Evolving culture and ways of working through DevOps, Lean, and Agile.
It’s likely a coincidence, but I’ve recently noticed a slew of issues arising in my work around test data management. As I dug into this, I found a disappointing lack of prescient information on how to manage this in an Agile environment. It’s going to be a quick one this week, but here’s my take on agile test data management.
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You can’t move for people talking about the project to product journey lately. Getting organisations to start mapping out what their products are so they can build cross-functional teams around them. Projects are transitory and lose us all of the learning, we want long-lived squads! While these sentiments are all rock-solid, unfortunately, they’re missing the point. I’m going to be controversial and say that creating a product team simply isn’t good enough. What you actually need is outcome alignment.
Continue reading “A product team is not the answer”
One of the largest challenges preventing organisations from competing effectively in the market is their structure. When you are optimised for technology or role, then you are not optimised for customer value. But how do you actually get there? What does good look like for your organisation if you went back to the drawing board? I’m going to share a process I’ve developed for redesigning a system for outcome alignment.
Note that this is not going to be a full article on digital transformation or strategic redesign. I am simply going to focus on the guiding principles and a specific approach to assist in exploring an outcome aligned design.
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The role of the project manager in Agile is often a complicated one. While there is little concrete direction by many of the frameworks, it is often understood that a traditional project manager may often find themselves moving into a Scrum Master or Product Owner role. The intent behind this guidance is clear, there’s no need for a Project Management Office (PMO) where we’re going. I disagree. Let me introduce the Lean PMO.
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A dependency chain is where you have a number of functions that all need to do some part of a piece of work in order to fully deliver it. These functions complete their part and then pass it along to another.
In my last article I showed why your IT requests were likely taking so much longer to service than you expected. But what if you have multiple dependencies chained together? How can you get a rough idea of how long something is going to take when you have a disconnected dependency chain rather than an end to end view of the system. In this article, I’ll explain the process of getting a rough statistical idea of how long something is going to take when you have multiple dependencies all linked together. I’ll explain this through an R script, but the concept is easily transferable.
Continue reading “Dependency Chain modelling”