INTERVIEW
RO-AI: The first optimisation expert that speaks your language
An de Wispelaere, Chief Product Officer, PTV Logistics
1. Conversational AI is beginning to enter logistics operations. What types of planning or optimisation questions are better suited to natural language interaction compared to traditional analytical tools?
Traditional analytical tools excel at descriptive tasks—telling you “what” happened through static dashboards and spreadsheets. However, natural language is far superior for investigative and prescriptive queries.
The “Why” Questions: Instead of manually cross-referencing data to find a bottleneck, a user can ask, “Why is this order unplanned?”. PTV Mira instantly investigates every constraint—capacity, time windows, and driver hours—to identify the root cause.
The “What-If” Scenarios: Natural language allows users to describe complex business changes as if talking to a colleague. For example, “What if we add a depot in Bristol?”. PTV Mira translates this narrative into a technical optimization model, runs the simulation, and quantifies the impact in seconds.
Contextual Exploration: Users can ask follow-up questions like “What about efficiency?” or “Filter on those,” because PTV Mira remembers the context of the conversation, eliminating the need for complex database syntax or multiple screen navigations.
2. When operations managers can ask questions in natural language and get instant scenario analysis, what kinds of decisions start happening more frequently or at different levels of the organisation?
The shift to natural language democratizes logistics intelligence, turning it into a shared language for the entire organization.
- Executive Strategic Agility: Decisions that were previously “scheduled exercises” now happen in real-time. A CEO can directly ask for high-level strategy, like optimal network distribution for an electric fleet, without waiting for a data team.
- From Gut Feeling to Fact-Based Validation: Historically, operational planners relied on experience and “gut feeling” to approve a plan. PTV Mira transforms this into a data-driven science. Planners can now instantly validate plan quality by benchmarking current results against similar historical scenarios. The question “Is this plan optimized enough to release?” becomes a fact-based decision, enabling proactive adjustments that reduce operational costs before the first truck even leaves the yard.
- Managing Undercapacity with Strategic Intelligence: When faced with an undercapacity situation—where demand exceeds available resources— PTV Mira does more than just report a failure. She acts as an Investigative Agent, analyzing constraints and presenting the planner with viable, fact-based options to reach 100% fulfillment.
- Cross-Functional Alignment: Because PTV Mira bridges the gap between the “Brain” (strategy) and the “Hand” (execution), finance and operations teams can collaborate on trade-offs, such as balancing service quality versus operational cost, on the fly.
3. Strategic planning decisions around network design or fleet composition have traditionally been scheduled exercises requiring specialist teams. How does real-time scenario modelling change the rhythm of these decisions?
Real-time modelling transforms strategic planning from a static, rare event into a continuous evolution.
- Eliminating the “Grandmaster Gap”: Traditionally, network design took weeks and required external consultants. PTV Mira allows internal teams to act as the “Grandmaster,” testing dozens of scenarios—like depot relocations or fleet-wide toll optimizations—simultaneously.
- Rapid Iteration: The rhythm shifts from “design once, run for a year” to “model, test, and refine”. A user can set up rules for various omni-channel flows and run repeatable models with updated data instantly.
- Outcome-Based Momentum: By reducing analysis time from hours to minutes, organizations can make “elephant-sized” decisions—like entering a new market or electrifying a fleet—with the confidence of data-backed simulations rather than assumptions.
4. Last mile teams constantly balance cost efficiency against service quality and sustainability targets. Can you share a practical scenario where a logistics operation navigated these competing priorities?
In modern logistics, teams must constantly balance service excellence against operational costs and sustainability targets. PTV Mira serves as the investigative agent that transforms these competing priorities into fact-based choices.
- The Conflict: Operations often reach a “tipping point” where a near-perfect plan (e.g., 99.75% fulfillment) hits a mathematical wall due to rigid constraints, such as driver working hours or geographic isolation.
- The Navigation: Instead of relying on gut feeling, teams use PTV Mira to perform root-cause investigations—identifying exactly which constraint (capacity, time windows, or range) is blocking fulfillment.
