What the impact challenge taught about customer discovery

The Impact Challenge at International Conference 2018 offered a practical lesson in how promising ideas become useful solutions. Held in New York from 18–20 November, the event asked undergraduate participants to think about workforce disruption, leadership and entrepreneurship through an applied, team-based problem.

For an Australian audience, the most relevant takeaway is that customer discovery begins long before a product launch. It is the disciplined process of learning how people work, what frustrates them, what they already do and whether a proposed solution fits their circumstances. That mindset matters in a market stretching from Sydney and Melbourne to regional towns, remote communities and fly-in fly-out work sites.

Start with the problem, not the pitch

A challenge brief can tempt teams to jump straight into solutions. Participants may imagine an app, training service or employment platform before speaking with the people affected by the issue. Customer discovery reverses that order: first identify the situation, then investigate the problem, and only later consider what might address it.

This is particularly important when discussing the future of work. Automation, flexible employment and changing skills affect a university graduate differently from a warehouse worker, a small-business owner or a regional employee commuting to a mining site. A broad statement such as “people need better career support” is a starting assumption, not a validated insight.

Listen for real behaviour

Good discovery conversations focus on what people have done rather than what they say they might do. Someone may claim they would use a new platform, yet continue relying on a friend, a Facebook group, a recruitment agency or a spreadsheet. Those existing workarounds reveal priorities, frustrations and willingness to change.

The same principle applies across Australia’s diverse employment landscape. A café owner in Brisbane, a TAFE student in Geelong and a contractor in Western Australia may describe “finding work” in very different ways. Asking about the last time they solved a related problem produces more useful evidence than asking whether they like an idea.

Separate evidence from enthusiasm

The Impact Challenge showed why teams need to distinguish a compelling story from a proven customer need. A passionate interview can make an assumption feel certain, especially when it aligns with the team’s original belief. Stronger research looks for repeated patterns across several people and settings.

Interviewers should record the exact language customers use, the frequency of the problem, its cost and the workaround already in place. If a business says staff training is difficult, follow up on time lost, budget limits, approval processes and previous attempts. These details indicate whether the issue is urgent enough to justify a new solution.

The event’s wider focus on changing workplaces also reinforces the value of human capabilities. Research into soft skills matter helps explain why empathy, communication and adaptability are central to customer discovery. They allow a team to hear uncertainty without forcing it into a neat answer.

Test the riskiest assumption first

Customer discovery is most efficient when teams identify the belief that could make the entire idea fail. It might be the assumption that employers will pay, that workers have enough time to participate, or that customers trust a digital service with sensitive information. Testing that point first prevents months of work on an attractive but unworkable concept.

A simple experiment can be more revealing than a polished presentation. A team might offer a manual version of the service to five users, create a short workshop, or ask an employer to commit to a trial date. The aim is not to imitate a finished product. It is to observe whether people take a meaningful step.

For Australian ventures, payment and access can be decisive. A small organisation may want the outcome but lack procurement capacity, while a regional customer may face patchy connectivity or limited local providers. A test that ignores these conditions can create false confidence.

Let local context shape the solution

Australia’s geography changes how customer problems appear. A service designed around dense city networks may work in inner Melbourne but struggle across the Northern Territory, where distance, connectivity and staffing patterns influence every interaction. Customer discovery must therefore include the practical environment in which a product will be used.

Language matters as well. People may describe a problem casually—“It’s a bit of a pain,” “I’m flat out,” or “I’ll have a yarn with the manager”—while still dealing with serious consequences. Researchers should respect that conversational style without mistaking informality for low urgency. They also need to account for multicultural workplaces, accessibility needs and the role of trusted community organisations.

The Australian market has a strong small and medium-sized business base, so the buyer and user are often close together. That can speed up feedback, yet it can also make personal relationships overly influential. A friendly conversation with one owner is useful evidence, but it should be checked against other businesses before the insight becomes a market claim.

Turn learning into a focused experiment

A useful discovery cycle ends with a decision: continue, change direction or stop. Teams should summarise what they heard, identify the strongest evidence and state which assumption remains uncertain. This creates a clear bridge between interviews and action rather than leaving research as a collection of notes.

The comparison below shows how challenge-based thinking can shift a team from presentation mode to customer learning.

Early approach	Discovery-led approach
Build a complete product first	Test the riskiest assumption early
Ask whether people like the idea	Explore recent behaviour and workarounds
Treat one strong interview as proof	Look for repeated patterns across customers
Design for an average user	Investigate local, social and workplace context
Measure attention or praise	Measure commitment, use and willingness to pay

The most practical next step is to choose one target customer group, write down three untested assumptions and conduct five interviews about a recent problem before designing the solution.