Building an early-stage software venture is analogous to charting a path up a previously unexplored mountain, with a successful product launch being the summit. For more specificity in this analogy, let’s consider a “successful” product launch to be the launch of a minimum-viable product that achieves product-market fit. This is not just launching a piece of technology, this is launching a piece of technology that reaches its end-users and customers, who in turn use the technology and cannot live without it.
Reaching product-market fit, or the summit of this uncharted mountain in this extended analogy, is the path that founders need to chart out at the early-stage. But before charting out a path, let’s take a step back, and consider the instrumental question of how do founders select the “mountain to chart?” If the actual “charting of the path” is the process leading up to product-market fit for a minimum-viable product, then the mountain itself is the specific segment of the problem space in which this startup is being launched. So, selecting a “mountain to chart,” is the analog to selecting a problem-space to build a startup in—and so how should founders do this?
Let’s start with defining a general problem space as a set of observed issues (e.g. inefficiencies, unnecessary costs, poor experience, etc.) that have at least one common thematic element (e.g. same industry, same geography, same end-users, etc.). This is a fairly broad definition, but it allows us to think about problem spaces beyond the ones directly facing businesses. Example problem space statements include:
· Farmers are having trouble anticipating changing weather patterns because of climate change, and are consequently unable to prepare their crop rotations properly
· Government offices in rural areas are having trouble relaying information to their central administration and information received tends to be incomplete
· Companies are having trouble tracking and verifying the environmentally conscious decisions their employees are making
· Hospitals and medical clinics in rural areas are having trouble accessing life-saving equipment and prophylactics in order to serve their surrounding populations
· Unemployed workers in advanced economies are having trouble upskilling in a cost-effective manner and are consequently unable to improve their livelihoods
As I’ve defined it, a problem space does not lend itself to a solution; it is simply a statement meant to capture the metaphorical (or perhaps, quite literal) pain experienced by a group of people, no matter how broad that segment of people. Now, returning to the analogy of climbing a mountain, the depth and breadth of the problem space is analogous to the difficulty of the mountain to climb – a problem space that refers to a large set of pain-points experienced by a large number of people tends to be more difficult to solve than a singular pain-point experienced by a single person, simply because there is increasing variance in the problems to be solved. However, a problem space with a broader, more inclusive set of problems tends to have more commercial potential (i.e. more potential value to generate) than a problem space with a singular person and a singular pain-point. Further, problem spaces with more commercial potential tend attract more competitors, which could dilute the individual commercial potential of any single venture entering that problem space. However, let’s ignore the market dynamics introduced by competitors for now and focus on the purpose of identifying a problem-space.
The first step in charting a path to product-market fit, or even a product launch, is to identify this space of people who you are building a startup for and to identify a set of observed problems/pain-points that sections of that group of people are experiencing. This latter task, the process of documenting the problems/pain-points of a segment and identifying subgroups of customers whose highest priority pain-points can be serviced by the same solution, is a process called “customer discovery,” which we will explore in more detail later in this series. However, the former task, the challenge of identifying a space of people to build a startup for, is much more subjective; it requires founders to look inward and identify which segment of people they empathize with most, they understand best (or want to understand best), and what industries/sectors/disciplines are most interesting to the founder. As will be repeated in some shape-or-form ad nauseum over the course of this series, empathy and ability to listen to your target customers is a core tenet of software venture-building, so the kinds of customers whose problems will serve as the basis of one’s venture must be customers who the founders are genuinely passionate about serving.
Ultimately, the aim of a new venture (and business in general) is to solve some extant problem affecting some group of people, and for that problem to be valuable to warrant enough payment from that group of people in order to support the cost of facilitating the solution. Identifying a problem space is a broad task where aspiring founders ask themselves:
1. What problems in the world are important to us, and why?
2. Who is affected by these problems, and how?
3. What are the potential profiles of people, groups, or institutions affected by these problems?
4. Where are these problems most prevalent, and how painful are these problems?
5. What are problems adjacent to the ones identified?
By going through the exercise of justifying the importance of a problem space, founders not only establish the area they want to work in, but they also justify its importance and use that as a source of motivation to set about finding and providing a viable solution. While entrepreneurs may be motivated by the short-term profit advantage to entering a market early, the reality of venture-building is that it is a long process (several years) before the venture actually returns the kind of value an entrepreneur may be seeking; as such, motivation beyond money is useful for keeping entrepreneurs focused on their ventures. And that starts with identifying the problem space and justifying its importance to the founders.
However, a summary of the problem space is not enough to set upon building a solution, since there are numerous potential questions to be answered. In the case of the first example problem space: Which farmers are we talking about? How much has the problem impacted their livelihoods? What have they tried so far, and why haven’t the existing solutions worked? Which crops are most heavily impacted by the problem at-hand? What are they doing right now to adapt to more volatile weather patterns? And so on. So where exactly do we start with respect to building a software venture to address perceived problems in a particular space? These questions, will be addressed through the process of customer discovery, which is the instrumental next step following problem space identification, and precedes any design or development of a solution. Let’s examine why customer discovery is the necessary next step for founders.
Instinctively, many aspiring founders will look at a problem space and immediately start crafting a solution to the problems observed. For example (returning to the farming problem space example), we could posit that an analytics tool with weather data could help farmers prepare their crop rotations more efficiently. This process is useful, but it’s not alone a strong enough case for launching a venture since ideation of a solution alone does not justify the need or existence of that solution. This may seem obvious, but it is a routine logical framework potential founders follow: (1) they’ll identify a problem space, (2) they’ll spec out a robust and powerful solution, (3) they’ll look for data that supports their proposed solution, and (4) they’ll set about trying to attract technical and financial resources to actualize their idea. The problem with this line of thinking is that, fundamentally, one will have a biased understanding of their customers and end-users; in this line of logic, founders are jumping straight from a hypothetical solution to seeking out data that already confirms their understanding of the problem-space. As such, the venture runs a high risk of (and usually results in) not being the appropriate solution for the customers in the problem space, which consequently causes the venture to not progress as the hypothetical solution misunderstands the real high-priority pain-points of its customers.
The risk of failure at this early-stage can be mitigated through the process of customer discovery, upon which the next articles in the series will expound. In this process, the broader statements surrounding a problem space will be granularized into more specific customer segments, and these segments will provide a “mapping” to what potential minimum-viable products (MVPs) could be. Customer discovery also allows founders to build a business case for investing in development, which is a necessary part of attracting angel or seed-funding (or providing a greater level of assurance as to the validity of using one’s own capital in the venture). Ultimately, in the pursuit of building software that identified customers actually want, it’s only reasonable to start with discerning their demands (solution features) and reasons for these demands (pain-points).