Let's Talk Supply Chain

Wes Coleman & Matthew Fehrenbach of Zebra Technologies on automation, frontline workers, supply chain innovation & the future of intelligent operations.
IN THIS EPISODE WE DISCUSS:
[02.32] An overview of Zebra Technologies today: who they are, what they do, and the challenges they help their customers solve.
"We're working every day to make businesses as smart and connected as the world we live in… Our goal is to give organizations enterprise asset intelligence. In a world of supply chain and retail complexity, we're helping our customers bridge the gap between high level strategy and daily frontline execution."
[04.43] From new product launches to a pivotal acquisition, the key milestones that have shaped Zebra Technologies since its founding in 1969.
[06.38] The acquisition of Motorola Solutions' Enterprise business, what it brought to Zebra, and how it expanded the solutions they could offer customers.
"The acquisition instantly doubled our size, and transformed us into an end-to-end workflow solution provider."
[07.52] Zebra's technology in action, and how it fits into customers' day-to-day workflows.
[12.30] How Zebra's customers approach new technology and automation, balancing enthusiasm for innovation with the practicalities of turning it into tangible results.
"Many customers think of things as individual components, like asset tracking with RFID, automating processes with machine vision, or predicting bottlenecks with generative AI. We try to guide them to stop viewing them as separate hardware components and, instead, treat them as an ecosystem."
[15.09] From asset tracking and inventory visibility to reduced shrinkage and improved worker engagement, the key outcomes retailers look to achieve with Zebra's solutions.
"Often retailers know they have a problem, they know what the problem is, but they're ensure what the options are for a solution."
[17.16] What asset tracking means for Zebra and its customers, and the value it delivers to their operations.
[18.29] An overview of Zebra's machine vision solutions and how they help customers improve quality, accuracy and operational efficiency.
[21.33] The ideal customer profile for Zebra Technologies and the operational challenges its solutions are best placed to tackle.
[23.14] Why Zebra champions an 'augmented workforce' approach, empowering frontline workers through technology and exploring how humans and automation can work together to improve operational performance.
"Up until a few years ago, being replaced was a real concern for workers. But we've seen that change. Now workers have great tech in their pocket, in their car, at home. And when they get to the workplace they also have an expectation for excellent technology."
[26.28] The evolving landscape of supply chain and frontline operations, the challenges and opportunities shaping the industry, and how customer priorities have shifted over the past five years.
"Customers are asking for orchestration and, five years ago, that meant something completely different."
[32.07] Looking ahead, Zebra's vision for the intelligent supply chain and the role it aims to play in helping customers realize that future.
"The future of retail supply chain is about removing that dock door – both figuratively and literally."
RESOURCES AND LINKS MENTIONED:
Head over to Zebra's website now to find out more and discover how they could help you too. You can also connect with Zebra Technologies and keep up to date with the latest over on LinkedIn, Facebook or YouTube, or you can connect with Wes or Matthew on LinkedIn.
Check out our other podcasts HERE.

Kris Gosser & Tim Meester of Shipium explore the four eras of freight audit, AI startups, the control era, and how Always-On Audit impacts your bottom line.
IN THIS EPISODE WE DISCUSS:
[02.39] Freight audit and pay's 120-year history, the problem it was originally created to solve, and why its fundamental approach has changed so little over time.
"Early on, it was about checking a bill against a tariff. Then, industry's got deregulated, things got more complicated, and the tools and processes got better – but the starting line never moved."
[05.46] The four eras of freight audit – Payment, Audit, Data and Control.
[12.35] How the traditional gain-share audit model works and why it can create incentives around recurring carrier billing errors.
"The model rewards finding over fixing… You can't audit your way out of a problem you keep shipping into."
[16.51] Why, despite seeing the same freight billing errors recur for decades, the industry has yet to address their root causes, and what has prevented a shift towards a more proactive, upstream approach.
"The technology in the 90's was built for the assumptions of the simplicity of the network… Now we have an infinite set of destinations, an infinite number of SKUS and permutations of packaging… parcel went from 4% to 40% of your volume – and the technology never caught up."
[23.51] What the new wave of AI-powered freight audit startups are genuinely improving, and why they're the last chapter of the data era rather than the beginning of a new era.
[29.34] The distinction between knowing that a shipment was wrong and being able to do something about it while the shipment is still in motion, and why timing matters so much in freight spend.
"We're moving from archeology to forensics."
[37.42] The 'control era' – what changes when you move from auditing shipments after the fact to actively controlling them in real time, why the control era requires the system of record for shipping data, and the importance of upstream visibility in preventing errors before they occur.
[43.31] How Shipium Compass and Always-On Audit work together to drive customer success, what logistics and transportation leaders should be doing now, and the key capabilities to look for when investing in technology.
"It's managing your carrier spend and the finance side of it, but it's also your carrier relationships. How do you create clarity and reduce friction?"
[50.44] What becomes possible when the industry moves beyond 120 years of looking backwards through freight audit to proactively controlling shipments, preventing errors, and shaping outcomes before they happen.
 
