Adam Horsman

Warehouse chaos is costing you deals. Last quarter, a Bay Area supply chain team faced relentless delays. Orders backed up. Costs spiraled. Customer complaints flooded in. Their warehouse looked like a maze—overflowing, error-prone, and impossible to scale. Ninety days later, everything changed. We re-mapped their space, tuned their fulfillment systems, and upgraded 3PL oversight. The result? 30% faster fulfillment. 25% lower costs. 20% happier customers—without hiring, or ripping out their tech stack. If your team is fighting daily fires instead of scaling, let’s talk about what a 90-day transformation could unlock for you. Ready to see your own before-and-after? 🚀

2

"Our WMS doesn't track more than 1 or 2 pack types per SKU, and our vendors keep changing packaging." I heard this exact pain point on three different prospect calls last week. It’s a great example of issues we see crushing fulfillment efficiency. Here's what's really happening:  ❌ Legacy WMS can only handle basic pack configurations ❌ Vendors change packaging specs frequently ❌ Operations teams scramble to manually adjust everything ❌ Errors multiply, costs skyrocket Our approach is different. Logiwa IO uses a 4-level package hierarchy (Unit, Pack, Case) plus irregular pack types for when vendors inevitably change specs. No professional services fees. No months-long customization projects. Companies stuck with $100K-$500K customization costs and 6-18 month implementations are missing the point. Modern fulfillment needs flexibility, not expensive band-aids. The real question: Are you solving fulfillment problems with software optimization, or just throwing hardware at legacy system limitations? #FulfillmentTech #WMS #LogiwaIO #PackagingOptimization #SupplyChain

35

1 Comment

If I had $1.5M in pre-production funding, and I wanted to actually nail my first pilot run, then ramp to scale production with my first commercial volume shipments - high margins, zero failure rates, and every deadline hit— Here are 5 things I ABSOLUTELY WOULDN’T do if I wanted to get there: 1. I WOULDN’T treat the pilot run as a formality. This is where most founders torch their budgets. Your pilot run is not a box you check before scaling—it’s the moment you find out if your design can survive real-world production. Tolerance drift, thermal failures, and defects that look harmless in the lab will bury you in the field. If you gloss over this, your first scale run will eat you alive. 2. I WOULDN’T underprice my manufacturing just to make the margins look pretty on a pitch deck. Every founder believes they’ll be the exception. That their project will be the one where the cheap quote holds up. It won’t. When you squeeze your suppliers to the bone, you get silent shortcuts, missed deadlines, and problems nobody admits until you’ve already wired 80% of your budget. If you want predictability, you have to pay for it. Period. 3. I WOULDN’T stay loyal to a factory that can’t evolve with me. It feels good to believe the first partner who helped you build a prototype can handle scale. Most can’t. If your supplier can’t hold tolerances at volume or won’t upgrade their process, you have to move on—before it’s too late to fix it. 4. I WOULDN’T assume a perfect prototype equals a production-ready product. Your first samples are the easy part. Scaling to 10,000 units is where everything you missed gets exposed: - Thermal loads you didn’t simulate - Tooling drift that trashes yield - Processes that fall apart when the schedule gets real You don’t get a second chance to earn customer trust. 5. I WOULDN’T let my funding round lull me into believing I’m immune to failure. When you have $1.5M in the bank, it’s easy to believe you can buy your way past operational discipline. You can’t. More capital just means you get to fail at scale. TAKEAWAY Most founders think the hard part is getting funded and building a prototype. It isn’t. The hard part is scaling it—on time, at spec, under real pressure, when nobody’s watching. The market is set up to reward big launches, viral press, and the illusion of momentum. But hardware doesn’t care about your headline. It cares whether your product actually works. If I were building today, I’d treat the pilot run and the first scale production as life-or-death. Because that’s exactly what it is. 👊🏻

14

Thinking about replacing your WMS to improve performance? You might be solving the wrong problem. Most WMS platforms manage transactions, not optimization. They don’t fix: • Excessive travel • Congestion in pick zones • Labor imbalance • Inefficient slotting These commons issues are what actually slow DCs down. So the question is: Is it the system, or the way the operation is optimized? Top-performing facilities aren’t replacing their WMS, they’re working with MTE to automate the optimization of how work flows. What’s the biggest constraint in your operation today? #slotting #warehouseexecution #warehouseautomation #mte

