Agility@Scale: Strategies for Scaling Agile Software Development
ScottAmbler 120000HESD Tags:  acceleration governance agileexec metrics velocity 5 Comments 38,039 Views
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.
ScottAmbler 120000HESD Tags:  metrics enterprise-agile governance disciplined-agile-deliver... 23,096 Views
Recently I have been asked by several customer organizations to help them to understand how to account for the expense of agile software development. In particular, incremental delivery of solutions into production or the marketplace seem to be causing confusion with the financial people within these organizations. The details of accounting rules vary between countries, but the fundamentals are common. In order to get properly account for the costs incurred by software development teams you need to keep track of the amount of work performed and the type of work performed to develop a given solution. Time tracking doesn't have to be complex: at one customer developers spend less than five minutes a week capturing such information.
Why is Time Tracking Potentially Valuable?
There are several financial issues to be aware of:
The point is that the way that a software developer's work is accounted for can have a non-trivial impact upon your organization's financial position.
What Do Agilists Think of Time Tracking?
So, I thought I'd run a simple test. Last week on LinkedIn's Agile and Lean Software Development group I ran a poll to see what people thought about time tracking. The poll provided five options (a limitation of LinkedIn Polls) to choose from:
The poll results reveal that we have a long way to go. Of the people inputting their time more of them believed it was a waste of time than understood it to be a valuable activity. When you stop and think about it, the investment of five minutes a week to track your time could potentially save or even earn your organization many hundreds of dollars. Looking at it from a dollar per minute point of view, it could be the highest value activity that a developer performs in a given week.
The discussion that ensued regarding the poll was truly interesting. Although there were several positive postings, and several neutral ones, many more were negative when it came to time tracking. Some comments that stood out for me included:
I think that there are several interesting implications from this discussion:
Disciplined agilists are enterprise aware. This is important for two reasons: First, you want to optimize your organizational whole instead of sub-optimize on project-related efforts; second, you can completely miss opportunities to add real value for your organization. In the anecdote I provided it was clear that many agile developers believe that an activity such as time tracking is a waste when that clearly doesn't have to be the case. Worse yet, although someone brought up the issues around capitalizing software development expenses early in the conversation a group of very smart and very experienced people still missed this easy opportunity to see how they could add value to their organization.
Granted, time tracking on an agile project team is nowhere near as sexy as topics such as continuous integration (CI), TDD, the definition of done, continous architecture, or many more. But you know what? Although it's a mind-numbingly mundane issue it is still an important one. 'Nuff said (I hope).
ScottAmbler 120000HESD Tags:  agile project-management continuous-delivery devops measures metrics 14,927 Views
I was recently involved in an online discussion about how to calculate the benefits realized by software development teams. As with most online discussions it quickly devolved into camps and the conversation didn’t progress much after that. In this case there was what I would characterize as a traditional project camp and a much smaller agile/lean product camp. Although each camp had interesting points, the important thing for me in the conversation was the wide cultural and experience gap between the people involved in the conversation.
The following diagram summarizes the main viewpoints and the differences between them. The traditional project camp promoted a strategy where the potential return on investment (ROI) for a project would be calculated, a decision would be made to finance the project based (partly) on that ROI, the project would run, the solution delivered into production, and then at some point in the future the actual ROI would be calculated. Everyone was a bit vague on how the actual ROI would be calculated, but they agreed that it could be done although would be driven by the context of the situation. Of course several people pointed out that it rarely works that way. Even if the potential ROI was initially calculated it would likely be based on wishful thinking and it would be incredibly unlikely that the actual ROI would be calculated once the solution was in production. This is because few organizations are actually interested in investing the time to do so and some would even be afraid to do so. Hence the planned and actual versions of the traditional strategy in the diagram.
The agile/lean camp had a very different vision. Instead of investing in upfront ROI calculation, which would have required a fair bit of upfront requirements modelling and architectural modelling to get the information, the idea was that we should instead focus on a single feature or small change. If this change made sense to the stakeholders then it would be implemented, typically on the order of days or weeks instead of months, and put quickly into production. If your application is properly instrumented, which is becoming more and more common given the growing adoption of DevOps strategies, you can easily determine whether the addition of the new feature/change adds real value.
Cultural differences get in your way
The traditional project camp certainly believed in their process. In theory it sounded good, and I’m sure you could make it work, but in practice it was very fragile. The long feedback cycle, potentially months if not years, pretty much doomed the traditional approach to measuring benefits of software development to failure. The initial ROI guesstimate was often a work of fiction and rarely would it be compared to actuals. The cultural belief in bureaucracy motivated the traditional project camp to ignore the obvious challenges with their chosen approach.
