Break down silos by capturing discovery in your backlog.
This blog was originally published as part of Optimal Usability’s CRUX Magazine.
Discovery is the process of uncovering new information and gathering evidence to inform your decisions.
Whether a team is conducting customer interviews, running ideation sessions, or testing out a new feature, discovery ultimately boils down to learning — to gathering new information in order to make better decisions. Of course, organisations have always needed to learn and adapt to survive, however the way that they learn has changed. In a recent article titled Competing on the Rate of Learning, BCG argues that we are actually in the third generation of “learning organisations.”
The first generation existed in the early 20th century, and focussed mainly on efficiency. A common example of this type of organisation is Ford with their Model T assembly line. Their goal was to deliver cars as quickly and efficiently as possible and so the majority of the learning effort inside the business was dedicated to continuous improvement and optimisation.
More recently, the second generation of learning organisations was faced with a new challenge - potential disruption and the need for innovation. While innovation itself is not new, organisations were suddenly expected to innovate at speed, and do so in parallel to their existing business operations. This left many businesses with the challenge of balancing the efficiency needs of their existing products, while simultaneously developing new ones.
And now, according to BCG, we are entering the third generation of learning organisations, which is being shaped by three important forces:
Firstly, we have unprecedented access to data. The explosion of Big Data, IOT devices and AI means that organisations have access to incredible amounts of data in essentially real time, and there is increasing pressure on organisations to leverage this data to make faster, smarter decisions.
Secondly, customer expectations are higher than ever and are changing rapidly. Enormous, resource-rich businesses like Uber and AirBnb are setting the standard that customers expect, and organisations are scrambling to keep up.
Lastly, disruptive, innovative new businesses, with access to the deep pockets of angel investors, are entering the market at an unprecedented rate, putting pressure on organisations to stay one step ahead and defend their marketshare.
These three factors combined create an environment where there is enormous pressure on organisations in this third generation to learn and adapt at lightning speed. This means that the rate at which a business is able to learn is the new competitive advantage. It’s no longer about efficiency. It’s no longer about optimisation or continuous improvement. It’s about learning, and therefore it’s about discovery.
The UX profession has, of course, long argued the importance of discovery, and in recent years, organisations have begun to sit up and take notice. The value of discovery and the importance of customer research and validation are more widely understood today than perhaps any other time in history. Thus the greatest impediment to organisations embracing discovery is no longer an unwillingness to do so, but instead an inability to do so effectively.
This inability stems from the fact that many organisations today have a significant imbalance in organisational capability and ways of working between discovery and delivery. While discovery as a practice is still relatively new to many, delivery processes have been maturing for years, resulting in established frameworks, tools and processes.
This imbalance manifests itself in three primary ways:
Discovery skills are isolated to specific roles, rather than being a core competency of the entire team, making it difficult to integrate discovery practice into the end-to-end operation of the business.
Discovery activity is often siloed from delivery activity, resulting is a sporadic, project based approach rather than continuous learning.
Discovery practice is fragmented across the organisation, resulting a proliferation of terminology, approaches and tools.
All of these factors conspire to make it incredibly difficult for organisations to embrace rapid learning and discovery. This is especially true for larger, more established organisations. These businesses are often already delivering at speed and therefore hesitant to slow down in order to implement an entirely new framework of cross-organisational discovery. However, there is one important step that organisations can take that will allow them to jumpstart their discovery practice without disturbing their current momentum.
Break down silos and improve visibility of discovery work by bringing it into the backlog.
An important first step in creating a strong discovery practice is to bring discovery work into the light and make it visible to the wider organisation. Teams need to break down silos, and ensure that discovery is an integrated part of the end-to-end product cycle, rather than merely a phase. Fortunately, teams with mature delivery practices already have a tool that does exactly this - the Agile backlog. A team’s backlog is not only the heart of their delivery practice, but has the potential to form the heart of their discovery practice as well.
The benefits of bringing discovery work into the backlog are numerous. For starters, the simple act of capturing discovery in the backlog increases visibility of the work that is being done. Anyone, in any team, can open up a sprint team’s backlog and see not only what they are delivering, but what they are learning as well. Beyond simply providing visibility, the backlog helps teams build a shared understanding of what discovery work is being done and, most importantly, why. This understanding is the first step in building an organisation-wide culture of learning and experimentation.
Perhaps most important however, are the conversations that the backlog grooming process creates. Capturing discovery work in the backlog allows it to benefit from the same level of rigour, refinement and discussion that delivery work enjoys. As the discovery stories are refined, the entire, cross-functional sprint team, has the opportunity to understand and contribute to the discovery process. Together, they are able to refine, estimate and prioritise discovery work right alongside delivery, making it a first class citizen of the PDLC.
Bringing discovery into the backlog sets businesses on the path towards rapid learning. It helps the wider business build capability in discovery processes and develop an appreciation for their value. It also encourages a continuous and consistent discovery approach, which is key to achieving speed of learning.
Capturing discovery in the Agile Backlog
For teams that decide to embrace this approach, the remaining question they face is how to go about actually capturing discovery in their backlogs. After all, tools like Jira are designed specifically to cater to agile development workflows. The standard backlog items — user stories, tasks, bugs and epics — don’t provide an obvious solution to capturing less defined, more open-ended discovery work. Capturing discovery as a user story isn’t appropriate - stories are about delivering end-to-end customer value. Tasks and sub-tasks don’t work either. They’re too vague, aren’t estimated, and don’t encourage teams to capture and refine the important details of the work to be done.
To effectively capture discovery, teams require specific, custom backlog items that are designed to handle the organic, open-ended nature of discovery. One approach is to create two entirely new, custom backlog items:
Research- These backlog items are used to capture divergent, open-ended discovery activities. Research items focus on answering open-ended questions. For example “How do people between the ages of 25 and 35 currently manage their personal finances?” or “How might we support young people in adhering to a budget?” The defining characteristic of a research item is that it’s divergent - teams will have more ideas and information at the end of the process than they started with.
Experiment - These backlog items are used to capture convergent, validation-based activities. They focus on answering closed, binary questions. For example “If we create a feature that sends alerts when people are close to their budgeted spending, will we see a reduction in overspending?” In this case, we have an idea or hypothesis and we’re trying to determine if it’s correct or not. The defining characteristic of experiments is that they are convergent - they help teams focus on just the most effective, successful ideas.
Each of these custom backlog items functions in the same way as a user story - they can be refined, and have key information and acceptance criteria attached. They can be estimated using story points and prioritised against other items in the backlog. However they are distinct in nature, and ensure that discovery is captured and visible to the entire team.
To summarise — speed of learning is the new competitive advantage, but the imbalance between discovery and delivery maturity is preventing organisations from learning effectively and continuously. Bringing discovery into the agile backlog increases visibility of discovery work, and begins to close the capability gap, laying the foundations for teams to learn and innovate at speed.