Former HP executive and Dscoop board member Roy Eitan opens conversation with an analogy from his HP Indigo days. Years ago, pilots carried printed flight manuals filled with information intended to prepare them for what might happen along a route. Today, flying an airplane using only static information would seem unthinkable. Roy challenges print leaders to consider a similar question about their supply chains: If demand, materials, costs and delivery conditions continually change, why rely on a static spreadsheet to decide what comes next?
For Trevor Spring, an experienced supply chain executive who has worked with major food and restaurant brands, that question hits close to home. He spent years working from what he calls a "big, beautiful, very fragile spreadsheet" that only one or two people truly understood. When a supplier slipped, a forecast missed or a large order moved, his team spent its time reacting. Trevor sees strong parallels with print: Both businesses are deadline-driven, operate under margin pressure and can lose the value of an order when the right materials aren't available at the right moment. "The plan is a static snapshot, and then reality moves," he said. "And by the time the spreadsheet catches up, you're reacting instead of deciding."
Tamar Weiser, founder and CEO of Hexight, believes companies can approach that uncertainty differently. Her team developed an AI-native planning platform designed to evaluate multiple possible futures rather than depend on a single forecast. Tamar describes the goal as becoming "risk-aware": Companies can model demand, inventory, supplier constraints, and other variables, then evaluate potential responses before disruption arrives. Hexight's CoPlanner can translate planning into actions by accounting for real-world constraints such as minimum order quantities, production capacity, reorder cycles, and supplier delays.
The potential payoff is better inventory decisions without sacrificing service. Trevor said organizations still relying heavily on spreadsheets can reasonably look for double-digit inventory improvements, though results depend on the sophistication of the operation. Just as important is the ability to evaluate opportunities quickly. A surprise order, late supplier, or sudden demand spike can be modeled against existing commitments so a team can understand the financial and operational consequences of different choices rather than spending days piecing the answer together manually.
That's where the webinar's "supply chain flight simulator" idea becomes especially useful. A flight simulator lets pilots encounter possibilities before facing them in the air, and AI-native supply planning can give business leaders a similar "what if?" environment and see the consequences.
Roy, Trevor and Tamar show how moving from static planning toward continuous scenario analysis can give print teams more time to decide, more visibility into risk, and a clearer understanding of the opportunities hidden inside all that uncertainty.
