Mastering the Product: Welcoming Nani Nitinavakorn to Verb Ventures’ Venture Partner Board
We are happy to welcome Nani Nitinavakorn as a Venture Partner at Verb Ventures!
Nani is a product guru and also an angel investor and advisor. She served as the Chief Product Officer (now, advisor) at Atom Learning, a pioneering Softbank-backed EdTech company. Nani also has an impressive track record with leading fintechs and fast-growing startups — Revolut, Grab and Agoda, which has allowed her to gather a wealth of knowledge and insights about scaling product-led tech businesses across various industries. Her extensive background in driving product innovation and her deep understanding of the intersection between technology and user engagement make her an invaluable asset for the founders in our portfolio, who are navigating the complexities of startup growth and scale.
Beyond the boardroom, Nani is a Judo black belt and a former Singapore national school Judo champion — an unconventional hobby that showcases her disciplined approach, persistence and focus — qualities that are immediately apparent and compelling when you get to know Nani.
We asked Nani a few questions to delve into her unique perspectives on product strategy, user experience, and the critical metrics that shape successful enterprises in today’s digital landscape.
You’ve been involved in numerous high-growth companies. How do you approach finding and validating product-market fit?
It might sound too generic, but trust me, sometimes the simplest product or solution to a problem is the most elegant one. Having been involved in numerous high-growth companies, I’ve learned that finding and validating product-market fit requires a flexible approach rather than rigid adherence to frameworks. While frameworks can provide useful guidance, they shouldn’t be followed blindly.
First principles and common sense should not be underestimated. You’ll hear many disciplines, quotes, and frameworks — each with their own success stories to back them up. Here are a few noteworthy examples:
● Airbnb’s “Do Things That Don’t Scale”: This approach emphasizes the importance of hands-on, bespoke solutions in the early stages to deeply understand and meet user needs.
● Apple’s Philosophy: “Don’t give the customers what they want. Our job is to figure out what they’re going to want before they do.” This highlights the value of innovation and anticipating user needs, rather than following their feedback and suggestions too much.
● Experimentation Philosophy: In contrast to Apple’s approach, many tech startups preach heavy experimentation over a waterfall approach. They iterate rapidly rather than taking a long time to build something with high conviction and launching it only when it’s ready. This process allows for rapid learning and adaptation and has helped many reach product-market fit (PMF) and even achieve unicorn status.
Each of these routes has its own successful case studies, proving that there’s no single best solution. One needs to assess the stage and context of their own product and offering and trust their judgement. In the end, you started this company because you believe you, more than anyone, have the best chance of solving this problem — so be adaptable, consider various approaches, and most importantly, trust your own judgement and conviction.
How do you cultivate a culture of data-driven decision making within your teams? Any specific recommendations?
In my organization, we have product management, data analytics, and UX design teams. Ensuring that these three teams have a data-driven mindset embedded in their DNA is a fundamental requirement for a Chief Product Officer. However, I believe that fostering a data-driven culture within just my teams or a specific department is insufficient. For true impact, this mindset must permeate the entire company so that everyone speaks the same language.
Here are my specific recommendations for cultivating a company-wide data-driven culture:
● Conduct In-House Data Literacy Lessons/Sharing: Organize regular workshops and training sessions to improve data literacy across all departments. This empowers everyone to understand and leverage data in their daily decision-making processes.
● Treat the Data Team as a Partner, Not a Support Function: Position the data team as a strategic partner in the organization. I discourage people from coming to the data team with specific requests like, “Can you help build this dashboard?” Instead, they should approach the data team with the problems they’re trying to solve. This way, the data team can act as a thinking partner, providing deeper insights and more strategic solutions.
● Foster a ‘Data-Slap’ Culture: Create an environment where anyone, regardless of rank or seniority, can challenge decisions from other teams, directors, or even the senior leadership team (SLT) if they have data to back their claims. In my company, this practice is so ingrained that people often push back on my suggestions by saying, “Let me data slap you, Nani,” which highlights our commitment to data-backed decision-making.
