Dave Crysler kicks off a three-part series with Cody Fisher, President of Concordance Innovations, to unpack the real challenges facing the healthcare supply chain. In this first episode, they dig into why the industry struggles with data trust, how organizations get trapped in analysis paralysis, and what it actually takes to drive change in one of the most complex supply chains in the world.

What You'll Discover:

• Why healthcare supply chains can't benchmark themselves against retail or automotive, and what makes the stakes fundamentally different
• How data distrust cascades through every decision, from ordering to inventory to forecasting
• Why waiting to "clean your data first" is a trap that keeps organizations stuck for years
• The real fear behind AI and automation adoption: are we just speeding up bad processes?
• Why optimizing for cost and maintaining resiliency aren't tradeoffs in healthcare, they're both non-negotiable
• How flipping the question from "why should we change?" to "what happens if we don't?" creates breakthrough moments
• The shift from squeezing contracts and price to creating value through operational change
• What leadership characteristics actually drive innovation, and why the best leaders are great storytellers

Whether you lead supply chain operations in healthcare or any industry wrestling with complexity, data challenges, and the pressure to modernize, this conversation will ground you in the realities that matter before the solutions make sense.

Dave Crysler breaks down one of the most expensive, invisible problems in manufacturing operations: competing sources of truth. Using a real example from a print manufacturer running three parallel systems, Dave walks through what happens when leadership never declares which system is the master, and why the resulting chaos costs six figures before anyone even notices.

What You'll Discover:

• Why "which number do we use" is probably the most expensive question in your organization
• How a print manufacturer's MIS, accounting tool, and paper job tickets created a no-win invoicing nightmare
• The two types of people who suffer most when sources of truth compete, and why both cost you on different timelines
• Why this is a leadership decision, not a technology problem, and the critical difference between having one system and having one master
• How people gravitate toward whichever system gives them the convenient answer in the moment
• Why companies that grow through acquisition face a multiplied version of this same problem
• The crawl step most leaders skip: why you audit before you decide, not the other way around
• How to designate a master source of truth and enforce it through Clarity, Consistency, and Accountability

If your team spends more time questioning where a number came from than acting on what it means, this episode will change how you think about the systems running your business. The tools are rarely the problem. The absence of a decision is.

Dave Crysler sits down with Sharon Custer, founder of Inventory Optimization Pro, to unpack why so many manufacturers trust their system numbers while their warehouse tells a completely different story. Sharon spent years in inventory strategy inside a Fortune 100 manufacturer before launching her own practice, and she brings real examples of how misaligned data, inconsistent naming, and siloed thinking quietly erode cash flow and operational performance.

What You'll Discover:

• Why a 100% inventory count can still leave you with stock-outs and overstock at the same time
• How SKU naming inconsistencies create ghost inventory that ties up cash and tanks your reporting
• The real cost of "deferred explanations," inventory adjustments that never get to root cause
• Why your demand forecast is probably built on false data, and how stock-outs and promotions distort the numbers
• How to gold-tag a single order and track its full journey to expose hidden margin leaks
• Why treating inventory like cash, and cycle counting like bank reconciliation, is the foundation for accuracy
• Where AI actually helps with inventory operations, and why clean data has to come first
• How siloed thinking between finance, operations, and purchasing means everyone is looking at the same system but drawing different conclusions

If you are running inventory-based operations and wondering why the numbers never quite add up, this conversation will help you see where the real problems are hiding, and what to do about them starting this week.