Agility@Scale: Strategies for Scaling Agile Software Development

A common goal of IT governance is to determine the productivity of various techniques, tools, and people as part of the overall effort to improve said productivity. If you can easily measure productivity you can easily identify what is working for you in given situations, or what is not working for you, and adjust accordingly. A common question that customers ask me is how do you measure productivity on agile teams. Although you could use traditional strategies such as function point (FP) counting, or another similar strategy, this can require a lot of effort in practice. Remember that we don't only want to measure productivity, we want to do so easily. Ideally it would be nice to do so using information already being generated by the team and therefore we won't add any additional bureaucratic overhead.

A common metric captured by agile teams is their velocity. Velocity is an agile measure of how much work a team can do during a given iteration. At the beginning of an iteration a team will estimate the work that they're about to do in terms of points. At the beginning of a project the team will formulate a point system, which typically takes a few iterations to stabilize, so that they can consistently estimate the work each iteration. Although the point system is arbitrary, my team might estimate that a given work item is two points worth of effort whereas your team might think that it's seven points of effort, the important thing is that it's consistent. So if there is another work item requiring similar effort, my team should estimate that it's two points and your team seven points. With a consistent point system in place, each team can accurately estimate the amount of work that they can do in the current iteration by assuming that they can achieve the same amount of work as last iteration (an XP concept called "yesterday's weather"). So, if my team delivered 27 points of functionality last iteration we would reasonably assume that we can do the same this iteration.

So, is it possible to use velocity as a measure of productivity? The answer is not directly. For example, we have two teams, A and B, each of 5 people and each working on a web site and each having two-week long iterations. Team A reports a velocity of 17 points for their current iteration and team B a velocity of 51 points. They're both comprised of 5 people, therefore team B must be three times (51/17) as productive as team A. No! You can't compare the velocity of the two teams because they're measuring in different units. Team A is reporting in their points and B in their points, so you can't compare them directly, The traditional strategy would be to ask the teams to use the same unit of points, which might be a viable strategy with two teams although likely not if you have twenty agile teams and particularly not if you have two hundred teams. Regardless of the number of teams that you have it would minimally require some coordination to normalize the units and perhaps even some training and development and support of velocity calculation guidelines. Sounds like unnecessary bureaucracy that I would prefer to avoid. Worse yet, so-called "consistent" measurements such as FPs are anything but because there's always some sort of fudge factor involved in the process which will vary by individual estimator.

An easier solution exists. Instead of comparing velocities you instead calculate the acceleration of each team. For example, consider the reported velocities of each team below. Team A's velocity is increasing over time whereas team B's velocity is trending downwards. All things being equal, you can assume that team A's productivity is increasing whereas B's is decreasing. Of course it's not wise to manage simply by the numbers, so instead of assuming what is going on I would rather go and talk with the people on the two teams. Doing so I might find out that team A has adopted quality-oriented practices such as continuous integration and static code analysis which team B has not, indicating that I might want to help team B adopt these practices and hopefully increase their productivity.

Team A: 17 18 17 18 19 20 21 22 22 ...Team B: 51 49 50 47 48 45 44 44 41 ...

There are several advantages to using acceleration as an indicator of productivity over traditional techniques such as FP counting:1. It's easy to calculate. For example, the acceleration of team A from iteration 1 to iteration 6 is (20-17)/17 = 0.176 whereas for team B it is (45-51)/51 = -.118. Of course, you don't need to calculate the acceleration over such a long period of time, you could do it iteration by iteration, although I find that doing it over several iterations gives a more accurate value. You'll need to experiment to determine what works for you.2. It is inexpensive. Acceleration is based on information already being collected by the team, their velocity, so there is no extra work to be done by the team. 3. It is unlikely to be gamed. Teams aren't motivated to fake their velocity because it provides them with important information required to manage themselves effectively. 4. It is easy to automate. For example, Rational Team Concert (RTC) calculates velocity automatically from its work item list (an extension of Scrum's product backlog) and does trend reporting via it's web-based project reporting functionality, providing a visual representation of the team's acceleration (or deceleration as the case may be).5. It offers the opportunity for more effective governance. This approach reflects three of the practices of Lean Development Governance: Simple and Relevant Metrics, Continuous Project Monitoring, and Integrated Lifecycle Environment.6. You can easily adjust for changing team size. If the size of a team varies over time, and it will, this metric falls apart the way that I've described it. To address this issue you need to normalize it by dividing by the number of people on the team to get the average acceleration per team member.7. You can easily monetize this metric. By knowing the acceleration of the project team and knowing how much they're spending each iteration, you can estimate the amount of money you're saving through process improvement. For example, if you're spending $100,000 per iteration and your acceleration is 2%, your cost savings is $2,000 per iteration.

Of course, nothing is perfect, and there are a few potential disadvantages:1. It is an indirect measure of productivity. Truth be told velocity really is a productivity measure, it's just that because it's measured in different units it's difficult to compare between teams. Acceleration is merely an indicator of the change in productivity.2. You actually need to measure what you're interested in. When you step back and think about it, you're not really interested in measuring your productivity, regardless of what the metrics wonks have been telling you the past few decades. In this case what you really want to know is your change in productivity because your real goal is to improve your productivity over time, which is what acceleration actually measures.3. Management must be flexible. For this to be acceptable senior management must be willing to think outside the "traditional metrics box". Using a non-standard, simple metric to calculate productivity? Preposterous! Directly measuring what you're truly interested in instead of calculating trends over long periods of time? Doubly preposterous!4. Your existing measurement program may be questioned. Once management learns how easy it can be to obtain metrics which enables them to truly govern software development projects they may begin to question the investment that they've made in the past in overly complex and expensive metrics schemes. This can be dangerous for the metrics professionals in your organization, particularly if your metrics group doesn't have valid measurements around the value of their own work. Ummmmm....5. The terminology sounds scientific. Terms such as velocity and acceleration can motivate some of us to start believing that we understand the "laws of IT physics", something which I doubt very highly that as an industry we understand. All it would take is for someone to start throwing around terms like "standard theory" and "unified model" and we'd really be in trouble. Wait a minute..... ;-)

In summary, measuring the acceleration of development teams is an easy to collect, straightforward measure of team productivity. I hope that I've given you some food for thought, and would be eager to hear about your experiences applying this metric in practice.

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