Mapping the Insights that Drive Startup Ideas & Theses
A framework developed working backwards from the Mental Models for Ideation
by Ali Afridi – Built SandHill.io; Former VC Principal
Over the past 6 years, I’ve been fortunate to work across multiple VC firms that have active incubation and thesis-driven investment practices. In both approaches, one of the frequent activities that an investor engages in is the development and evaluation of new ideas. One of my personal obsessions has been to better understand and codify these practices to enable these to be run more effectively and systematically going forward.
Last fall, I published a compilation of mental models that entrepreneurs and investors leverage to develop new startup ideas & venture theses. At the heart of these models were a range of input insights, which I also refer to as ‘inputs’, that fuel the presented models and drive new ideas.
As I’ve used these models further, I’ve found that the inputs I laid out in the initial post can be grouped into a few key buckets. In an attempt to organize these, I’ve shared a couple of working frameworks below that I find helpful as I go through these activities.
Consider the below frameworks as v1, a first attempt that I arrived at by working backwards from the mental models I previously shared. Part of my hope in sharing these publicly is to solicit feedback and discover what I’ve missed. Drop me a line if you have suggestions and I’d love to publish updates to this post over time with credits to other contributors.
The frameworks below should be helpful to both entrepreneurs ideating as well as investors who take a thesis-driven approach. In order to not keep repeating ‘founders/investors’ below, I’ll stick with the term ‘innovators’ in this post to encompass both sets of individuals.
The Major Buckets
Before diving into the full map, it’s worth taking a quick look at the 5 major buckets the inputs fit into.
As I’ll demonstrate later in this post, insights across any of these buckets can drive new venture ideas.
For the above buckets:
User Insights – A user can be an individual consumer or a corporate user. This doesn’t necessarily need to be the customer; for marketplaces or multi-sided platforms, this could include insights from the supply / creator-side as well.
Company Insights – Insights related to the performance of specific corporations or institutions that play in a market. This could also be for a specific division or product within a company if a business has many offerings.
Market Insights – Insights related to a collection of companies/institutions and how they operate together in a market.
Market Shifts – Trends & catalysts changing the dynamics across each of the buckets.
Others – A catch-all for the few insights that don’t fit neatly into the buckets above.
The Full Map of Inputs
Going a step deeper from the major buckets, I’ve included the full list of identified inputs below. For this map, I’ve segmented inputs into 2 categories:
Primary Inputs (in red) directly feed into at least 1 of the mental models that I previously presented. I’ll share more on how they do at the end of this post.
Secondary Inputs (in blue) don’t directly feed into a mental model but are related information that is helpful for ideation
This map showcases the identified inputs across each of the buckets. The top buckets (i.e. User Insights, Company Insights, etc) break out insights at different levels of the global economy. The market shifts across the bottom row are constantly leading to evolutions in the above buckets.
Although it may be intuitive how some of these inputs can drive new ideas or theses, most of the primary inputs feed into numerous mental models that can be used to develop a broad range of ideas. I’ve shared an example of how this works later in the post.
Since I’ve had a chance to leverage this map for many months now, I’d like to point to a few things that stand out to me.
1 – There’s no right place to start on this map
Inputs across any of the buckets can drive new ideas or theses. Successful innovators can find opportunities by focusing on completely different parts of this map.
Frontier tech-focused innovators (ex. Lux) or those innovating based on tech inflections (ex. Floodgate) may spend more time tracking developments in the bottom right bucket (“Technological Shifts”). Innovators focused on market shifts or waves may focus their attention primarily on insights related to the bottom row (“Market Shifts”).
Firms like Rocket Internet built extremely successful approaches focused primarily on company-level insights. And plenty of other innovators choose to start their focus with user problems, specific markets, depictions of the future, or a combination of these inputs.
2 – Knowing what to look for can guide where to look
One of the reasons why I find this mapping especially helpful is that knowing explicitly what you’re looking for can help you know where to look.
For example, company and market-level inputs can be gathered through research reports, recent news, market intelligence tools, and discussions with industry insiders amongst other sources.
User insights can meanwhile be gathered from discussions & interviews, through our own life, through others’ analyses, or through online forums and social media sites. Market shifts and other inputs can similarly be gathered through defined channels.
3 – Insights across one bucket can point to insights in others
Many of the inputs across these buckets are interlinked. For example, studying the fastest growing companies in a sector can point to potential market shifts, operational best practices, customer pain points, value propositions that are resonating, distribution channels that are effective, and inform illustrations of the future.
Although the map above was built to be a tool to help with new venture ideation, I find it’s also a helpful resource for knowing what to get up to speed on in a new market I’m studying. Identifying these different factors and forces in a market can greatly improve one’s competency on where a sector stands and where it’s headed. The more inputs that one can identify, the more potential ideas and theses they can develop.
Developing Ideas with the Inputs
Each of the primary inputs I laid out above (in the red boxes) feeds into at least one of the mental models that I previously compiled – in most cases, they feed into many. Although I won’t go through each one, I’ve picked one of the inputs that I find frequently leveraged and I’ve included some of the mental models that it feeds into, along with examples of potential ideas that can be developed with each.
As the graphic above demonstrates, to develop ideas leveraging this approach one starts with one of the primary inputs from the map presented in Figure 2. From there, the input can be applied to one of the appropriate mental models. This can drive a number of potential startup ideas & theses. A non-exhaustive list of mental models that I’ve shared previously can be found here.
It should go without saying but any ideas and theses developed with this approach still require diligence and vetting. This approach enables top-of-the-funnel ideation that one can then evaluate to determine whether the opportunity exists in market.
Some final points and future improvements
In my own day-to-day, I’ve been keeping a list of the different inputs across buckets for almost a year now. I maintain lists across a few key sectors that I’m interested in as well as in different geographies. I’ll also note down inputs from different industries or geographies that stand out – since inputs from one market can help in ideation in another. This list of inputs has driven much of where I have spent my time looking at new investment and incubation opportunities over the past year.
Although the graphics above may make this process appear linear, in reality, it feels more like the flywheel below. The development & evaluation of ideas uncovers additional input insights that then enable further ideation. Information uncovered in previous diligence processes will often plant the seeds for future ideas and opportunities.
The frameworks I’ve presented above provide a list of inputs that can be identified to drive new venture ideas. One of the areas that I’d like to expand on in future posts is around sharing more frameworks from other investors and operators that can point to potential gaps in markets due to specific combinations of these inputs across buckets. Sign up for the SandHill.io newsletter below to get those updates alongside theses & analyses from 600+ VCs.
A huge thank you to Chelsea Zhang and Simran Suri of Equal Ventures for invaluable feedback and suggestions on iterations of this post.
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Awesome article! I tried to access the mental model's link but is not working. Can you share again?