝐚𝐭𝐚𝐥𝐨𝐠 𝐏𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐳𝐚𝐭𝐢𝐨𝐧 Not all ASINs are created equal. To optimize inventory management, you should categorize your products into tiers: ▪️A-Tier ASINs: Products contributing 5% or more of total sales. These are your top performers and must stay in stock at all times. ▪️B-Tier ASINs: Products contributing 1-5% of total sales. Important but slightly less critical—replenish as needed. ▪️C-Tier ASINs: Products contributing less than 1% of total sales. These are your “nice to have” items; prioritize them last if space or resources are limited. This tiering system ensures you’re focusing on what matters most, keeping the business afloat by prioritizing high-impact products. 𝟑. 𝐎𝐯𝐞𝐫𝐬𝐭𝐨𝐜𝐤 𝐚𝐧𝐝 𝐀𝐠𝐞𝐝 𝐈𝐧𝐯𝐞𝐧𝐭𝐨𝐫𝐲 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 Overstocked or slow-moving products can quietly drain profitability due to Amazon’s long-term storage fees. To manage this: ▪️Regularly analyze aged inventory reports to identify items sitting for too long. ▪️Consider running removal orders to clear excess stock and reduce storage costs. ▪️Use this data to refine your ordering process and avoid overstocking in the future. #Amazon #inventory #ecommerce #sales #revenue

Mastering Safety Stock Calculations: A Critical Element in Inventory Management In the world of inventory management, one of the most significant challenges is handling uncertainty. Whether it's unpredictable demand patterns or fluctuating lead times, both can lead to either stockouts (running out of products) or excess inventory (tying up cash in unsold goods). The Safety Stock Formula: Safety Stock = Z × √( (σd² × LT) + (D² × σLT²) ) Where: • Z = Service level factor (e.g., 1.65 for a 95% service level, representing the probability of not running out of stock) • σd = Standard deviation of demand (how much demand fluctuates from the average) • LT = Average lead time (the typical time it takes to replenish stock) • D = Average daily demand (average number of units sold per day) • σLT = Standard deviation of lead time (how much lead time varies) Let's Work Through an Example: Imagine a company has the following details: 1 Average daily demand (D) = 200 units 2 Demand variability (σd) = 50 units 3 Average lead time (LT) = 5 days 4 Lead time variability (σLT) = 2 days 5 Service level = 95% (Z = 1.65) Now, let’s apply the formula: Safety Stock = 1.65 × √( (50² × 5) + (200² × 2²) )
Safety Stock = 1.65 × √( 12,500 + 160,000 )
Safety Stock = 1.65 × 413.7 = 683 units So, the company needs to keep an additional 683 units in safety stock to ensure they meet demand with a 95% service level, given these uncertainties. Key Insights & Takeaways: • Safety stock is essential to manage both demand variability and lead time uncertainty. This helps you avoid stockouts and ensures you can continue operations smoothly even when things don't go as planned. • The service level (the probability that you won’t run out of stock) is crucial. A higher service level—like 95% or 99%—requires more safety stock. But this comes at a cost, as you're holding more inventory. You need to balance the cost of holding extra stock against the risk of losing sales. • Dynamic safety stock is more effective than static safety stock. As conditions change—whether due to seasonal demand shifts, supply chain disruptions, or changes in lead times—your safety stock levels should adjust accordingly. Relying on real-time data allows you to be agile and proactive. • Optimal inventory management is about striking the right balance between risk and cost. Too little safety stock increases the chance of stockouts, which can damage customer satisfaction and sales. On the other hand, too much safety stock can tie up working capital and lead to excess inventory, increasing storage costs and obsolescence risks. By using the formula provided, you can make data-driven decisions that allow you to: • Maintain a balance between cost and risk • Ensure customer satisfaction by meeting demand • Optimize cash flow by avoiding excess inventory The key is to continually monitor your safety stock levels and adjust them dynamically based on real-time demand patterns and supply chain conditions.

Ripped from the headlines... 𝗪𝗵𝗲𝗿𝗲 𝗱𝗶𝗱 𝗮𝗹𝗹 𝗼𝘂𝗿 𝗰𝗮𝘀𝗵 𝗴𝗼??? The business was in pain. Their cash was frozen in an iceberg of inventory. “We can see the mountain of cash tied up on the balance sheet, but we don’t know how it got there, and don’t know how to free it up.”   • They reached their borrowing limits.   • Softening orders killed cash flow.   • Their warehouse was bursting at the seams. The challenge: Unlock cash without sacrificing service levels. 𝗦𝘁𝗲𝗽 𝟭: Define the problem: Excess inventory tied up cash. 𝗦𝘁𝗲𝗽 𝟮: Gather data: Production, shipments, inventory, procurement spend. 𝗦𝘁𝗲𝗽 𝟯: Realize the disconnect: Sales underperforming, Procurement overbuying. 𝗦𝘁𝗲𝗽 𝟰: Take Action: Slow inflow, generate sales, and align procurement with actual demand. 𝗦𝘁𝗲𝗽 𝟱: Sustain Improvements: Implement a basic Sales & Operations Planning (S&OP) process In situations like this, when people are feeling the pressure, it's critical to take a calm and collected approach and focus on guiding the people through the process. We developed an S&OP process based on a deep understanding of the business's needs and sustained the gains, helping the team come up to speed quickly while facilitating significant organizational changes. The result: • 41% inventory reduction • Closed a warehouse • $𝟲.𝟗𝟯 𝗠𝗶𝗹𝗹𝗶𝗼𝗻 𝗶𝗻 𝗰𝗮𝘀𝗵 𝗳𝗿𝗲𝗲𝗱 𝘂𝗽 𝘄𝗶𝘁𝗵𝗶𝗻 𝗻𝗶𝗻𝗲 𝗺𝗼𝗻𝘁𝗵𝘀 In private equity, time is money. S&OP isn’t a theory—it’s a practical way to unlock cash, boost efficiency, and align teams without disruption. 𝗦𝗮𝗹𝗲𝘀 & 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝗴𝗲𝘁𝘀 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗮𝗹𝗸𝗶𝗻𝗴 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘁𝗵𝗶𝗻𝗴𝘀 𝗮𝘁 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘁𝗶𝗺𝗲. S&OP can solve the mystery... ... 𝙤𝙛 𝙒𝙝𝙚𝙧𝙚 𝘿𝙞𝙙 𝙊𝙪𝙧 𝘾𝙖𝙨𝙝 𝙂𝙤? 𝘞𝘩𝘢𝘵 𝘪𝘯𝘷𝘦𝘯𝘵𝘰𝘳𝘺 𝘤𝘩𝘢𝘭𝘭𝘦𝘯𝘨𝘦𝘴 𝘩𝘢𝘷𝘦 𝘺𝘰𝘶 𝘧𝘢𝘤𝘦𝘥—𝘢𝘯𝘥 𝘩𝘰𝘸 𝘥𝘪𝘥 𝘺𝘰𝘶 𝘴𝘰𝘭𝘷𝘦 𝘵𝘩𝘦𝘮? Hi, I'm Mike Ryan, and I help #middlemarket manufacturers solve #supplychain problems. If you found this helpful, follow me for more S&OP insights. Mike Ryan Founder Michael@MRyanGroup.com 330.283.7234 Next week... "𝘛𝘩𝘦 𝘍𝘰𝘳𝘦𝘤𝘢𝘴𝘵 𝘕𝘰 𝘖𝘯𝘦 𝘛𝘳𝘶𝘴𝘵𝘦𝘥!" #PrivateEquity #SOP #WorkingCapital #ManufacturingLeadership #EBITDA