The agile/lean camp also believed in their strategy. In theory it works very well, and more and more organizations are clearly pulling this off in practice, but it does require great discipline and investment in your environment. In particular, you need investment in modern development practices such as continuous integration (CI), continuous deployment (CD), and instrumented solutions (all important aspects of a disciplined agile DevOps strategy). These are very good things to do anyway, it just so happens that they have an interesting side effect of making it easy (and inexpensive) to measure the actual benefits of changes to your software-based solutions. The cultural belief in short feedback cycles, in taking a series of smaller steps instead of one large one, and in their ability to automate some potentially complex processes motivated the agile/lean camp to see the traditional camp as hopeless and part of the problem.
Several people in the traditional project camp struggled to understand the agile/lean approach, which is certainly understandable given how different that vision is compared with traditional software development environments. Sadly a few of the traditionalists chose to malign the agile/lean strategy instead of respectfully considering it. They missed an excellent opportunity to learn and potentially improve their game. Similarly the agilists started to tune out, dropping out of the conversation and forgoing the opportunity to help others see their point of view. In short, each camp suffered from cultural challenges that prevented them from coherently discussing how to measure the benefits of software development efforts.
How Should You Measure the Effectiveness of Software Development?
Your measurement strategy should meet the following criteria:
Not surprisingly, I put a lot more faith in the agile/lean approach to measuring value. Having said that, I do respect the traditional strategy as there are some situations where it may in fact work. Just not as many as traditional protagonists may believe.
ScottAmbler 120000HESD Tags:  velocity governance acceleration agileexec agile metrics 2 Comments 10,927 Views
I've been getting a lot of questions lately about applying the acceleration metric in practice. So, here's some answers to frequently asked questions:
1. How do I monetize acceleration? This is fairly straightforward to do. For example, assume your acceleration is 0.007 (0.7%), there are five people on the team, your annual burdened cost per person is $150,000, and you have two week iterations. All these numbers are made up, but you know how to calculate acceleration now and IT management had darn well better know the average burdened cost (salary plus overhead) of their staff. So, per iteration the average burdened cost per person must be $150,000/26 = $5,770. Productivity improvement per iteration for this team must be $5,770 * 5 * .007 = $202. If the acceleration stayed constant at 0.7% the overall productivity improvement for the year would be (1.007)^26 (assuming the team works all 52 weeks of the year) which would be 1.198 or 19.8%. This would be a savings of $148,500 (pretty much the equivalent of one new person). Of course a 20% productivity increase over an entire year is a really aggressive improvement, regardless of some of the claims made by the agile snake oil salesman out there, although at 10-15% increase is a reasonable expectation. What I'd really want to do is calculate the acceleration for the year by comparing the velocity from the beginning of the year to the end of the year (in Western cultures I'd want to avoid comparing iterations near to the holidays). So, if the team velocity the first week of February 2008 was 20 points, now the same team's velocity the first week of February 2009 was 23 points, that's an acceleration of (23-20)/20 = 15% over a one year period, for a savings of $112,500.
2. Is acceleration really unitless? For the sake of comparison it is. The "units" are % change in points per iteration, or % change in points per time period depending on the way that you want to look at it. Because it's a percentage I can easily monetize it, as you see above, and use it as a basis of comparison.
3. How do I convince teams to share their data? This can be difficult. Because acceleration is easy to calculate for agile teams, and because it's easy to use to compare teams (my team has .7% acceleration whereas other teams down the hall from mine have accelerations of .3% and -.2% of teams), people are concerned that this metric will be used against them. OK, to be fair, my team might be OK with this. ;-) Seriously though, this is a valid fear that will only be addressed by an effective governance program based on enablement, collaboration, and trust instead of the traditional command-and-control approach. Management's track record regarding how they've used measurements in the past, and how they've governed in general, have a great effect on people's willingness to trust them with new metrics such as acceleration. The implication is that you need to build up trust, something that could take years if it's possible at all.
4. Why does this work for agile teams? Agile teams are self organizing, and an implication of that is that they will be held accountable for their estimates. Because of this accountability, and because velocity is a vital input into their planning and estimation efforts, agile teams are motivated to calculate their velocity accurately and to track it over time. Because they're eager to get their velocity right, and because acceleration is based on velocity, there's an exceptionally good chance that it's accurate.
5. What about function points or similar productivity measures? Function points can be calculated for projects being developed via an agile approach, or other approaches for that matter, but it's a very expensive endeavor compared to calculating acceleration (which is essentially free) and likely will be seen as a bureaucratic overhead by the development team. My rule of thumb is that if you're not being explicitly paid to count function points (for example the US DoD will often pay contracting companies to create estimates based on function point counts) then I wouldn't bother with them.