When do you think is the right time for a startup to hire a CPO or heads of product, design, and data? Are there cases where a more hands-on, junior team might be more effective?
This question ties nicely with the previous one. The best answer is — it depends! Contexts can vary greatly. Here are my thoughts:
Early Stage: When you haven’t yet figured out product-market fit (PMF) and basic unit economics, it might not be wise to hire a CPO or head of product yet. In this stage, the founder should be responsible for these tasks. Handing over your nascent, unvalidated product (your baby!) to someone else might not be the best approach.
Initial Scaling: When you need to double down on execution and scale what has already worked, a hands-on junior or mid-level person might be more effective. Their focus can be on getting things done quickly and efficiently.
Product Suite Expansion: As you start expanding your product suite, you might need a head of department to ensure the team has a longer-term vision and direction. A part-time executive working alongside and guiding mid-level product managers can also be a good approach during this phase.
Further Scaling: At this stage, a CPO might be needed to ensure that cross-functional teams work together with a shared direction and to pave the way for a broader vision. Promoting the head of product or hiring externally is a debate for another day.
Post-Scaling: Depending on the company’s ambitions and the talents that have been upskilled, you might find that continuing without a CPO is also possible. For example, I’m transitioning from a CPO to an Advisor at my previous company. A good executive works themselves out of their job. They know when to step up and take charge but also when to step aside once their work is accomplished.
Following the flexible mindset from the previous question, there’s no need to fixate on having to hire a CPO or Head-of, or to feel that once you hire, it needs to be a full-time or permanent role.
In a market where finding real talent who is also a culture fit is rare, being flexible and working around that talent might also be more effective. For instance, if you meet the right person but don’t need a full-time CPO or head-of yet, consider hiring them part-time or building a relationship with them for when they will be needed in the future.
In the end, adapting your hiring strategy to the current needs and context of your startup is crucial. There is no one-size-fits-all approach, and flexibility is key to ensuring you have the right people at the right time.
Can you share your insights on how to adapt organizational structures as a company evolves? From your experience, are there any ‘must do’ or ‘no-goes’ in organizational structures you could use to build a scalable product-led business?
This is purely my opinion and might be contentious for some. The only two ‘no-goes’ for me are:
- Fear of Re-organization: Avoid being too rigid with structures that worked previously or at other well-known companies, as contexts can vary greatly.
- Centralized Decision-Making: Believing that figuring out organizational structure is solely the responsibility of the senior leadership team (SLT).
While there’s no definitive ‘must-do’, here are some insights and recommendations based on my experience:
● Treat Organizational Structure as Dynamic: Organizational structures and ways of working should be treated like products — constantly changing, iterating, and evolving with the company’s growth and challenges. For instance, at my recent company, we found that the traditional product organization was less effective than treating the Head of Product for the B2C and B2B segments as the General Manager of each respective vertical. This approach suited our company size and context better, leading to significant improvements in alignment and performance.
● Empower Decision-Making at All Levels: Organizational structure and hierarchy should streamline processes, not hinder progress. Ensuring that even the most junior employees feel empowered to challenge decisions — what we call “data-slapping” the SLT — is crucial.
● Promote a Flexible Mindset: Instill a culture where the status quo is not seen as a rule. Just as laws evolve over time, so should organizational structures. Mid-managers should feel empowered to propose company-wide changes if they make sense. For example, in an international expansion team at one of my previous companies, we found the structure inefficient. By collaborating with other PMs, we successfully proposed dissolving the expansion vs. core product distinction, demonstrating the importance of challenging the status quo.
● Avoid Over-Complexity: Like a product, simplicity often trumps complexity. While it’s essential to adapt your structure, avoid making it overly complex, as this can lead to confusion, slower decision-making, and inefficiencies. Keep the structure as simple as possible while still meeting your organization’s needs.
