Algorithms can predict demand, but they can't build trust as much as people's connections do. In supply chain technology, the real breakthroughs happen when teams learn to do a basic human skill — to listen. With listening comes empathy and curiosity, two of the most underrated and immeasurable skills in digital transformation. Here's why having these skills is crucial.
When people hear about supply chain technology, they often picture complex algorithms like in movies about our digital future: robots delivering all the packages, predictive models crunching sterile data, and dashboards glowing with green KPIs. The reality is different (and who would doubt that!) After years of building digital products for global operations, I've learned that the real superpower behind all these futuristic images isn't even data itself — it's listening.
Listening as a diagnostic tool
In every project I deal with, I start not with a model but with a conversation. I start with the questions, and then listen between the lines: people often reveal the most when they don't say it out loud. I figure out why the company needs to change, what they want to achieve, and what the hidden signals are. You can't offer to optimise what you don't truly understand, and you can't understand a business without listening to the people behind it.
Before moving into tech, I worked in the FMCG sector, which taught me to speak the same language as my clients — the language of operations, demand, and risk. That experience helps me bridge perspectives between business and technology.
Translating pain into product
I often describe my work as translation — turning business pain into product requirements. Stakeholders rarely talk in technical terms; they talk about missed shipments, stockouts, or unexpected write-offs. My role is to listen to those stories until I can see the pattern behind them. When you start from that place, you stop chasing perfect algorithms and start designing for impact. The product becomes not just a tool but a language that connects data to human judgment.
I've seen the most enormous inefficiencies hidden not in spreadsheets or complicated structures but in how teams communicate — or fail to communicate at all. Sometimes an algorithm integration "fails" simply because people don't believe in it. Listening helps uncover that disconnect before it turns into resistance.
Empathy as strategy, not sentiment
Coming from the FMCG world, I was used to environments where trust and timing mattered as much as precision. Moving into tech made me realise how easy it is to get lost in abstraction — in complicated terminology, over-engineered processes, and the obsession with delivery. Empathy and human skills help bring you back.
When I understand what drives decision-makers — their risks, fears, and goals — I can design systems they'll actually trust. Every planning dashboard, automation flow, or optimisation model begins with one question: Who needs to trust this system enough to act on it?
Building cultures that listen
Listening shouldn't depend on one person's intuition — it should be built into team culture. The strongest product teams I've seen make empathy systematic: they shadow operations, run open retrospectives, and rotate roles between tech and business. Once you've been in someone's shoes, you start to treat their requests differently.
Every time someone listens deeply, the system learns something no dataset could ever teach.
That mindset also protects us from overconfidence in technology. No matter how advanced an AI model is, it can't replace context — and context lives in people. Weather fluctuations, supplier relationships, and the complexity of customs can be observed, but not always directly translated into data you can feed into an AI tool. It's in the daily trade-offs, the improvisations, the decisions that no algorithm was trained to predict.
Beyond efficiency
In the end, supply chain transformation isn't just a technical mission.
Every competent manager shouldn't do things just for the sake of doing them. The core purpose is human profit — in money saved, resources preserved, and a more efficient workload.
If you still doubt the value of listening, think about it. For years, projects were shaped not by metrics or forecasts but by a single phone call from a distributor someone trusts. The moment you make it a habit to treat people as humans, not data points, your algorithms will start to reward you back.
Technology keeps evolving, but resilience still comes from people who listen — to data, to markets, and to each other.