Hitting production targets used to be mostly about keeping lines running and hitting throughput goals. Today, food and beverage leaders are under pressure to do all that and manage tight margins, expensive raw materials, sustainability expectations, and nonstop customer demand for consistency. That’s pushed real-time visibility from “nice to have” to non-negotiable — not just as a reporting tool, but as a way to change how people think, react, and improve every day.
That’s where Worximity comes in. As Director of Account Management, Catherine Tardif spends her time with plants that want to see exactly where they’re losing time and product, then turn those insights into measurable gains. The story isn’t about dashboards on the wall; it’s about operators, supervisors, CI teams, and executives all working from the same data to make smarter decisions, faster.
In this conversation at EATS, Catherine talks about why hidden loss is still one of the biggest untapped levers in food manufacturing, how Worximity helps teams turn real-time data into daily behaviors, and where AI can remove the grind of analysis so people can focus on action.
Q. EATS is full of automation and analytics conversations. What trends or challenges are you hearing from manufacturing leaders this year that feel genuinely new or urgent?
Catherine Tardif: Newer or urgent, I would say with raw materials being so expensive now, scraps, rejects, and giveaway due to overfill are the biggest challenges right now.
Q. Are leaders thinking more about visibility as a performance tool or as a resilience strategy?
CT: I would say both. Everything starts with the data. We need real-time visibility so we can see what’s happening, and then we can improve based on that data.
Q. What’s the broader takeaway for manufacturers — why does seeing downtime and performance data in real time change everything?
CT: With no data, you’re running your production line blindsided. You don’t know how much time you spend on cleaning, for example. For one client, we reduced cleaning time, 50% of that downtime. That’s huge.
The broader takeaway for manufacturers who want to see results like that: start by connecting your equipment. We measure what’s happening, and then we improve over time with insights.
Q. Do you think most plants still underestimate how much hidden loss is buried in untracked downtime?
CT: One hundred percent.
Q. Many digital tools promise insight, but you’ve said Worximity’s value comes from the action it spurs. How do your customers bridge the gap between dashboards and daily decision-making?
CT: The real-time monitoring is more for the operators on the shop floor and the supervisors, so they can act on the data and the downtimes in the moment.
The insights and analytics behind it are more for the C-level, so they can act on that data and improve efficiency over time. That’s where we make the big gains — combining what happens in real time with the deeper analysis.
Q. What role does leadership behavior play in making that translation stick?
CT: Leadership behavior plays a huge role. We don’t want to ask too much of the operators. They have one main thing to do: produce units. So we have to make sure we’re reducing the downtime that makes them lose time on their production day and on activities that are not value-added.
Q. Continuous improvement programs can stall without clarity. How are teams using your analytics to build accountability and engagement across shifts or sites?
CT: Teams use our analytics to rank opportunities with the highest amount of money they can save. That makes it easier for the CI team and the C-level to focus on the right downtimes first.
Q. Do you see data becoming a common language between operations, maintenance, and management?
CT: Absolutely. We usually choose KPIs that speak to different levels. Operators are not going to have the same overview dashboard as supervisors and C-level. We need KPIs and dashboards that speak to each level so everyone can engage with the data in a way that makes sense for their role.
Q. What have you learned about getting operators excited rather than resistant?
CT: We spend time with every level in the company. We spend time with the operators as well as with the C-levels. We make sure they understand why we’re doing this — that it’s to help them in their day-to-day operations, not to add extra work.
Q. Is ease of use the key, or is it the sense of empowerment that data brings?
CT: Both. It needs to be easy. If it’s complicated, they’re not going to use it. So the platform has to be simple enough for them to use, but it also has to speak volumes through the KPIs and how we manage our dashboards.
Q. What financial or operational metrics best demonstrate the impact of real-time analytics — beyond OEE percentages?
CT: First, we need to understand the need of the client. Do they want to produce more, or do they want to be more cost-efficient with what they’re producing? We speak to that pain with our different KPIs. It might be a higher quantity per hour, or maybe units per kilograms an hour.
Q. How quickly do most customers start to see tangible gains?
CT: After two or three days, visibility is already super fast. Just putting that screen up and letting operators see their real-time efficiency with the target speed increases efficiency in real time. But I would say in the first three months, we see the biggest gains.
Q. What role do you see AI playing in manufacturing performance? Is the next step prediction, automation, or something else?
CT: Right now, I see AI playing more of a role at the C-level, helping prioritize opportunities. The idea is to spend less time crunching data and more time taking action on that data.
Q. How does Worximity think about keeping a ‘human in the loop’ while scaling intelligence?
CT: AI is not going to replace anybody — it’s going to make them more efficient. Our goal is to make industries more efficient, and AI fits with that.
Q. If you could challenge every executive walking the EATS floor to think differently about data, what would you tell them?
CT: If you don’t connect and measure, you cannot improve. If you don’t have that data, you’re producing blindsided.
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