Build the Right Thing
Kickstart ResearchOps:
- Kickstarted Research Operations practices for scaling Design Discovery;
- Introduced Research Repo & Data Repos.
- Rounded-up and rounded-out the Personas;
- Setup Documentation with guidelines, best practices and mini research roadmaps;
- Improved the tooling for qualitative research handling, tagging, parsing and compiling insights

Build the Thing Right
UX Design improvements on Core product including:
- Better UX Discovery to our roadmaps,
- Design Systems: Working with Core Design group to build-out and align the Design System(s) for Core product
- Identifying and Fixing UX debt
- Iterative User Testing
- ChatOps: discovery and definition of ChatOps features for Developer Experience
Setting up ResearchOps
Having some experience of a large scale research operation from my Oracle days, I saw that this was missing at CloudBees, and still to be done: Not necessarily my domain but I rolled up my sleeves and began installing the following high-level items into our tooling & processes and rolled out in three parts:
* Outlined the Double Diamond Design Process;
* Created Confluence guidelines & related Jira Epics created the necessary documentation and tasks for running research operations correctly and efficiently:
* Setup ResearchOps Tooling (Shared Research Repo); Socalized it with Design & PM.
The UX Double Diamond Model and UX Workshops
Stepping into a new Product Team without much prior experience with design process calls for some contextual workshops, and an introduction to the designer process. The model I like most and usually use is the Design Council double diamond, which breaks down the Design Thinking process into these subsections:
Model the ResearchOps model into Confluence documentation and a linked Jira board Epic
Because we work in Confuence and Jira it made sense setting up the high-level guidelines and guardrails for running a research operation in those tools primarily. Here is a diagram of the above flow converted into some Research steps in Confluence:
And the corresponding Jira Epic:
Next Step: Research Repo
Setup ResearchOps Tooling: Research Repo and Config
Having a shared research repo is essential to a research-led organisation, informing product across the board and available and open to everyone.
I examined and identified a great tool for this called Dovetail, I made the pitch for it, and we (eventually) bought our licenses, which we then expanded from the design team to the product org.
Before socialising to Design or Product However, we needed some guidelines and guardrails here also:
a) Research Templates aligned with the Confluence documentation to get "Researchers" up and running quickly.
b) A research Taxonomy: The Dovetail research repo works by tagging transcripted conversations from Interviews: we needed alignment on the tags we use so that searching, filtering and categorising is aligned later on:
And here they are converted into a Global set for all users.
These are then used when tagging transcriptions from user interviews:
And we do a lot user interviews
But the beauty of a tool like Dovetail as a complete research repo and with data taxonomy is that we can quite quickly pull up insights from searching and filtering across the board on all projects tagged with the same labels:
Then we put them into charts for analysis and presentations
The final piece is to pull together all the insights into Themes which become your insights - inside each of these are all the comments made by the customers that you tagged and grouped, compiled into nice summaries which are easily fed into the product iteration process.
In this example, some high level insights from the Interviews on DevOps Workload Analytics were:
Once this was in place, the hard part - you would think - is socialising it. The good news is that every Product Owner or Manager who saw this fell immediately in love with it and wanted access. Now all Design and Product are using this repo. FTW!
Honestly I didn't think it would come out this well at all but I had the support of my managers which really helped. I was so stoked I wrote a Medium article about it to share its success.
The short story of its success is that everyone was so pleased that the Data Insights team got pulled into the Design team and we hired our first - and second - researchers! 
In addition, research and data is kicking off in a big way at CloudBees, mainly thanks to the open culture and this is a big win for everyone.
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