This month I thought I’d go over a few books that have shaped the way I view agile practices. You’ll note that while none of them are actually agile implementation guides, they all speak to the values and principles that live behind agile implementation. While readers of these titles have typically been in the tech and startup world, each book contains an approach to tackling uncertainty that should resonate with anyone running an applied research project.
Zero to One – Peter Thiel (2014)
- Start Small: Capture the largest part of the smallest customer segment. It is better to start small and monopolise a tiny market than to try and capture a larger market. Starting small puts you in close contact with customers and helps you truly understand the value you are delivering. Once you have your systems up and running, then you can move onto larger target audiences.
- The Future Can Be Planned: People see the future as random, and as a result, a project with a good definite, simple plan will often be underrated and underestimated. Thiel argues that the future can be planned, and while your plan might be wrong, it is better to have a simple bad plan than no plan at all.
These ideas particularly apply to science and research projects. Projects are often undertaking amazing and novel research that can change entire industries – but at the heart of every project lies the question of adoption and impact. I’m always curious about how each project team defines their ideal customer and who they believe their early adopters will be.
The Lean Startup – Eric Ries (2011)
- Learning is everything: This book introduced the idea that ‘learning’ is one of the most important things you can do at the early stage of a project, and that everything we know is an assumption until validated through a range of small-scale experiments. The faster you learn, the more you know. The more you know, the more you can adjust your project to deliver the value you have set out to achieve.
- The Lean Canvas: Using a lean canvas, it is possible to untangle your assumptions and lay them out on a one-page plan. The boxes found in these one-page plans ask for your best guesses about how you’ll add value, how you’ll reach customers, how clearly you understand your customer’s problems etc. However, they are all assumptions until tested with validated learning. [note: I don’t think the lean canvas is actually mentioned in The Lean Startup, but it is too heavily affiliated with this book to ignore]
- MVPs: A key way to learn is through building Minimum Viable Product (MVPs). These are products that convey just enough of your project’s value to early adopters (customers) so you can quickly and cheaply learn if you are on the right path. This creates a cycle of building something, measuring its impact and then learning, or adjusting your course of action as a result of new knowledge. Build, measure, learn.
- Pivot: Adjusting your project in response to new information, or pivoting, is a good thing. Pivoting is not blindly splashing about looking for answers. It is a considered decision to change your activities so you have a greater chance of meeting your outcomes.
The takeaway for research projects is that if you want your research to have an impact you have to call out your assumptions and find ways to validate them through experiments. Most importantly, each project has assumptions that live beyond the central research questions they have been contracted to answer. There are many assumptions around adoption and implementation that the teams also need to consider.
Change by Design – Tim Brown (2009)
- The Venn Diagram of Desirability: An essential takeaway from Change By Design is that each project can be viewed through the overlapping lenses of desirability (will a customer use it), viability (does it make business sense) and feasibility (can we do it). Most projects begin with viability or feasibility in mind, and only consider the desirability of their idea once the project is complete. Change By Design challenges us to seriously consider whether customers will use our products/research before we invest too much in building them.
- Empathy: Customer empathy is the heart of design thinking. Being able to talk in detail about who you believe will find value in your initiative is incredibly powerful. Why? Because it raises adoption questions you’ll need to answer if you want your project to have true impact. It’s not enough to ring fence your work and hope that later on someone else will figure out who will find value in it.
Putting the customer at the center of scientific research is exciting. While applied research has always been about delivering value, customer-centric scientific research pushes teams to consider the actual end-user of their research, not just the organisations who are paying the researchers to explore an idea.
Scaling Up – Verne Harnish (2014)
- Metrics: The strongest projects have a small number of solid, achievable objectives. These objectives reflect the outcome you would like to achieve. The smaller the number of metrics, the clearer the projects vision will be. [note: I’d suggest that your outcome should state how your project will change a customer’s life.]
Metrics and outcomes are particularly important for applied research projects because research can often be seen as exploratory. Having a limited number of project outcomes phrased in a way that demonstrates the value of the project to a customer helps to ground exploratory projects in a united vision. This can prove challenging for teams that are accustomed to reporting against activities they have done rather than measuring themselves on how they are delivering impact to an end-user.
Agile is both a mindset and a practical approach to exploring new situations and adjusting course as needed. There are plenty of physical practices you can implement to help manage teams in ways that meet this mindset (scrum is particularly useful) but as a first step, developing customer-centric, outcomes-based mindsets is essential.
A few words on language
- Customers and end-users: refer to the people that will ultimately benefit from the research. This does not assume that they are actually customers paying with money but rather people that will use the thing you create. This includes terms like ‘markets’ and ‘target groups’.
- Project, product and initiative: refer to research projects.