As I mentioned in the first post — a researcher conducting a sprint should not rely on a fixed method of working. Instead they should develop principles and philosophies that can guide them.
One important principle is to embrace the world of digital platforms.
Often, when I recommend a new platform to someone, I’m met with comments along the lines of ‘oh no, not another platform’. This attitude will hinder an insight sprint.
I’m not suggesting that you need to become an active user of every social network on the web. I am saying you should keep an eye out for anything that can facilitate the capture of information in a new way.
Some Examples
There are four areas of the sprint where a knowledge of digital platforms comes in useful.
- Engaging with participants — for example, I have used LinkedIn to quickly recruit, set up and run a community of business leaders. I have used WhatsApp to run multiple discussion groups
- Netnography — I’ll talk more about netnography in a later post, but this refers to finding information from forums and social networking sites
- Internal communication — Slack is a great tool for internal comms, it replaces the formality of email with the informality of instant messaging.
- Analysis — writing a shared Google Doc is one example of speeding up analysis, another is using Trello, which I’ll explore at depth now
Coding data in Trello
One of the most powerful tools I have come across is Trello. It affords rapid, collaborative, and colourful codification of insight.
Trello uses four dimensions to organise information:
- Columns with titles
- Colour coded tags that can run across the columns
- Multiple boards — you can link boards together to connect concepts
- Hierarchy — you can place the most important things at the top of the column
I’ve made a YouTube video that explores how to use Trello — watching that will help you understand the design of the tool, and how you can use it for research:
What Trello achieves is a powerful way to code your data. Coding data is important (coding qualitative data means organising it into groups). You cannot just rely on your brain to remember all the useful stuff.
Unfortunately, I see lots of researchers doing this. They will have multiple discussions, capture lots of insights, and then rely on their memory and ‘gut feeling’ about what an answer is. If you aren’t leaning on data, then you aren’t doing research.
One further reflection on the coding of data is the triangle below. Although this represents a more traditional (and less agile) approach to coding qualitative data, it has strong implications:
In the context of an insight sprint, we can see level 1 as rapidly creating a Trello board with as much ‘stuff’ in as possible. Level 2 is the process of weighing up where you are at the end of the week. Level 3 is the creation of either a new Trello board, or tighter refined columns. And level 4 is the answer to the question the insight sprint set out to answer.
In summary - having an objective map of your thinking mapped out on Trello board will help you develop insights at the speed needed for a sprint. It is also something that can be built on at a later date. It is also something that delights a client. It also provides visibility over what you’ve been doing, allowing the client to follow along. And, when you offer your findings from a research sprint, the client can go over the data themselves, perhaps finding a story of their own.
The Future of Trello
I’ve been using Trello on projects for over a year now and I have developed refined ways of using it. I allow it to shape the way I think.
There are two reflections I have on the tool moving forward:
One, I would like to work out how to usefully collaborate on a Trello board at scale. How can we have 30 researchers all uploading insights on a single Trello board in a way that is clean and concise? I think that answer will lie in training — we need people that get it, and they need to all be involved from the start, taking ownership of the board from inception.
Two, the data can be downloaded as a JSON file. This means that it has the opportunity to be integrated into machine learning and artificial intelligence. It can connect human intelligence and artificial intelligence.
Of course, there are other tools that people can use. But Trello is extremely user friendly, making it easy for researchers to collaborate. And, to be blunt, we might as well all agree that we will use this method and platform so that we can begin exploring deeper ways to collaborate as an industry.
So finally, I think a quick note on Trello’s business model is important here. As a research industry — we will only support Trello if it continues to be free for researchers to use, and it allows open access to the data that we upload. Monetisation strategies should not hinder this.
Comments welcome :)