4

"Why is 42% of our shipping spend going to expedited orders?" "What's our true margin by customer after factoring in raw material costs, tiered pricing, and marketing spend?" "Which SKUs are profitable at MSRP but underwater at our wholesale pricing tiers?" "What's our real cost of goods sold when you include packaging, freight, and channel fees?" These are the questions that actually drive decisions at a CPG or e-commerce brand. And none of your current tools can answer them. Not on their own. Your accounting system sees revenue and costs — but only after the fact. Your bill of materials system knows raw material pricing. Your shipping platform knows logistics spend. Your POS system knows transactions. Your marketing tools know ad spend and ROAS. Your marketplace channels take their cut and report what's left. Each one sees its slice. None of them see the full picture. So the real questions — the ones about SKU profitability across pricing tiers, customer contribution after all costs, root cause analysis on margin erosion, plan vs. actual before it hits your books — those questions fall into the gap between systems. And that gap is where most mid-market companies are flying blind. You can do this analysis manually. Pull data from five systems, clean it, join it in Excel, run the calculations. It's possible. But it's not repeatable. And by the time you finish, the numbers have already changed. An AI agent that connects across your data sources does this differently. You ask the question in natural language. The agent figures out which systems it needs — your accounting data for revenue, your BOM system for material costs, your shipping platform for logistics, your CRM for customer segmentation. It pulls the data, writes the code to aggregate and calculate, and delivers the answer in a format you can actually use. The first time you ask a complex question, the agent works through it step by step. But once the answer is validated, that becomes a saved skill. Next time anyone on the team asks something similar, it runs instantly. Over time, you're building an institutional library of every analytical question your company has asked and answered well. This is the difference between AI features bolted onto individual SaaS tools and an agent built on your data infrastructure. The SaaS AI only knows what its own platform sees. The agent connects everything — and answers the total cost of ownership questions that no single system can touch. You don't need another dashboard. You need something that connects all your systems and answers the questions none of them can answer alone. #AIStrategy #EnterpriseAI #FinanceAI #CPG #BusinessIntelligence #DigitalTransformation

10

2 Comments

Most retailers think their RFID "failed" when the real problem was never the technology. Here's what we've found after helping hundreds of retailers: The biggest mistake? Choosing cheap labels to "save money." We regularly see companies using $0.03 labels that can barely be read from 3 feet away. Then they blame RFID when their inventory counts are still a mess. The shift: Quality labels with proper RSI ratings and Arc approval aren't an expense. They're insurance against inventory chaos. Here's what to do right now: Check your label specifications. If they're not Arc-approved or have read ranges under 10 feet, you're fighting an uphill battle. We've seen retailers go from 65% inventory accuracy to 99%+ simply by switching to proper labels and calibrated systems. The reality? Your inventory problems aren't technology problems—they're implementation problems. Want to know if your RFID system can be saved? Comment "GUIDE" to get our free RFID Troubleshooting Checklist. This step-by-step guide helps you identify exactly what's broken in your current setup and whether it's worth fixing or time to start fresh.

16

Most inventory tech hasn't evolved past the 1990s. Manual counts, barcode scanners, wishful thinking about accuracy. Look at the chart below. Manual systems score "poor" across every metric that matters.  Other technologies barely reach "fair." That's exactly why we built DexoryView from scratch. The real innovation isn't making old systems slightly better. It's rethinking what inventory intelligence looks like with autonomous robots and AI that actually understands warehouse operations. DexoryView Optimise hits "excellent" where traditional systems can't function. 100,000+ pallet locations mapped daily with 99.5%+ accuracy. The industry keeps patching legacy systems with modern expectations. We built the future instead. That's innovation leadership, not following trends, but making everyone else's approach obsolete.

39

3 Comments

Produceplan today isn’t just software. It’s an operating system for the fresh food supply chain. Produceplan was built by produce people first—people who’ve lived the chaos of harvest windows, grower settlements, inventory mismatches, shrink, claims, recalls, and razor-thin margins. Software came second. That’s why Produceplan is an all-in-one, vertical platform purpose-built for fresh produce—not a generic ERP retrofitted to agriculture. From field to facility to final customer, Produceplan connects: Growers & grower-shippers Packers & repackers Brokers & distributors Inventory, logistics, and financials Real-time P&L down to the field, block, or lot Native traceability and compliance built into daily workflows No duct-taped systems. No spreadsheets in the shadows. No guessing where the profit went. We don’t start with features—we start with pain points. We don’t chase trends—we solve operational realities. And we don’t build for software demos—we build for harvest day. What’s coming in 2026 is a natural extension of that same philosophy: Integrated financing designed specifically for fresh food operators Workforce & labor management aligned to harvest, packing, and repack realities Embedded payments to move money faster and reduce friction across the supply chain Deeper automation, smarter insights, and fewer manual touchpoints—everywhere it counts Not bolt-ons. Not third-party patchwork. Built into the same operational backbone our users already rely on. Produceplan exists for one reason: To give fresh food operators real-time visibility, real accountability, and real control over their supply chain—so they can make better decisions while it still matters. >Produce first. >Operations first. >People first. Software just happens to be the tool.

9

1 Comment