Catherine Kraus: What leads Scrum teams to be unpredictable, and unreliable!

The team had a lot of unfinished work, and sprint-to-sprint spillovers. It started to feel that the management of the work was out of control. As Catherine investigated, she found that a lot of work was being added to the Sprint after planning. All of these new items diverted the team’s focus, and they were no longer predictable, or able to finish some of the critical user stories planned. In this episode, we explore what were the reasons the team got to that point, as well as what Catherine learned that helps, still today, avoid falling into the same trap.

About Catherine Kraus

As a Scrum Master & Team Coach, Catherine Kraus inspires and galvanizes others into action with her playful and pragmatic approach. She works with organizations to build happier, healthier teams with purpose. She has over 15 years experience leading various transformation and change management projects in IT, Finance, HR & Marketing.

You can link with Catherine Kraus on LinkedIn.

BONUS: The art, and science of making prediction with #NoEstimates. With Dan Vacanti and Marcus Hammarberg

We explore a real-life project that Marcus was part of, and how the #NoEstimates methods he used helped him make predictions, even if did not estimate the work to be done.

This conversation started from an article that Marcus had posted earlier on social media. In that article Marcus explained how he had used data, as opposed to estimates to make a prediction of when the project would be finished. This approach still creates a lot of controversy on twitter, even if it has been (at the time of recording) 10+ years since the original discussion around estimates started by Woody Zuill and Vasco Duarte on twitter under the tags of #NoEstimates and #Estwaste respectively. 

As Marcus quickly found out in this project, the rate of progress could not have been predicted easily at the start (if at all). When he first started the project, the progress was swift, but at one point he faced a problem he could not solve for several days. This phenomenon is not new for any programmers in the audience, and is quite common. Also, one of the reasons why using methods like #NoEstimates (as explained in the #NoEstimates book, and in Marcus’ blog post), can help uncover information that estimation would not. 

Dealing with surprises: the information you need to share with stakeholders

Continue reading BONUS: The art, and science of making prediction with #NoEstimates. With Dan Vacanti and Marcus Hammarberg

BONUS: Enabling accountability with NoEstimates in government, with Craeg Strong

In this episode, we explore the use of NoEstimates approaches in a regulated and governmental environment. 

When Craeg and his team was called in to the Social Security administration, they were asked to help the Office of the Inspector General (OIG) assess the use of software development methods in an environment where the teams were adopting Agile methodologies, but the overall governance still followed the old school, linear (aka waterfall) methodologies. 

When the OIG is involved, it usually means that the organization being audited needs to prove that they are taking good care of public money invested in their processes. Therefore the challenge was to ensure that the teams were both following the Agile practices they said they had adopted, as well as taking the necessary actions to ensure proper use of public funds. 

Using NoEstimates to increase accountability

Continue reading BONUS: Enabling accountability with NoEstimates in government, with Craeg Strong

BONUS: Incremental Delivery in Business Intelligence (BI) and Data Warehouse projects with Raphael Branger

Raphael has been a guest on our regular show, and in those episodes, we approached the topic of Agile applied to Business Intelligence projects. In this episode, we dive deeper into the concepts and ideas that Raphael mentioned earlier, and we learn how Business Intelligence projects can be delivered incrementally, and in an agile manner. 

Slicing User Stories to enable incremental delivery

We start this episode with a practice that is critical for Agile teams: how to slice User Stories to enable the delivery of incremental value to customers. We discuss several strategies that Raphael uses to be able to deliver valuable functionality even in the first week of a project. 

Taking into account that usually, BI projects are executed by larger, and more traditional firms, his approach brings clarity and ensures that the team and the customer are able to evaluate the product from the first week. This practice is critical in collecting feedback from customers early on and avoiding producing products (dashboards, in this case) that no one will use. 

In this segment, we refer to a blog post by Raphael where he describes his User Story slicing approach in more detail.

#NoEstimates in BI projects

One of the inspirations for Raphael’s work on slicing User Stories was the #NoEstimates book and a few conversations that he and Vasco Duarte had in the early stages of Agile adoption at IT-LOGIX, Raphael’s company.

In Raphael’s perspective, the focus should shift from “sizing” stories to understanding what might be a good experience for the customer: customer delight; and then validating those assumptions directly with customers by delivering possible solutions very early on. 

As a way to apply #NoEstimates, Raphael started to apply the concept of “timebox” (limited time) to each of the User Stories being developed. His own rule is that a User Story should be developed within 1 or 2 days at the most, which pushes the teams to focus on what is critical to provide value to the customer. 

Timeboxing User Stories to validate assumptions

In this episode, we also explore how Raphael came to the realization that User Stories need to be timeboxed, rather than estimated. He shares a story of a project where the team produced a dashboard that did not get used by the customer (they had metrics). That was a transformative point in Raphael’s approach, leading him to focus on early and often delivery. Which led to the #NoEstimates heuristic that a User Story should be given a timebox. 

In this segment, we refer to the episode about a team that Runtastic that is using #NoEstimates, and how that has helped the team focus, and provide value faster. 

About Raphael Branger

Raphael Branger is a Certified Disciplined Agile Practitioner and a pioneer in adapting agile methods in the context of data and analytics projects. He works as a Principal Consultant Data & Analytics at IT-Logix in Switzerland with more than seventeen years of experience in business intelligence and data warehousing.

You can link with Raphael Branger on LinkedIn and connect with Raphael Branger on Twitter

 

BONUS: Marcus Hammerberg on predicting Software development without estimation

Marcus wrote a blog post about predicting progress in ‘well-defined’ projects. He used a simple example where uncertainty was very limited. You can read the details in the blog post. However, even when uncertainty about the work was low, the predictions he was able to do (and he collects quite a few metrics in that story), was limited. 

In this episode, we explore the limits to prediction, and how that affects how we should look at prediction in our own software projects. 

Embracing uncertainty and what that means in practice for software projects

Continue reading BONUS: Marcus Hammerberg on predicting Software development without estimation

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