Flow Metrics

Returning to the time I was told by my team manager I was going to form a new team to work on a new product, I’ve never thought that in almost 4 years, my team has grown and sustained in a way different than other teams in the company. When I was in my previous team, many people struggled using Scrum. People are obsessed with Story Pointing. Some team members refused to attend the Sprint Review and Retrospective. Everyone works without a clear goal but only emptying the backlog and fighting the deadlines. Arguments like Code Refactoring versus meeting the deadlines and estimation versus actual were everywhere. There were times that I doubted if Scrum brought us a tough time. There were times that I almost wanted to quit the job due to the burnout. ...

As a Scrum Master of the team, I often raise questions to stimulate the team’s discussion and improve their understanding of Scrum and other frameworks or practices we use. “It’s Thursday and the fourth day of our 5-day Sprint,” I said, “If I pull a Product Backlog Item from the Backlog, I have to finish it by tomorrow, or else the Work Item Age will be increased by 2. Should I pull it or slice it to guarantee I can finish it by tomorrow?” ...

Every system operates under specific conditions, including Kanban with Flow Metrics. Of the 4 Flow Metrics, it is important to understand that Kanban with Flow Metrics is supported by Little’s Law. Little’s Law states that the average number of customers in a stable system is equal to the average arrival rate multiplied by the average time a customer spends in the system. To uphold Little’s Law, the system must be in a steady-state condition. ...

Last time, I described how my team applies Flow Metrics with Scrum. Although we don’t often estimate the short-term delivery, we are sometimes asked when a big feature will be completed. In the Story Points era, we used Story Points and calculated the average velocity of the previous 3 to 5 sprints for forecasting. In theory, averaging is the easiest way to forecast. However, in reality, unexpected situations may arise. For example, someone may call in sick, there may be a public holiday in the middle of the Sprint, or a PBI may be blocked by external parties. It is easy to fall into the trap of relying solely on averages, resulting in an unrealistic forecast. Moreover, communicating Story Points to stakeholders can be challenging due to their inherent ambiguity. In such situations, Monte Carlo Simulation comes into play. ...

It has been over three months since I introduced Flow Metrics to my team. My team has changed their mindset when it comes to work. Today, I am going to discuss how I apply Flow Metrics to the team. Before implementing Flow Metrics, I created a spreadsheet and recorded all the Product Backlog Items (PBIs) created in 2023. Following Daniel Vacanti’s Flow Metrics for Scrum Team, the spreadsheet includes an Aging Work in Progress Chart, Cycle Time Scatterplot, and two Monte Carlo Simulations: “How Many” and “How Long.” I obtained the Service Level Expectation (SLE) for the Cycle Time. ...

Last month, I wrote a blog post about why I have refrained from using Story Points and capacity estimation in my team since day one. I have been delving deeper into Kanban and immersing myself in the materials, and I have started implementing it. After introducing Kanban and Flow Metrics to my team, I received a lot of questions and feedback from them. Kanban is a strategy for optimizing the flow of value through a process that uses a visual, pull-based system. There may be various ways to define value, including consideration of the needs of the customer, the end-user, the organization, and the environment, for example. ...

When I first practised Agile on my old team, one of the things I learned from the consultants was Story Points. Since then, it has been used in many product teams in my company. As all the teams use Scrum as the main framework, many colleagues even misunderstand Stories and Story Points as Scrum ideas. They’re actually from Extreme Programming. Stories Points were invented by Ron Jeffries, one of the three founders of Extreme Programming. They were invented to abstract from hours to complete an item. With the Fibonacci series, developers can easily say the bigger the Story Point is, the more complex the Product Backlog Item is, and the more uncertainty in developing the Product Backlog Item could be. Developers can use empiricism to vote for the size of a Product Backlog Item. With the aid of the velocity trend, they can select the Product Backlog Items into their Sprint Backlog. ...