204: Will a Duck DB-Like Excel Emerge by 2075? And Is Data Every Company’s Most Valuable Asset? Featuring Benn Stancil of Mode
Aug 28, 2024
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Benn Stancil, an expert in data and strategy with experience at Microsoft and startups, discusses the evolution of data management and the future of Excel. He reflects on navigating uncertainty in startups and the critical role of intuition in decision-making. Benn highlights the need for product focus amidst industry noise and explores the potential of AI in data analysis. He imagines a future where tools evolve beyond traditional frameworks, emphasizing the importance of understanding business needs to drive effective decision-making.
Benn Stancil emphasizes the importance of trusting personal instincts over conventional startup norms to achieve innovative success in data.
Understanding product market fit as a nuanced spectrum is crucial for startups, focusing on the right audience rather than mass appeal.
The evolution of data teams highlights a shift from IT dependencies to essential, well-defined roles, necessitating impactful business decision-making.
Deep dives
Ben Stancil's Background in Data Analytics
Ben Stancil began his career in policy research before transitioning to a data team at a startup in San Francisco that was later acquired by Microsoft. He co-founded Mode, an analytics business intelligence tool that enabled data teams to create actionable dashboards and perform data analysis. After building Mode for a decade and subsequently selling it to ThoughtSpot, he found himself at a crossroads, becoming 'unencumbered' and exploring new opportunities in the data space. His experiences offer insights into the evolution of data tools and the common misconceptions encountered throughout his journey.
The Importance of Following Your Own Path
Stancil emphasizes the importance of pursuing innovative ideas without getting trapped by conventional startup playbooks. Early in his career, he observed how teams often followed established rules despite their own logic suggesting otherwise, out of fear of stepping outside accepted norms. He reflects on a mistake made at Mode, where early success in a blog about data analysis was abandoned because it didn't align with traditional marketing strategies. His key takeaway is to trust one's instincts, committing to personalized methods that yield successful outcomes, rather than attempting to conform to external expectations.
Navigating Startups and Product Market Fit
Stancil argues that the journey of a startup involves numerous decisions that can lead to either success or failure, with clarity on product market fit being essential. He observes that product market fit is not a binary state but rather a spectrum that depends on customer excitement, ease of sales, and the alignment of products with user needs. The underlying sentiment is that recognizing when something works for a specific segment is crucial, even if that segment isn't large. He stresses the importance of targeting the right audience rather than trying to appeal to everyone in order to find potential growth.
The Evolution of Data Teams
According to Stancil, the perception and structure of data teams have significantly evolved over the past decade, moving from obscure roles to essential positions within organizations. Initially, data tasks were often burdened on IT departments, leading to inefficiencies and a lack of focus on data itself. Now, as data-centric roles become better defined, there is a pressing need for those teams to balance the increasing demand for analytical insights with practical business applications. While the enhanced focus on strong data practices is commendable, Stancil notes ongoing challenges in translating data analysis into truly impactful business decisions.
Rethinking the Future of Data Tools
Stancil shares his perspective on the enduring relevance of Excel, contending that its persistent use stems from unique traits that facilitate intuitive data management. He believes any potential successor would need to combine ease of use and the ability to manipulate data without complex setups, straying away from overly abstracted tools. This leads to the idea that future tools may need to blend hybrid models, connecting both local data handling with the advantages of cloud computing while keeping user experience at the forefront. He highlights the potential for integrating AI and unstructured data analysis, suggesting that the real value lies not in mere numerical manipulation but in distilled insights drawn from qualitative observations.
The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.
RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
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