Tim is currently the President & CEO of Agillitics, a technology solutions and consulting services firm based in Atlanta, GA.  Agillitics empowers companies to make data driven decisions to improve operational performance, enable innovation, and drive competitive advantage.

Certified: ►Supply Chain Professional (CSCP) ►PMP ►Lean Six Sigma Master Black Belt

Tim is experienced consulting and sales director with proven ability to manage large cross-functional teams, identify, design, implement innovative business solutions, and build sustained client relationships. Tim has a diversified background in retail, consumer products, e-commerce, automotive, industrial goods and services, logistics, and government. Tim also has a demonstrated ability to deliver results that have a measurable, positive impact on a clients’ bottom line while bridging the gaps between strategic vision, technological innovation, and operational execution.

Tim has designed innovative supply chains from the ground up and directed implementations across multiple verticals and  service offerings including Warehousing, Labor Management, Transportation, Order Fulfillment and Business Intelligence for a large list of clients/partners including:  FEMA (Federal Emergency Management Agency), DELL, AVON, Mary Kay, The Home Depot, Newell Rubbermaid, Republic National Distributing Company (RNDC), Donaldson Corporation, Siemens, Genuine Parts Company, Pendleton Woolen Mills, Orvis, Carter’s, Sigma Aldrich, etc.

Tim has an MBA and BS in Industrial & System Engineering from Georgia Institute of Technology.

Specialties: Supply Chain Management Strategy, Planning, and Execution (Warehousing, Transportation, Labor, Order Fulfillment, Material handling equipment, Business Intelligence, etc.), Project and Program Management, Performance and Process Optimization, Operations/Process Design, Risk Management and Mitigation, Strategic Management Consulting, and Change Management.

Tim Judge

🎤 What Not to Say at the Gartner Supply Chain Planning Summit
 ......If You Want to Get to the Good Stuff 😊 

The Gartner Supply Chain Planning Summit is where smart people say smart things.

But let’s be real, it’s also where a lot of surface-level fluff and supply chain jargon gets repeated on loop.

In Entrepreneur's Organization (or EO), we have a concept called 5%.

5% means to cut through all the BS, and focus on the transparent, clear, meaningful, valuable, deep, etc. of an idea, story, pitch, theory, that actually matters.

So, in the spirit of cutting through the 95% noise and getting to the real 5% that builds trust, insight, and connection,

Here’s a list of what NOT to say:

If you're a VENDOR, please don’t say:
 ❌ “Our platform does it all.”
 ❌ “Just layer AI on top.”
 ❌ “Integration is easy!”
 ❌ “You don’t need to worry about data quality.”
 ❌ “We’re in the Magic Quadrant... somewhere.”

If you're a SUPPLY CHAIN LEADER, please avoid these too:
 ❌ “Our data is fine—it’s all in spreadsheets.”
 ❌ “We’ll deal with AI after we finish our ERP upgrade.”
 ❌ “We just need one more dashboard.”
 ❌ “This is how we’ve always done it.”
 ❌ “IT handles that.”

💡 The truth?

You already know the real challenges.

Messy data, siloed systems, cultural blockers, and tech debt.

Let’s talk about that.

Because when we skip the script and focus on the 5% that actually matters, the entire conference gets better (for everyone)

👇 What phrase do you hope never to hear in Denver?

#GartnerSC #SupplyChain #SupplyCHainPlanning
#SupplyCHainManagement #DataDriven #AIMaturity #GartnerPlanningSummit #GartnerSupplyChainPlanningSummit
#RealTalk

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Rescuing Supply Chain Leaders Drowning in Data but Starving for Insights | CEO at Agillitics | Supply Chain Analytics

Information isn’t the advantage.
Action is.

And nowhere is that more obvious than in supply chain.

Most companies aren’t struggling because they lack data.

They’re struggling because their data isn’t usable, trusted, or timely enough to drive decisions.

We don’t need more reports.
We need faster insight → faster action.

That’s the real advantage.

