When I say IT prioritisation, I mean the process by which we choose how to spend our limited resources within an IT organisation in order to deliver value. It doesn’t matter if the value for you is internal efficiency, external revenue, or anything in between. We simply can’t do everything, so we need to make choices.
These choices are often hard enough to make, requiring us to make decisions using imperfect knowledge in a complex environment, but we seem hell-bent on making it 10 times harder.
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.
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.
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.
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.
You’ve got a quick job to do so fire it off to an IT team. It should only take around half a day of effort so you expect to hear back by the end of the week. Three weeks later and you’re still waiting. So why is this happening? What is the deal with IT delays?
Apologies in advance to all scientists, engineers, and mathematicians.
Over this series, I’ve spoken in detail about the organisational impact of IT dependencies in your system. I’d like to take a diversion and discuss how it can impact the individual.
I posit that even without the work benefits you could derive from eliminating dependencies, the quality of life changes you could bring about would more than pay for the effort.
This isn’t an article about workplace stress, we’re all pretty familiar with its cost to our economy. Nor is this an article about the cost of employee churn. It’s not even about the cost to productivity through disengagement. Let’s move forward knowing the impact of people not being happy.
After some of my recent articles on building a dependency map, a few people got in touch asking for tips on actually creating them. Here’s a quick way to get started.
You might have noticed the following example in my previous posts.
I created the graphic above with an amazing bit of kit called Neo4j. It’s actually an incredibly sophisticated graph database technology, so it almost feels a little sacrilegious to be using it for this.
If you’re not up to speed on the concept of dependency mapping, then I’d suggest taking a look at my previous post where I talked through how to go about building a dependency map.
So what happens now? You’ve gone through the workshop and now have a bunch of data that’s telling you what? Something about your system? I’m going to run through some of the actions I take when attempting to understand a dependency map.
Recently, I published an article where I discussed the concept of dependency as a proxy for complexity. I also tried to show that complexity is the biggest aspect to consider when attempting to improve the flow of value. This is all part of a concept I call Dependency Mapping.
Following publication of the article, I had a few people who read it on LinkedIn reach out for some advice on actually doing it in their place of work. In this article I will dig deeper into the process by which we can start to map out dependencies. With the map completed, we can then work to remove them.
Dependency maps are going to be messy as they try and convey a huge amount of information. We’ll aim small, and then offer some suggestions for improvement from there.