These days we’re all under pressure to produce new software, new features and new interface improvements quickly. And the speed demanded by a market of disruptors and startups is ever-increasing.
Within this context, techniques such as agile and lean startup can help immensely to identify critical issues, bring people together in constructive forms and ensure a focus on delivery of software. However, in the rush to ideate, build an MVP and launch, we can still sometimes forget to validate assumptions and fail to incorporate the right kind of user input through selected contextual research. When this happens, sometimes the results can be frustrating; other times they can be disastrous.
Two recent instances have highlighted this. One is well known: Microsoft’s now-infamous Tay AI bot fiasco. The other is virtually unknown but personally frustrating to me: the recent relaunch of the public website for my son’s school Trinity Grammar.
The other night I attended a presentation from Adam Ludwin, CEO of Chain. Chain is a blockchain infrastructure company from San Francisco that completed a USD$30M fundraising from finance industry companies last September.
Adam spoke about how blockchain will transform not just finance but a range of industries where assets can be easily digitised. Here’s my take on some of the key points in the presentation…
A blockchain supports digital assets
Just as the digital revolution allowed for the creation of digital assets such as music, news and movies, it also supports the creation of truly digital money.
the observation that the threat to traditional banking practice from Silicon Valley comes as much from the adoption of new software development practices as from new technologies and disruptors;
the benefits of agile in terms of delivering rapid product innovation;
the importance of being prepared to ‘fail’, ie pivot and re-position; and
the observation that ‘fast fail’ does not necessarily signify ‘failure’ as much as ‘hypothesis testing’ – in other words allowing product design/development decisions to be based on observations and facts rather than assumptions and preferences.
Much of the discussion in recent years about payments disruption has highlighted the potential benefit of new capabilities to displace the payment component of a commercial transaction to the background; simplifying the process, removing friction and emphasising the value-adding component of the transaction.
The case in point that is always cited is, of course, Uber. Recent coverage in Sydney of yet another round of outrage over Uber’s surge pricing has highlighted the brand risk associated with making payments ‘too invisible’ In the most recent spate of complaints, Uber customers have complained about fare increases of up to 800% over new year’s eve.