RESOURCES AND LINKS MENTIONED:
Head over to Shipium's website now to find out more and discover how they could help you too. You can also connect with Shipium and keep up to date with the latest over on LinkedIn, or you can connect with Kris or Tim on LinkedIn.
If you enjoyed this episode and want to hear more from Shipium, check out :
564: Discover Why Peak Season Is A Margin-Making Event, Not An Ops Event, with Shipium
502: Current Success vs Future Potential: Finding the AI Balance, with Shipium
491: 2028 – Shipium Counts Down to the AI Revolution
299: Modernize Your Ecommerce Supply Chain, with Shipium
Check out our other podcasts HERE.

Scott Jennings of Anaplan talks about operationalizing AI in planning, eliminating latency tax, the shift to autonomous multi-agent systems, & your next steps. 
IN THIS EPISODE WE DISCUSS:
[02.52] Scott's role at Anaplan, what they do, and their ideal customer profile.
"If you're not collaborating, you're going to get stuck in siloes - and that's what we hear from companies time and time again. It's that ability to collaborate with your peers, and with all the different technology that's available, that determines success or failure."
[04.38] From use case selection and success criteria to cost, why – despite huge investment in AI experimentation – many organizations are still struggling to demonstrate tangible business value, and why 2026 is the year of change when it comes to businesses moving from AI experimentation to proving ROI.
"Companies are beginning to ask questions, about trade offs – did they pick the right use cases to experiment with AI? They're not sure. Did the experiment work, and can it be scaled?  They're not sure. And then the bill comes, and it turns out that tokens are expensive."
[08.10] What 'AI ROI' actually looks like in planning, and the metrics executives should be looking at to know whether an AI investment is genuinely paying off.
"Finance talks a lot about working capital, but the moment you move to supply chain you're talking units. Bringing those two concepts together, so you can understand the financial impacts across the board instantly, is what's been driving most of the AI projects I've seen."
[12.18] Why planners are often reluctant to rely on AI recommendations, and what organizations need to do to move from a 'black box' to a more explainable, transparent approach.
[15.56] Why 'AI for AI's sake' can actually create more problems, and why it's critical to ensure your data is ready for AI use.
"When you think about AI, you want to think about what's going to drive the big metrics that are important to your organization, and then work backwards. What you don't want to do is just start running AI projects… sometimes the cost is higher than running the exact same project with humans!"
[20.17] The importance of real-time planning, the cost of the 'latency tax' when decisions are delayed because data, teams and systems aren't connected, and how significant that impact can be for large organizations.
"You can lose 5 cents on every dollar due to decision delay. And that's millions of dollars for a large company."
[23.43] Why a common business ontology and semantic layer are critical in helping AI understand how demand, supply, inventory, capacity and financial outcomes are connected to drive more effective results.
"Ontology is a map of your business that AI can use to better understand how it operates, because AI needs to be told a lot about your business to be effective."
[26.40] How an AI system can move from identifying a change in demand to understanding its implications for things like bills of material, plant capacity, lead times, inventory buffers and ultimately the P&L.
[30.09] How organizations should think about combining probabilistic AI – for things like demand sensing and pattern recognition – with deterministic calculation engines for financial math, rules and governance.
[34.48] How the role of the planner shifts when AI stops simply answering questions and begins continuously monitoring the business, generating scenarios and routing exceptions for people to act on.
[37.23] Multi-agent AI systems – what a world of specialized AI agents look like in a planning environment, and where humans should remain in control.
[41.11] What organizations should be looking for in a planning platform, and the importance of capabilities like an embedded calculation engine, business-owned models, connected data and native AI.
"From an agentic AI perspective, you have to have a deterministic and scalable calculation engine with purpose built supply chain planning models that are connected to all relevant internal and external sources."
[44.05] How organizations can identify a high-value planning use case, prove ROI quickly, build trust and scale AI across the enterprise.
 
RESOURCES AND LINKS MENTIONED:
Head over to Anaplan's website now to find out more and discover how they could help you too. You can also connect with Anaplan and keep up to date with the latest over on LinkedIn or YouTube, or you can connect with Scott on LinkedIn.
If you enjoyed this episode and want to hear more from Anaplan, listen to 514: Turn Strategic Planning Into Retail Profitability, with Anaplan or 499: Navigating the EV Revolution, with Anaplan.
Check out our other podcasts HERE.

