How to Pilot Robotic Systems Successfully

A warehouse stuck in ‘pilot mode’ isn’t learning, it’s losing. Pilots feel safe. Low commitment. 'Let’s test this robotics system here and see what happens.' But here’s what I see in real warehouse automation projects: Pilots run for months, sometimes years. Operators get tied up supporting the pilot instead of fixing core issues. Vendors never get a true picture of scale because the system lives in a bubble. And the cost is bigger than the invoice: Labor drag - operators babysit the pilot alongside their day job. Cultural drag - teams stop believing warehouse robotics will ever 'stick.' Financial drag - investment gets tied up without building capability. And two truths people avoid saying out loud: 1. Pilots are often led by Innovation teams with great intentions. But if ownership shifts to Ops, IT, or Engineering mid-stream, it falls flat - those teams already have 20 other projects. 2. Robotics pilots aren’t free. They involve hardware, software, and people. Vendors can’t absorb those costs forever 'hoping' scale will come. If scale is the goal, clients need to set clear deliverables and KPIs upfront. ➡️Guidance if you’re in this spot (bookmark this): 1. Define the finish line - What does 'go / no-go' look like before the pilot begins? 2. Limit the time box - 90 days is plenty to prove scale potential. 3. Keep ownership clear - Don’t hand it off mid-stream; align cross-functional support from day one. 4. Set mutual KPIs - Vendors and operators both know what “success” means. In warehouse automation, a pilot that never ends isn’t safer, it’s more expensive. Decide fast, scale what works, and stop what doesn’t. ------------ I work with operators and executives to build automation readiness playbooks that prevent pilot fatigue and set up robotics programs to scale. If your team is facing this, let’s connect. ------------ #WarehouseAutomation #WarehouseRobotics #PilotMode #AutomationStrategy #SupplyChainExecution #OperatorFirst

Stop counting people. Start counting what you deliver for every dollar. Illustration: A regional warehouse keps missing ship times. Three handoffs. One re-check loop. Overtime spikes. SLAs slip. Then they change one lane: Same team. Two small cobots. Two handoffs removed. Clear owner for the flow. Orders per shift go up 28%. Errors fall. Cost per order drops. Fewer 2 a.m. saves. That’s “throughput per dollar.” Customers feel it as speed and fewer mistakes. Boards see it as lower cost per outcome. Both matter. Where teams go wrong: • Automate steps but keep the same handoffs. • Track hours and headcount, not output. • Buy robots without redesigning the flow. • Reward “savings,” not reliability. Do a 30-day pilot: 1. Pick one workflow end to end (pack → label → ship, or intake → triage → resolve). 2. Time every step. Mark waiting, rework, handoffs. 3. Remove two handoffs. Let software/cobot do repeats; keep humans on exceptions and judgment. 4. Name one owner for the whole flow. 5. Measure four things: • Units per hour per dollar • First-pass yield (no rework) • Response time • Tickets/injuries/overtime Add guardrails: • Safety first. Clear stop rules. • Train for new roles (exception handling, quality). • Maintenance plan and spare parts. • Fallback if the robot or model fails. What to stop doing: • “Utilization” dashboards that hide customer pain. • Headcount cuts without flow redesign. • Chasing full automation when a hybrid wins now. This isn’t about replacing people. + It’s about designing smarter teams. + Let AI/robots handle repeats. + Let humans use judgment. + Raise what you deliver per dollar - on the floor and in the boardroom. 📩 Rewiring ops for “throughput per dollar” with AI + robotics? Let’s talk. 📬 Subscribe to BRIDGE: https://lnkd.in/gCdavukQ ♻️ Repost if your teams still count heads instead of outcomes ➕ Follow Adi Agrawal | Bridge the Gap

MIT: 95% of Gen-AI pilots are failing. Here’s what the 5% winners do differently (steal this): 1. Start with work, not with models. Winners redesign jobs and workflows before they ship bots. Tooling follows a process, not the other way around. 2. Tie “individual value” to “org value.” If employees don’t feel AI making their work easier, the org won’t see returns. Make competence, autonomy, and collaboration the first-class metrics. 3. Go narrow, then scale. Document a few repeatable use cases (claims triage, reconciliation, collections) with unit-economics, then templatize. IBM and others have long warned: the hard part is scaling, not the POC. 4. Measure real productivity lift. In support, gen-AI has shown ~14% productivity gains at scale, with the biggest boost for junior reps. Instrument your pilots to prove (or kill) value fast. 5. Invest in org learning. Top performers combine AI learning with organizational learning, training, feedback loops, change management: not just prompt libraries. 6. Data + governance ≫ model of the month. Most stalls are from data quality, integration, and risk controls, not “we need the newest model.” Treat AI as infrastructure (monitoring, access, privacy), not a feature. A ruthless pilot checklist (copy/paste it): - Clear problem owner with P&L accountability - Baseline + target unit economics (AHT, defect rate, $/ticket…) - Change plan: job redesign, SOPs, training, incentives - Observability: evals, drift, hallucination gates, feedback loops - Scale plan: integration into systems of record; security sign-off If your AI pilot isn’t changing how work is done, it’s not a pilot, it’s a demo with better lighting

When we say "turnkey," we don't mean "here's your robot, good luck." We mean we're giving you the keys to a system you can actually run. Most integrators deliver hardware and disappear. You're left figuring out training, safety protocols, and how to keep it running. That's not turnkey. That's expensive equipment transfer. Real turnkey integration means multiple teams working in parallel: - custom tooling design, - training curriculum development, - career development partnerships with FANUC America Corporation or else, - safety assessments, - and full systems integration. Because here's what I've learned: the robot is the easy part. Getting your people competent with it, keeping them safe around it, and ensuring it runs in your environment—that's where projects succeed or fail. At Kinetic Technologies LLC, we don't hand off cells we wouldn't run ourselves. When you get the keys, you're getting a system that's ready for production, not just installation. The difference between a robot installation and a production-ready system is everything that happens around the robot. #automation #manufacturing #turnkey  #training  #robotics  #safety