When you turn raw supply chain data into:
	•	accurate OTIF alerts instead of static tables
	•	inventory risk signals instead of weekly spreadsheets
	•	labor performance insights instead of historical logs
	•	capacity constraints before they hit the floor
	•	exception-driven workflows instead of manual hunting

…you shift from simply knowing to consistently doing.

That’s when your planners move from reactive to proactive.

That’s when operations stop fighting fires.

That’s when AI stops being a buzzword and becomes a capability.

Because at the end of the day:

Information informs.
Insight moves.
Action transforms.

And the companies who operationalize their data are the ones who win. 💪

(7) Feed | LinkedIn

📊 50% of warehouse labor time is lost to non-value activities like searching, waiting, and walking.

📅 Data Point of the Day #143 – Saturday

🧠 Takeaway: The fastest gains come from removing wasted motion.

👶 Baby Chains: “Every step should serve the work.”

🐶 Bronxie the Bullwhip: “I walk enough to close my exercise ring by lunch!”

📌 Source: OPEX Warehouse Efficiency Benchmark 2025

💡 Real-world example: A regional 3PL cut wasted motion by 22 percent after redesigning travel paths and enforcing location accuracy. Throughput improved the same week.

❓ Where does wasted motion hide in your operation?

This GIF nails where most supply chains really are with AI right now 😂👇

Everyone wants “AI Agents” sliding in from the clouds. Meanwhile the enterprise is standing there with a 20-year-old WMS, siloed data, and inventory accuracy that swings like a mood chart.

We talk about AI like it’s magic. But AI is just math sitting on top of your data. If the data is wrong, the math gets weird fast.

What leaders expect AI Agents to unlock:
 • Network orchestration
 • Jedi-level demand sensing
 • Fewer expedites and firefights
 • A smoother path to EBITDA

What actually shows up:
 • Systems that don’t reconcile
 • Lead times built on tribal knowledge
 • Supplier data that only one person understands
 • Agents hallucinating because the inputs look like a DC after peak season

Here’s the truth:
AI isn’t failing. The data foundation is.

You can’t duct-tape AI onto broken processes and expect autonomy, speed, or accuracy. You get there by unifying the data, cleaning it, governing it, and making it accessible.

AI Agents aren’t the finish line.
They’re the reward for doing the hard work.

Fix the data first. Then bring on the agents. That’s when supply chain shifts from reactive to compounding.

📊 65% of warehouses use predictive analytics to forecast demand and optimize resources

📅 Data Point of the Day #126 – Wednesday

🧠 Takeaway: Predictive means fewer surprises, smoother shifts, and smarter slots.

👶 Baby Chains:  “Seeing ahead beats catching up.”

🐶 Bronxie the Bullwhip: “But I like guessing — it keeps things exciting!”

📌 Source:  Manhattan Associates -State of Warehouse Operations Report

💡 Real-world example: A 3PL used predictive analytics to anticipate inbound surges, cutting overtime hours by 18%.

❓ What’s one decision you’d automate if you trusted the forecast fully?

#SupplyChainAI #Forecasting #DigitalSupplyChain #WarehouseAnalytics #BabyChains #BronxieTheBullwhip

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📊 Over 90% of warehouses are adopting WMS or predictive maintenance tools by 2025.

📅 Data Point of the Day #130 – Sunday

🧠 Takeaway: Integration is now infrastructure.

👶 Baby Chains: “Connected systems create connected teams.”

🐶 Bronxie the Bullwhip: “Wait—so paper’s out of the network?”

📌 Source: Omniful / Clickpost

💡 Real-world example: A national distributor cut downtime by 28% after linking their WMS, fleet telematics, and equipment health data—creating a single, proactive visibility layer instead of three disconnected dashboards.

❓ Which system in your tech stack needs to ‘join the network’ next?

#SupplyChainAI #WMS #PredictiveMaintenance #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

(15) Feed | LinkedIn

🥈 Baby Chains Weekly Recap | The Silver Shift in Supply Chain

Silver is having its moment, moving from “precious” to “critical” as demand surges for solar, electronics, and renewable energy.

