11 February 2020
Imagine a team writing software for a shopping website. If we look at the team's output, we might consider how many new features they produced in the last quarter, or a cross-functional measure such as a reduction in page load time. An outcome measure, however, would consider measure increased sales revenue, or reduced number of support calls for the product. Focusing on outcomes, rather than output, favors building features that do more to improve the effectiveness of the software's users and customers.
As with any professional activity, those of us involved in software development want to learn what makes us more effective. This is true of an individual developer trying improve her own performance, for managers looking to improve teams within an organization, or a maven like me trying to raise the game of the entire industry. One of the things that makes this difficult is that there's no clear way to measure the productivity of a software team. And this measurement question gets further complicated by whether we base effectiveness on output or outcome.
I've always been of the opinion that outcome is what we should concentrate on. If a team delivers lots of functionality - whether we measure it in lines of code, function points, or stories - that functionality doesn't matter if it doesn't help the user improve their activity. Lots of unused features are wasted effort, indeed worse than that they bloat the code base making it harder to add new features in the future. Such a software development team needs to care about the usefulness of the new functionality, they improve as they deliver less features, but of greater utility.
One argument I've heard against using outcome-based observations is that it's harder to come up with repeatable measures for outcomes than it is for output. I find this point difficult to fathom. Measuring pure output for software is famously difficult. Lines of code are a useless measure even if they weren't so easily gamed. There's poor replicability with Function Point or Story Points - different people will give the same things different point scores. Compared to this, we are very good at measuring financial outcomes. Of course, many outcome observations are more tricky to make - consider customer satisfaction - but I don't see any of them as more difficult than software functionality.
Just calling something an “outcome”, of course, doesn't make something the right thing to focus on, and there is certainly a skill to picking the right outcomes to observe. One handy notion is that of Seiden, who says that an outcome should be a change in behavior of a user, employee, or customer that drives a good thing for the organization. He makes a distinction between “outcomes”, which are behavioral changes that are easier to observe, and “impacts” which are broader effects upon the organization. In developing EDGE, Highsmith, Luu, and Robinson advise that outcomes about customer value (reliability of a dishwasher) should be given more weight than outcomes about business value (warranty repair costs).
A consequential concern about using outcome observations is that it's harder to apportion them to a software development team. Consider a customer team that uses software to help them track the quality of goods in their supply chain. If we assess them by how many rejects there are by the final consumer, how much of that is due to the software, how much due the quality control procedures developed by quality analysts, and how much due to a separate initiative to improve the quality of raw materials? This difficulty of apportionment is a huge hurdle if we want to compare different software teams, perhaps in order to judge whether using Clojure has helped teams be more effective. Similarly there is the case that the developers work well and deliver excellent and valuable software to track quality, but the quality control procedures are no good. Consequently rejects don't go down and the initiative is seen as a failure, despite the developers doing a great job on their part.
But the problems of apportionment shouldn't be taken as a reason to observe the wrong thing. The common phrase says "you get what you measure", in this case it's more like "you get what you try to measure". If you focus appraisal of success on output, then everyone is thinking about how to increase the output. So even if it's tricky to determine how a team's work affects outcome, the fact that people are instead thinking about outcomes and how to improve them is worth more than any effort to compare teams' proficiency in producing the wrong things.
Seiden provides a nice framework for thinking of outcomes, one that's informed by experiences with non-profits who have a similarly tricky job of evaluating the impact of their work.
My colleagues developed EDGE as an operating model for transforming businesses to work in the digital world. Focusing on outcomes is a core part of their philosophy.
Focusing on outcomes naturally leads to favoring Outcome Oriented teams.
My fellow pioneers in the early days of Extreme Programming were very aware of the faults of assessing software development in terms of output. I remember Ron Jeffries and I arguing at an early agile conference workshop that any measures of a team's effectiveness should focus on outcome rather than output - although we did not use those words yet. That thinking is also reflected in my post Cannot Measure Productivity.
I recall starting to hear my colleagues at ThoughtWorks talking about a distinction between outcome and output appearing in the 2000s, leading Daniel Terhorst-North to suggest that outcome over features should be a fifth agile value. This favor to outcomes is a regular theme in ThoughtWorks-birthed books such as Lean Enterprise, EDGE, and the Digital Transformation Game Plan.
Alexander Steinhart, Alexandra Mogul, Andy Birds, Dale Peakall, Dean Eyre, Gabriel Sixel, Jeff Mangan, Job Rwebembera, Kief Morris, Linus Karsai, Mariela Barzallo, Peter Gillard-Moss, Steven Wilhelm, Vanessa Towers, Vikrant Kardam, and Xiao Ran discussed drafts of this post on our internal mailing list. Peter Gillard-Moss led me to the Seiden book and other work from the non-profit world.