Bryan Keller of Keller Logistics Group talks about what they do; preserving a family-business culture; & the challenges & innovations defining logistics. 
IN THIS EPISODE WE DISCUSS:
[02.22] Bryan's journey in the Keller family business, from summer internships to CEO.
[07.07] Keller's near 50-year history, how and why the company was founded, and the biggest turning points that transformed Keller from a trucking company into a full logistics provider.
[11.47] An overview of Keller – who they are, what they do, and how they help their customers.
"I've looked at customer diversification, service diversification, geographic diversification – all for us to remain a privately-owned company for the next 100 years."
[15.27] The ideal client profile for Keller Logistics Group.
[17.29] The challenges customers typically see day-to-day, and how Keller supports them through disruption.
"The reasons for the disruptions are different, but they cause the same issues… You've just got to know how to react to that volatility, and create solutions for your customers where they can have a variable cost structure. Because no-one wants to pay for a truck that's not working or empty concrete."
[18.47] Keller's approach to working with customers to tackle challenges and design the right solutions.
[20.16] A case study exploring how Keller helped a key client find the right balance between spot price and dwell time to save them $800,000.
[22.15] The most exciting logistics innovations changing the landscape right now, and in the future.
"What's exciting is the data we now have… It's taken a lot of noise out of the equation, so we can now really work on making the supply chain more efficient. Where we need to go next – dynamic scheduling."
[25.41] What differentiation looks like for Keller and how that, in turn, creates competitive advantage for their customers.
"Our go-to-market strategy is: how can we save our customers money? How can we create that raving fan?!... Some of our competitors are looking to generate margin, looking at each deal as a one-off, not as a lifecycle."
[28.43] Why Keller's mission centers their people and community just as much as their customers, and how they preserve a family-business culture as the organization grows.
"It's the Keller 'Circle of Life' – we deliver for our people, they deliver for our customers, and we give back to the community to enrich as many lives as possible."
[33.07] The challenges and potential technology innovations that will shape the future of logistics.
"What's AI going to bring to the table?"
RESOURCES AND LINKS MENTIONED
Head over to Keller Logistics Group's website now to find out more and discover how they could help you too. You can also connect with Keller Logistics Group and keep up to date with the latest over on LinkedIn, Facebook and X (Twitter), or you can connect with Bryan on LinkedIn.
Check out our other podcasts HERE.

Michael Rentz of Gnosis Freight talks about where organizations are quietly losing money & moving beyond visibility to turn logistics data into cost savings. 
IN THIS EPISODE WE DISCUSS:
[02.50] Why logistics technology is still treated as a cost center, rather than something that can directly improve margin, and how to make that shift.
"If you have the right teams, mindsets and technology partner, you can get to a point where it's not a cost center, it's a growth center."
[07.49] What changes when a supply chain leader starts looking at logistics data through a P&L lens rather than an operational one.
"During the pandemic, for the first time probably ever, we had CFO's asking: "What the hell is demurrage and detention?!"
[11.27] Where companies are typically losing money in their logistics operations.
"A lot of enterprises have had to make up a for a lack of reliability, and that translates into carrying more inventory… How much it costs to move goods is also at a premium."
[15.07] How you connect operational events – like a delayed container, missed free time or an inefficient dray move – to their actual impact on landed cost, the value of data, and the problem with the 'flaw of averages.'
[17.58] How, from documentation to communication, small operational issues can easily multiply to become significant margin problems.
"A best in class standard for an international logistics team is 'Did we hit budget?' I'm not familiar with people asking 'Did we beat budget?'
"Your most valuable assets – your people – are being asked to do the exact same task in a slightly different way 50 times a day. How much better could the system be running if you freed up that headspace for them to think critically on behalf of the business?"
[19.51] Why we need to think differently about KPIs and budgets if we're going to see supply chain as a value driver not a cost center, and where team priorities fit in.
"You have to get teams off the back foot, from a defensive to offensive posture; get them back into doing the work that's actually in their job description."
[27.46] How better data can help resolve invoice errors and help companies identify and recover money they're currently leaving on the table.
"Invoice discrepancies shouldn't be a driver for profitability or growth, you should always get what your bargained for… AI has unlocked a huge amount of capability when it comes to reconciling matching invoices. The key unlock for us is having the underlying data."
[30.41] The key metrics you should put in front of a CFO to prove that better logistics data is delivering a real financial return, and how Gnosis helps customers, through data science, tooling and service, with an outcome-first approach.
[40.26] Finding the balance between AI and tribal knowledge, why it's important to think about how dynamic your data really is, and why context is critical.
RESOURCES AND LINKS MENTIONED:
Head over to Gnosis Freight's website now to find out more and discover how they could help you too. You can also connect with Gnosis and keep up to date with the latest over on LinkedIn, Instagram, Facebook and X (Twitter), or you can connect with Michael on LinkedIn.
If you enjoyed this episode and want to hear more from Gnosis Freight, check out 559: From AI Hype to Business Value: The Future of Supply Chain Intelligence, with Gnosis Freight.
Check out our other podcasts HERE.