This morning on my way into work, I was traveling from a different train station. Totally unfamiliar with the station layout, I was for a moment, confused about which end of the platform to stand on. I would be exiting the train at Southern Cross station, and I wanted to be at the Collins St end of the platform when I exited. Another passenger must have registered my puzzled expression and asked me if he could help. I explained that I needed to commit to waiting for the train at one end of the platform, or at the other end, and that I would either be very wrong, or right. At that moment the thought struck me that this was a good analogy for Lean Startup thinking in product development. If I was right, then I’d have only a short walk to catch my next train. But if I was wrong, then I’d know just as soon as I arrived, and I could correct my path.

In his 2011 book, The Lean Startup, Eris Reis proposes that key to the success of new product ideas is testing your assumptions. Rather than launching with a fully-fledged product, on which you have expended huge amounts of effort and money, he advocates for pushing to market at least some features, to test your assumptions about what would be useful or attractive to customers. This allows you to fail early and inexpensively, or succeed early too!

There are a few approaches to this. One is what he calls “smoke and mirrors”, which is more an approximation of a product than the real thing. It provides some functionality for customers, but this is not necessarily driven by the end state processes or software. Instead it simply approximates the end state, so that you can test if the end state is going to meet customers’ expectations, ahead of investing in building the end state.

The advantage of taking this approach is pretty clear. You can validate your assumptions before investing the resources to build the end state. In the university, this type of model could apply if we were building a new online form to replace an existing process. Our product vision might be an end to end process that collects the information required from students and manages cross faculty exchange of information. Taking a Lean Startup approach, perhaps we could build an interface that collects the information, simply to validate that it will be compelling for students, but retains some manual manipulation of data, just until we validate we are collecting the right data and have created a form that is compelling enough for students to engage with. Obviously the “smoke and mirrors” manual part of the process can be replaced with a digital solution once we have validated our assumptions, and perhaps pivoted to find the optimal way to collect the initial information required.

Another way that Reis suggests arriving at an optimal product is through releasing something that may not entirely constitute a minimum viable product. He argues for putting aside our deeply held beliefs that we can only launch an end state high quality product. Where a product provides new and exciting functionality for users, assumptions about if it will be useful and compelling for users, also need to be tested. By launching with just one feature, instead of a planned 10 features, users can still interact with the product and provide feedback and requests for additional features that can be built in response to this.

In my work environment, this might look like us responding to some website feedback about a certain feature that users would like to see on the website. We might develop the beginnings of this feature and then advise the users who requested it to have a go at interacting with it. By engaging in a dialog with users around the beginnings of the feature, we are most likely to be able to shape it in such a way that it best fits users’ needs.

Resisting the urge to hold back until a fully featured version is available can be a huge mindset change. Essentially though, this type of scenario is typically played out with early adopters, who are the intelligence behind driving future features and pushing the boundaries of the Internet of Things. These users tend to be heaps more tolerant of early prototypes and appreciate engagement on development of product features.

My first scenario in this post was about being right, or very wrong. Obviously the stakes aren’t very high, when all I’m doing is choosing between which end of the train platform to stand on. The idea in Eric Reis’ Lean Startup model, accords with this though. Test your assumptions early and always, when the stakes aren’t high. Users will appreciate it, and so will those holding the purse strings to your product!