It’s a perfect reflection of what’s happening in supply chains: automation and intelligence are no longer optional luxuries… they’re essential materials for resilience.

This week’s key stats:
⚙️ The global warehouse automation market will double from $29.9B (2025) to $63.4B (2030)
📦 90%+ of warehouses are adopting WMS or predictive maintenance tools by 2025
🚛 22% of procurement leaders expect logistics costs to rise more than 10% this year
🏭 60% of manufacturers expect warehouse space needs to keep growing
👷 73% of warehouse managers can’t find enough workers
📈 65% of warehouses use predictive analytics to forecast demand
🤖 78% of warehouses are increasing investment in robotics

The takeaway:
As silver becomes critical to energy, data and automation are becoming critical to operations.
The supply chains that adapt fastest will shine the brightest.

#SupplyChainAI #DataStrategy #DigitalSupplyChain #BabyChains #BronxieTheBullwhip #WarehouseAutomation #PredictiveAnalytics #ResilientSupplyChain

📊 16% of Black Friday purchases are returned within the first 72 hours.

📅 Data Point of the Day #149 – Saturday

🧠 Takeaway: The return wave begins before the peak wave ends. Reverse logistics is now part of the weekend workload.

👶 Baby Chains: “A smooth return protects the entire cycle.”

🐶 Bronxie the Bullwhip: “I prepare for returns the same way I prepare for leftovers.”

📌 Source: NRF Holiday Returns Study / Loop Returns 2025

💡 Real-world example: A major apparel brand pre-slots return SKUs during Black Friday weekend, reducing processing time by 28 percent and keeping forward flow steady.

❓ How early do returns start to hit your network?

📊 Peak-season mis-picks increase by 22% when inventory accuracy slips below 97%.

📅 Data Point of the Day #150 – Sunday

🧠 Takeaway: Accuracy collapses fast under pressure. The strongest peak seasons come from the cleanest data.

👶 Baby Chains: “A stable inventory sets the tone for the entire shift.”

🐶 Bronxie the Bullwhip: “I can find anything… unless it moved.”

📌 Source: WERC DC Measures / DHL Picking Benchmark 2025

💡 Real-world example: A consumer goods DC raised accuracy from 96.4% to 98.1% before peak, reducing mis-picks enough to free an equivalent of six labor-hours per shift.

❓ Where does accuracy slip first when volume surges?

📊 By 2026, 75% of logistics firms plan to adopt intralogistics automation.

📅 Data Point of the Day #134 – Thursday

🧠 Takeaway: Internal flow is the next frontier of efficiency.

👶 Baby Chains: “The quietest optimizations make the loudest gains.”

🐶 Bronxie the Bullwhip: “Guess forklifts need performance reviews now!”

📌 Source: Logistics IQ 2025 / Omniful

💡 Real-world example: A national 3PL implemented AGVs for pallet transfers and saw 19% faster dock turns while lowering accident rates. The secret wasn’t speed — it was consistency in every move inside the four walls.

❓ Where in your operation could quiet automation deliver big impact?

#SupplyChainAI #Intralogistics #Automation #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

📊 The global warehouse automation market will double from $29.9B (2025) to $63.4B (2030).

📅 Data Point of the Day #131 – Monday

🧠 Takeaway: Capital is chasing flow.

👶 Baby Chains: “Automation is the new floor space.”

🐶 Bronxie the Bullwhip: “Maybe I should invest in conveyor belts…”

📌 Source: Clickpost 2025

💡 Real-world example: A national distributor avoided a $12M facility expansion after deploying robotic conveyors and automated sortation — boosting throughput per square foot by 37% without adding real estate.

❓ Are you investing in more space or more flow?

#SupplyChainAI #WarehouseAutomation #DigitalSupplyChain #Robotics #BabyChains #BronxieTheBullwhip

📊 54% of supply chain leaders say bottlenecks come from handoffs, not tasks.

