Excellent product managers are rare, something that I can attest to after having worked in the data department of a major Chinese tech firm. That’s why it’s often said that a good product manager is the most valuable talent of an artificial intelligence (AI) start-up firm.
Interestingly, there are limited courses on product management in universities, and very few books focus on internet product management.
In the future, there will be more products driven by AI and data technology.
A good manager for such products should have deep understanding not just of the technology, but also the market and user experiences. Knowledge about algorithm and data development are also essential.
However, many product managers have put excessive emphasis on technical functions but fail to give the issue of monetization more thought.
Product management is about combining science and commerce.
Who are the buyers? What questions will they ask before buying? What are the potential issues that could hold back a purchase? Is there one function that can fix the issue? These are the questions I always ask.
One has to collect market views in the early stage of product development.
If the product is targeted at corporates rather than individuals, one should find out who makes the buying decision. What factors would influence the decision? The whole decision-making process and buying cycle are also important.
Failure is part of the innovation process. There is less to lose if you fail in the early stage. When you have already spent a lot of time, money and efforts before realizing the idea does not work, shifting the track will be much more difficult and costly.
No matter what, if you find out your product prototype is not attractive to potential clients and investors, the best way is to start all over.
This article appeared in the Hong Kong Economic Journal on Dec 12
Translation by Julie Zhu
[Chinese version 中文版]
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