- The Simulation: Planners run “What-If” scenarios to test the impact of strategic shifts, such as extending shifts or outsourcing certain orders.
- The Result: By comparing these scenarios, organizations can quantify the exact ROI of their decisions. This allows them to achieve 100% service quality while simultaneously identifying the most cost-efficient path that reduces mileage and carbon footprint.
Scenario: Selective Time Window (TW) Expansion
A particularly high-value application of this intelligence is analyzing the trade-off between Time Window (TW) precision and Delivery Cost Income.
- The Challenge: A retailer wants to reduce operational costs by encouraging customers to accept wider or overlapping delivery slots. However, wider slots mean lower delivery fees paid by the customer.
- The Investigation: Instead of an “apply to all” strategy, the planner uses PTV Mira to model the network effect of expanding windows in specific regions versus others.
- The “What-If” Modeling:
- Baseline: Strict 30-minute windows with high delivery income but high transport costs.
- Scenario: Overlapping 2-hour blocks in all areas with reduced delivery fees.
- Fact-Based Decision: PTV Mira simulates these changes and reveals the “tipping point”: in some regions, the operational savings from better route consolidation far outweigh the loss in delivery fee income.
- The Outcome: The organization moves from an expensive, uniform strategy to a region-specific slot strategy. This allows them to offer the right window at the right price, maximizing both customer satisfaction and the bottom line without over-provisioning their fleet.
5. Across European logistics - retailers managing their own fleets, carriers optimising networks, 3PLs balancing multiple clients - are certain operational contexts proving more receptive to conversational optimisation? What makes some organisations ready whilst others remain cautious?
Receptivity to conversational optimization isn’t tied to a specific industry vertical like retail or 3PL; it is fundamentally driven by an innovative mindset. Organizations that succeed are those that embrace new technology rather than succumbing to the “fear of the unknown”.
We understand that trusting an AI agent with complex logistics is a journey. Much like learning to use self-driving functionality in a car, users often start by verifying every action PTV Mira takes. Over time, as they see PTV Mira consistently validate their rules and constraints, that “manual check” habit fades, replaced by a deep level of trust in the system.
The value of this speed and clarity is universal across all clients, but the speed of acceptance varies. What bridges this gap is our reputation at PTV Logistics—our customers know how perfectionistic we are about our own algorithms, so when we vouch for PTV Mira as a reliable partner, it provides real, foundational value to their transformation process.
6. As last mile operations face increasing pressure from driver shortages, volatile fuel costs, and tightening delivery windows, which of these challenges do you see creating the most friction for logistics teams over the next few years?
It’s not any single challenge—it’s managing all of them simultaneously. That’s where the real complexity lies.
When driver shortages collide with fuel volatility and tight delivery windows, creating a feasible plan that respects all constraints becomes exponentially harder. Manual management breaks down entirely, which triggers a cascade of secondary problems: finding software sophisticated enough to handle the complexity, hiring experts to model your operations correctly, and ensuring planners use the system optimally.
There are so many failure points. What we saw repeatedly in the past was the classic pattern: you implement a system, the consultants leave, planners start adjusting parameters to handle edge cases, and suddenly your results deteriorate. Figuring out what went wrong—which parameter change caused the breakdown—used to require deep technical expertise and days of investigation.
PTV Mira eliminates these failure points. You provide your order data and fleet information, then explain your constraints in plain language—the way you’d explain them to a colleague. She handles the modelling, keeps your setup optimized, and maintains performance even as your network or volumes shift. No hidden parameter drift, no silent degradation. Just transparent, consistent optimization that adapts with you.
Ready to play the game your competitors don’t even realize has started? Hear more from An de Wispelaere, CPO of PTV Logistics at 14:45 on day 2 of the Leaders in Logistics Summit on 18th of March. For more information before the event, please visit our website: www.ptvlogistics.com
An de Wispelaere, Chief Product Officer , PTV Logistics
An De Wispelaere is the CPO of PTV Logistics and a co‑founder of Conundra, where she served as Managing Director for a decade. She holds a PhD in Mathematics with significant research contributions and 20+ years of experience in algorithms, modelling, and supply‑chain optimization.
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