📅 Data Point of the Day #138 – Monday

🧠 Takeaway: Flow breaks between teams before it breaks inside them.

👶 Baby Chains: “The handoff shapes the outcome.”

🐶 Bronxie the Bullwhip: “So we need a referee?”

📌 Source: Supply Chain Leadership Outlook 2025

💡 Real-world example: A nationwide distributor fixed a recurring dock delay by connecting purchasing, inbound, and warehouse teams through one shared ETA signal, cutting staging time by 23 percent.

❓ Which handoff creates the most friction in your operation?

#SupplyChainAI #FlowManagement #SupplyChainLeadership #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

📊 Gartner reports that only 8% of companies describe their planning process as “fully connected,” with most still juggling 20+ disconnected workflows.

📅 Data Point of the Day #152 – Wednesday

🧠 Takeaway: Planning breaks in the gaps between systems long before it breaks in the numbers.

👶 Baby Chains: “Connection creates clarity. Clarity creates confidence.”

🐶 Bronxie the Bullwhip: “My planning is connected too… mostly by sticky notes.”

📌 Source: Gartner Supply Chain Planning Survey 2025

💡 Real-world example: A global CPG brand reduced planning cycle time by 41 percent after replacing fragmented spreadsheets with a unified planning layer that synced demand, supply, and finance.

❓ Where does your planning process disconnect first?

📊 AI-enabled forecasting can reduce supply chain errors by up to 50%.

📅 Data Point of the Day #141 – Thursday

🧠 Takeaway: Better forecasts create better flow.

👶 Baby Chains: “Accuracy grows when AI guides the next move.”

🐶 Bronxie the Bullwhip: “If AI can cut errors, maybe it can fix my handwriting too.”

📌 Source: McKinsey – The State of AI in Supply Chain 2025

💡 Real-world example: A global apparel brand used AI-driven forecasting to align channel mix and replenishment timing. They cut out-of-stocks by 18 percent with no change in safety stock strategy.

❓ What error would you eliminate first with a smarter forecast?

#SupplyChainAI #Forecasting #AIinSupplyChain #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

📊 Every 5-point increase in forecast accuracy boosts service levels by up to 10%.

📅 Data Point of the Day #145 – Monday

🧠 Takeaway: Accuracy creates stability, and stability drives service.

👶 Baby Chains: “The right number sets the entire day on track.”

🐶 Bronxie the Bullwhip: “If I forecast snacks right, I never miss.”

📌 Source: McKinsey — The State of AI in Supply Chain 2025

💡 Real-world example: A national retailer improved store-level service by 8 percent after applying AI-based forecasting to replenishment timing.

❓ Where would better accuracy move your service the most?

📊 80% of 3PLs are investing in predictive analytics for supply chain operations.

📅 Data Point of the Day #132 – Tuesday

🧠 Takeaway: Data readiness is now a competitive service.

👶 Baby Chains: “3PLs win with foresight, not forklifts.”

🐶 Bronxie the Bullwhip: “Do forecasts come with a warranty?”

📌 Source: OPEX Guide 2025

💡 Real-world example: A regional 3PL used predictive analytics to anticipate customer volume spikes two weeks early. The result? 15% faster dock turns and zero missed SLAs — all before peak even started.

❓ What’s the next decision in your network that predictive analytics could make for you?

#SupplyChainAI #3PL #PredictiveAnalytics #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

📊 22% of procurement leaders expect logistics costs to rise more than 10% this year.

📅 Data Point of the Day #129 – Saturday

🧠 Takeaway: Inflation in freight hits faster than inflation on shelves.

👶 Baby Chains: “Every dollar unplanned is profit unpaid.”

🐶 Bronxie the Bullwhip: “Maybe we can just ‘negotiate’ gravity!”

📌 Source: CIPS Pulse Survey 2025

💡 Real-world example: A mid-market retailer saw freight costs spike 13% YoY even though store prices rose only 4%. The gap forced them to revisit routing guides, cube utilization, and carrier mix just to hold margins steady.

