Data-driven products with purpose (Part 1/3)
“Yeah, well, you know, that’s just, like, your opinion, man.”
I’ve heard variations of this statement in the workplace — The Dude is not alone in making them.
From my experience, there is a strong correlation between the value of an opinion and its maker’s reputation. If my business associates trust me, then they will be less likely to doubt my claims. If you’re new to an industry market, then your professional opinion may leave a weaker impression on potential investors, partners, or team members than an expert’s opinion— The Dude would be right to dismiss your opinion if you lack credibility. I’ve seen this firsthand multiple times. On the other hand, if you’re a popular social media influencer, then even the most nonsensical opinion will make waves (quite unfortunate, in my opinion). The Dude would not be swayed by the influencer’s opinion, either — he wants facts.
In this three-part post, I look at the relationship between data and business strategy (Part 1), the perspectives of tech startups Impactoria and Loio (Part 2), and my own experience that led me to take data more seriously in product and project management (Part 3).
Special thanks to Ridwan Alam, a data scientist who commented on one of my LinkedIn posts asking about how I have applied data science into the product and project management life cycles. He made a pretty interesting blog and video about how Tesla autopilot works, and I cover more of his thoughts in Part 3. His comment inspired me to write this post.
Data and strategy
Leaders who rely on their gut and conclude that some people “just get it” mirror the “work hard and you’ll become a billionaire, too!” mindset from my experience. I have met with hundreds of entrepreneurs aspiring to make the next big thing. What I’ve found is a billion-dollar idea doesn’t sell itself, and while working hard helps, being at the right place at the right time with the right people helps much more.
Given how unlikely it is for the stars to align to help a hard-working person become a billionaire, a more forward-thinking mindset in solving real problems is one that is based on data and design thinking. In practice, this involves making genuine efforts to understand businesses and consumers. These efforts help in making decisions about how to provide them value using facts and not untested hypotheses.
It’s also important not to get stuck in a data vacuum. Decision analysis might be missing some guiding opinions that would provide focus. Additionally, a healthy risk appetite helps decision-makers to meet at least some threshold of certainty based on some reasonable amount of data as opposed to “total” certainty with all possible data.
When data is ignored…
When top executives do not rely on data, the impact on their company culture is clear: data does not appear to be important in the decision-making process. When colleagues collectively buy in to rely on data, all it takes is leadership disregarding the data to show the team that data-driven decision-making is not valued. Some of my experiences have confirmed this happens in practice.
Many businesses fail to become data-driven because their company culture fails to value data’s potential. The data-driven competition stays ahead and the rest lag behind. Someone’s opinion of whether someone “gets it” won’t matter when data proves to be more reliable.
… and strategy is ignored…
Being data-driven makes an industry player more competitive. However, if the business lacks a guiding opinion, there may be too much data to consider and no genuine hypothesis to validate before making a decision.
I recall in a past experience where the stakeholders didn’t value data, but they also didn’t value strategy as their opinion constantly changed. They valued the concept that they championed, but in product management, there are several other phases — you can’t launch reliably without taking the concept further. Imagine a situation where neither data nor strategy is valued—what would you get?
… a foundation bringing the two together is needed to create impact
Let’s start with a guiding opinion — with that, we can formulate a strategy based on that opinion. Is that strategy sound? If it’s known market practice to apply that strategy, then we’re not talking about opinion any longer, the guiding opinion is a market-tested fact. What if the strategy is not supported by common practice?
With market leaders looking to apply data-driven decision-making, it’s no surprise that tech startups also consider data not just to validate proposed strategies and decisions, but to make data central to delivering product value.
I had a chance to talk with tech startups Loio and Impactoria to learn more about how they apply data science to enhance product value — read their insights in Part 2.
This is a personal blog. The views and opinions expressed in this article are those of the author and do not represent those of people, institutions or organizations that the author may or may not be associated with in a professional or personal capacity. All information is provided on an as-is basis.
