By Qianyu Wang
Why System Thinkers Like Supply-Chain Graduates Are Unexpectedly Well Positioned
When we picture a product manager in the tech industry, we tend to imagine someone sharply technical — an engineer who can talk about APIs one moment and design sprints the next. But the more I spoke with Zichun Zhao, a product manager at Vivo who shares nearly the same academic background as me, the clearer it became that the modern PM is something different: less of a miniature CEO and more of a system detective.
Both Zhao and I studied supply-chain management as undergraduates and later moved into operations research. None of this sounds like traditional product-management training. Yet as Zhao described his day-to-day work and the realities of product development, it became obvious why system thinkers like us are starting to show up more frequently in PM roles — and why the job looks so different from the stereotypes.
PM Work Starts Where Certainty Ends
Zhao works on Vivo’s advertising platform, where the team builds algorithms and solutions that help e-commerce clients — like Taobao sellers — reach users through media channels. On paper, it sounds technical. In practice, Zhao says, the hardest part of the job is that nobody really knows the full answer.
This is especially true of advertisers themselves. Many clients enter meetings not because they know what they want, but because they don’t. “Some don’t know their real target audience,” he told me. “Some can’t tell whether they want sales, traffic, or just visibility.”
He shared one story about an e-commerce client who insisted their ads “weren’t working.” After several conversations, Zhao realized the problem wasn’t bidding strategy or user traffic — the client’s creative team was overwhelmed and recycling old images. No algorithm could fix that. The moment captures something essential about PM work today: the job starts where the information stops.
Systems Thinking: A Hidden Advantage
When I asked whether his supply-chain training mattered now, Zhao didn’t hesitate. “Of course. Product work is basically looking at flows — information flows, value flows, incentive flows. It’s all systems.”
His perspective mirrors a broader insight recognized in industry research: systems thinking is fundamentally about seeing relationships rather than isolated parts. As Preston writes, effective problem-solvers “map behaviors, incentives, and feedback loops” instead of reacting to surface level symptoms [1]. This approach is especially powerful in product environments where user needs, engineering constraints, and business goals interact in nonlinear ways.
Supply-chain coursework teaches you to identify the bottleneck that truly limits performance, see how actors in a network interact, and understand how upstream decisions affect downstream outcomes. Zhao uses this constantly. In advertising, the “bottleneck” might be slow creative production, mismatched incentives between advertisers and the platform, or a data gap about user behavior. “It’s the same logic,” he said. “You figure out which part of the chain is actually holding everything back.”
Industry observers similarly note that the future PM is less of a technical operator and more of a “systems navigator” who can integrate ambiguity, domain constraints, and stakeholder incentives into clear decisions [2]. That’s why supply-chain graduates—once assumed to be headed toward logistics — are quietly becoming strong PM candidates. When technology products behave like dynamic networks, system logic becomes a competitive advantage.
The Real Struggle: Getting High-Quality Information
If PM work revolves around decision-making, then the hardest part is simple: reliable information is scarce.
Zhao explained that even within the company, different data sources conflict. Clients don’t always respond. Competitors never reveal their internal mechanisms. Industry reports skip crucial context. “You end up stitching together clues,” he said.
So where does useful insight come from? Zhao relies on a mix of informal channels: podcasts and Little Universe interviews where marketing directors casually reveal how they work; conversations with senior sales managers who know what clients won’t say publicly; short MOOCs or industry talks to benchmark best practices; and casual chats with colleagues who hold years of tacit knowledge. Real insight rarely comes from a clean spreadsheet — it comes from understanding how people and incentives interact.
Why PM Work Is Inherently Social
As Zhao put it, “Knowing the right answer is useless unless you can get people to agree to do it.”
This means PMs must be skilled at managing relationships, not just roadmaps. They motivate overworked teams, negotiate with stakeholders who have conflicting priorities, explain to engineering why a fix matters, and help business teams understand technical constraints. Technical knowledge helps, but without interpersonal understanding, a PM’s ideas never become real. Zhao described it as learning the “people system” inside a company.
AI Is Changing the Workflow — but Not the Role
One of the most forward-looking parts of our conversation was Zhao’s view on AI. He sees it not as a threat but as a shift similar to the industrial revolution. “Efficiency will explode,” he said. “But PMs won’t disappear. They’ll just work differently.”
AI speeds up research, competitive analysis, early prototyping, and note-taking. But it cannot interpret why something matters, how to prioritize, or who needs to be convinced. Those tasks
remain deeply human. The new essential skill, Zhao argues, is knowing how to ask AI the right question — prompting becomes a form of structured thinking.
Who Actually Thrives in PM?
As I neared the end of our conversation, I asked Zhao something I personally cared about: How can someone tell if they’re a good fit for PM work?
His answer wasn’t about major or technical ability. Instead, he asked back: Do you stay calm when things are ambiguous? Can you make decisions without perfect information? Do you enjoy figuring out messy problems? Can you align people with different incentives?
“PMs are the people who like connecting dots,” he said. “If that’s you, you’ll do well.”
Entering a rotation-based role at Lalamove, this resonated with me. I realized that my supply chain training wasn’t irrelevant at all — it might be precisely what helps me see the whole system when things get complicated.
Conclusion
Talking with Zhao made me realize that product management is less about owning a title and more about navigating complexity. As tech products grow more interconnected and AI accelerates every part of the workflow, companies will increasingly rely on people who can see the whole picture — who can turn noisy information into clear decisions and bring very different teams into alignment.
This mirrors what Yehoshua and other industry experts have argued: the future PM is a translator of complexity, someone who can integrate AI tools, human incentives, technical constraints, and business needs into coherent action [3].
That is why system thinkers, including those from supply-chain and operations-research backgrounds, are becoming a better fit for these roles than the old stereotype of the “pure tech” PM. Heading into a rotation at Lalamove, this conversation turned product work from a vague idea into a concrete personal question: Do I enjoy connecting dots across users, data, business
needs, and technical constraints? I don’t know the full answer yet, but now I know what to look for. And in a future shaped by AI and complexity, the people who understand systems — and help others move through them — will sit at the center of how tech products are built.
Reference:
[1] L. Preston, “Unlocking the power of systems thinking,” Medium, 2017. [Online]. Available: https://medium.com/disruptive-design/unlocking-the-power-of-systems-thinking-b3809eaab519. [Accessed: Dec. 3, 2025].
[2] T. Legrain, “The future of product management in 2025: Navigating key trends and transformations,” Medium, 2023. [Online]. Available: https://legrain.medium.com/the-future-of product-management-in-2025-navigating-key-trends-and-transformations-7d2deb8ae35b. [Accessed: Dec. 3, 2025].
[3] T. Yehoshua, “Tamar Yehoshua on product leadership in the age of AI,” McKinsey & Company, 2024. [Online]. Available: https://www.mckinsey.com/industries/technology-media and-telecommunications/our-insights/tamar-yehoshua-on-product-leadership-in-the-age-of-ai. [Accessed: Dec. 3, 2025].