6. What about calculating acceleration for iterative project teams? Iterative project teams, perhaps following Rational Unified Process (RUP), can choose to calculate and track their velocity and thereby their acceleration. The key is to allow the team to be self organizing and accountable for their estimates, which in turn motivates them to get their velocity right just like agile teams (RUP can be as agile as you want to make it, don't let anyone tell you differently).
7. What about calculating acceleration for traditional project teams? In theory this should work, in practice it is incredibly unlikely. Traditional teams don't work in iterations where working software is produced on a regular basis, they're typically not self organizing, and therefore there really isn't any motivate to calculate velocity (even if they do, there is little motivation to get it right). Without knowing the velocity you can't calculate acceleration. If you can't trust the velocity estimate, and I certainly wouldn't trust a traditional team's velocity estimate, then you can't trust your acceleration calculation. So, my fall back position to calculate productivity improvement would be to do something like function point counting (which is expensive and difficult to compare between teams due to different fudge factors used by different FP counters) and then looking at change in FPs delivered over time.
8. How can I apply this across a department? It is fairly straightforward to roll up the acceleration of project teams into an overall acceleration measure for a portfolio of teams simply by taking a weighted average based on team size. However, this is only applicable to teams that are in a position to report an accurate acceleration (the agile and iterative teams) and of course are willing to do so.
9. What does a negative acceleration tell me? If the acceleration is negative then productivity on the team is going down, likely an indicator of quality and/or team work problems. However, you don't want to manage by the numbers so you should talk to the team to see what's actually going on.
10. What does a zero acceleration tell me? This is an indication that the team's productivity is not increasing, and that perhaps they should consider doing retrospectives at the end of each iteration and then acting on the results from those retrospectives. Better yet they can "dial up" their process improvement efforts by adopting something along the lines of IBM Rational Self Check.
Recently I visited a customer who had adopted Scrum. They were a few sprints, what Scrum calls iterations, into the project and were running into some difficulties. Although I was primarily brought in to educate senior management on disciplined agile software development, I was also asked to sit in on the team’s daily stand-up meeting so that I could hopefully provide some suggestions as to how to address the problems they were running into.
Their work area was fairly typical. They had some whiteboards which they were using for project planning and tracking, with sticky notes to indicate what work had been taken on by each team member. The current status of the task (not yet started, in progress, and completed) was indicated by putting each sticky note in a corresponding column for the status and corresponding column for the team member. This allowed everyone on the team to easily share their status and to see the status of everyone else. On the sides were sketches of the architecture as well as some business oriented models. In addition to Scrum the team had adopted several practices from Agile Modeling, in this case they had done some initial requirements envisioning and architecture envisioning, as well as practices from Extreme Programming (XP) for construction. In short, they had followed a fairly common strategy of combining practices from various agile methods.
This would have worked perfectly fine if they had tailored the practices to reflect the situation that they were in, but instead they adopted them "straight out of the book". First, the team was distributed, with most of the team in the location that I was visiting but some people located in two other distant cities. Therein was the source of most of their problems. The people at the other two locations weren’t getting much value out of the daily stand-up meetings, even though they would dial in, because they couldn’t see the project status information. Although people at this location were trying their best to represent these distant people in the daily stand-ups it wasn’t working well – their status information wasn’t being kept up to date and for some people it was a bit of mystery as to what they were actually working on at all.
This team also had 30 people in it, which isn’t a big deal although it can stretch the limits of the simple modeling and planning tools (in this case paper and whiteboards) that they were using. Because the team was larger they were investing a fair bit of time creating burn down charts at both the iteration/sprint and project levels. One of the unfortunate implications of using manual tools for project management is that any associated metric/status reporting in turn becomes manual as well. Considering how the agile community is so concerned with working efficiently, I find it comical that we have a tendency to overlook our own potentially unnecessary bureaucracy such as this.
The problem was that the team was applying strategies, in this case using sticky notes and whiteboards to capture the detailed iteration plan, applying similar strategies to capture key models, and were verbally relaying of status information between sub-teams. There are perfectly fine strategies for smaller co-located teams, but not so good for large or distributed teams. The solution was to recognize that they were in an Agility@Scale situation and needed to tailor their approach to reflect this fact. In this case they needed to forgo some of the manual tools and instead use electronic tooling such as Rational Team Concert (RTC) to share information across disparate locations, in particular the work assignment and corresponding status information. RTC also creates common agile reports such as burn-down charts based on the activities of the developers, providing accurate (nearly) real-time information while removing the burden of status reporting. The RTC project dashboard does more than just this, to see an actual example of one visit www.jazz.net to see the dashboard for the RTC development team itself. You can also see their actual work item list too, a more advanced version of Scrum’s product and sprint backlogs.[Read More]