❓ Which cost bucket in your network is rising the fastest right now?

#SupplyChainAI #LogisticsCosts #Procurement #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

📊 The global AI-in-logistics market will hit $20.8B in 2025, growing about 45% per year.

📅 Data Point of the Day #133 – Wednesday

🧠 Takeaway: AI is no longer a pilot—it’s the platform.

👶 Baby Chains: “The question isn’t if AI fits, it’s where first.”

🐶 Bronxie the Bullwhip: “Think it can plan my lunch break?”

📌 Source: DocShipper 2025

💡 Real-world example: A global freight forwarder used AI-driven routing and ETA prediction to reduce demurrage fees by 31% and customer complaints by 40%. Once AI was embedded in daily operations, manual interventions almost disappeared.

❓ Where could AI quietly remove the most friction in your network?

#SupplyChainAI #Logistics #ArtificialIntelligence #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

📊 47% of distribution centers say their biggest productivity losses come from searching for inventory, not moving it.

🧠 Takeaway: Time disappears faster in the aisles than at the dock.

👶 Baby Chains: “Accuracy is the fastest path to speed.”

🐶 Bronxie the Bullwhip: “I swear this pallet was here yesterday.”

📌 Source: DC Operations Benchmark Report 2025

💡 Real-world example: A home goods distributor reduced search time by 29 percent after tightening location accuracy and cleaning up bin standards. Throughput increased the same week without changing headcount.

❓ Where does time slip away most in your building?

#SupplyChainAI #WarehouseEfficiency #InventoryAccuracy #DigitalSupplyChain #BabyChains #BronxieTheBullwhip

📊 Optimized slotting reduces pick-path travel distance by 27%.

📅 Data Point of the Day #144 – Sunday

🧠 Takeaway: Better slotting builds better flow.

👶 Baby Chains: “Travel time is the quiet tax on throughput.”

🐶 Bronxie the Bullwhip: “My slotting system is alphabetical… mostly.”

📌 Source: DHL Picking & Slotting Study 2025

💡 Real-world example: A consumer goods distributor re-slotted fast movers and cut pick travel by 19 percent without adding automation or labor.

❓ What is the biggest gap in your slotting strategy today?

Michael Myers

Lully

Founder & CEO

The Rubic

Advisor

Axial Innovative Solutions

Sales Marketing Consultant

Third Wave Automation

Director of Product Solutions

ODW Logistics

Engineering Manager

Industrial Engineer

Ryder Supply Chain Solutions

Supply Chain Engineer

Abercrombie & Fitch

o	Manhattan Labor Management implementation project owner
o	Build and develop labor standards for direct to consumer job functions via Maynard and discrete standards
o	Configuring labor management for current process flow
o	Creating Warehouse a map and coordinate system for LM functionality
o	Training management on labor management software utilization
o	Perform analytical process improvements for distribution operations
o	Built standard operating procedures (SOP) for Manhattan Labor Management Use

Associate Industrial Engineer

Big Lots

o	Completed task and unit of measure evaluations and performed time studies with the engineering team through Timer Study+ on iPad or Android device
o	Collaborated with engineering team to develop job standards and an associate incentive system
o	Provide support for Manhattan WMS and LM Go-Live to DC Operations team for associate performance and throughput evaluation
o	Coordinated with project management team for Manhattan Warehouse Management and Labor Management software configuration by creating and updating tasks, events, employees and locations within the software environment.
o	Reduced engineering labor hours by 10 hours per week by creating an excel macro workbook to automate data analysis and entry from Quetech Timer Study+
o	Developed testing hierarchy and procedures for the implementation of Manhattan Warehouse Management and Labor Management Software. 
o	Performed tests against WMS and LM for data quality and integrity.
o	Documented Manhattan WMS and LM issues using HP Quality Center and Atlassin JIRA Issue Management software
o	Created DC supervisor standard operating procedures for Manhattan WMS and LM user interface

Industrial Engineering Intern

Father, husband, workaholic obsessed with warehouses

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