The nobrainer approach to better business decision-making for growth and innovation.
Data Strategy
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Innovation
Human Understanding
Data in the company's life cycle
Founders start up forward-looking.
In the early stages of a company, the founders and their team are focused 100% on forward-looking data, or even early indicators, that can help identify an MVP. This is why visionary startup advisors like Ash Maurya from Lean Foundry and my great friend Emiliano Villarreal advocate for startups doing a lot of early customer research.
Once the MVP is found and the company gains traction, founders often shift their focus to growth and performance. This transition leads to a greater emphasis on present-looking operational data, aimed at increasing productivity and driving the company's growth towards becoming profitable.
As the startup matures and achieves a viable economic model, attention shifts again—this time toward financial data. Founders, now business leaders, manage a growing team while responding to market forces and investor expectations, striving to improve both top and bottom lines.
However, even as visionaries, most founders are removed from the front lines of value creation and innovation. Those tough decisions are now in the hands of Strategy, Innovation, Product and/or Marketing Teams. As the data that originally fueled the company's success becomes outdated—or, in some cases, never properly existed as other than evidence, these teams begin operating on increasingly uncertain assumptions.
Forward-looking data is crucial in this context. It enables teams to continuously learn about their customers, establishing shared insights that foster better collaboration and ongoing learning.
What happens to data as the business grows?
As businesses evolve, the handling and type of data naturally shift. Backward-looking financial data tends to reside with CFOs and their administrative teams, while present-looking operational data typically falls under COOs and business development.
One key characteristic of these two types of data is that they are inherently part of the business. Their sources are often systems or platforms already in place, and the analysis can usually be performed internally. This makes backward and present-looking data relatively inexpensive to obtain and generally unbiased, as it can be evaluated by the company itself.
On the other hand, the more creative side of the business (Strategy, Innovation, Marketing/Sales and HR) have fewer affordable sources for the data they need to navigate the complex, risky, and uncertain decisions they face. Some marketing teams rely on social media data, which offers good value, especially through tools like A/B testing. While this reduces uncertainty by providing clear outcomes (clicks or no clicks), it only informs decisions after the strategic moves have already been made.
Other key data used by these strategic and creative departments often includes industry-specific insights or brand value data (recognition and perception). While important, industry data rarely helps differentiate your company or create new value, and brand data is usually focused on the present or recent past.
True forward-looking data requires research, and high quality data of this kind requires a third party to eliminate bias. Why? Because the data is centered around concepts, messages or products that are in the process of being developed by that same team, which makes them biased when it comes to gathering and analyzing data objectively about people’s reaction to their own creations.
In behavioral economics, this is known as avoiding biases like Confirmation Bias (seeking information that supports pre-existing beliefs), the IKEA Effect (overvaluing what we create), the Curse of Knowledge (being too close to the product to see it clearly), and Bandwagon Effects (following popular trends). When a team collects data on its own creations, it risks clouding judgment and making flawed decisions.
It is simply not good practice to gather and analyze data about things that affect you, if you want to make the best choice. Or as we say in nobrainer: “the game is more fun if the umpire is out of the game”, a riff on my grandfather Isaac’s lesson not to be judge and party when making decisions.
Forward-looking data, in this respect, forces companies to test their ideas, or deepen their understanding of customers through lenses that provide a perspective untainted by their team experience.
This approach forces companies to test their ideas and deepen their understanding of customers without the distortion of internal biases.
However, it does come with higher costs and the added challenge of working with third-party researchers. The combination of increased expenses and greater data uncertainty can sometimes tempt companies to forgo forward-looking data altogether, convincing themselves they can manage without it.
The risk of not using forward-looking data.
There are at least 3 major risks companies face when they under-invest in forward-looking data:
1. Hampering Innovation and Creativity: Without high-quality forward-looking data, innovation and creative teams are left navigating uncertainty blindly. This lack of insight makes decision-making feel like guesswork. Conversely, providing these teams with reliable, forward-looking data empowers them to make more informed decisions, increasing their chances of success.
2. Relying on Assumptions and Opinions: Without forward-looking data, teams tend to rely on past assumptions or subjective group opinions. By bringing in external data, teams can align on a shared perspective, leading to clearer focus, better collaboration, and sharper execution. Data-driven decisions reduce friction and streamline the creative process.
3. Not Testing New Ideas: Failing to test new ideas can result in avoidable, sometimes catastrophic—mistakes. Creative teams often fall prey to groupthink or internal politics, which can cloud judgment.An unbiased outside perspective can help teams refine their new creation and catch potential red flags that went unchecked during development or early execution.
Companies that neglect forward-looking data may find themselves trapped in a cycle of extracting short-term value from both employees and customers, which ultimately leads to friction in their operations and finances.
In contrast, companies that invest in forward-looking data become more human-centered and data-driven, giving them a competitive edge. This advantage not only improves decision-making but also leads to long-term benefits and sustainable growth.
This principle applies not just to businesses but to societies as well. As we navigate a new era with outdated economic and social systems, investing in collective human understanding will be key to overcoming our challenges and building a better world for everyone.
Thank you for taking the time to read through these insights. I hope they inspire new ways of thinking and approaching your data strategies. Looking forward to continuing the conversation and helping drive innovation forward.
