Modified on by LeslieEkas
Successful agile teams require timely leadership to help the team work together, make decisions and progress. A team leader may have a job associated with leadership like a scrum master, or a team leader may emerge when the opportunity presents itself. Making leadership work on an agile team requires that you learn to lead and to follow. Early in my career as a manager, I partnered with a leader from another team to design and build a new product. I was full of energy and excitement and I wanted my team to accomplish great things. However I was aggressive, a lot of the time. I was quick to pass out assignments, check on progress, and be impatient. My new partner had a very different personality and I noticed that she had a particular trait that I lacked. She was very good at working with teams in real time to solve a problem. I told myself to stop and pay attention. How does she do it?
She came to each discussion prepared. She did her homework in advance so that she had knowledge of the topic and often an opinion. At the beginning of the meeting she set the tone to one of knowledge sharing, respectful discussions, and decision making. She started by reviewing the problem at hand and made sure that everyone in the meeting was on the same page. And then the real difference came, when others offered their thoughts, she listened. I mean she really listened and paid attention to what they were saying. She would read back the thoughts to make sure that she understood and let the team know that she understood. She did not allow herself to get distracted. Her focus on a topic helped to keep the meeting on course. Her natural ability to hear everyone’s input and respond to it let them know their input was valuable. Finally, she was always calm. This was the deal breaker.
After watching her run very successful discussions, I paid attention to my own behavior. I worked harder to make sure that I came prepared. But when I disagreed with an opinion my heart beat would increase, and my impulse was to jump in fast and offer my opinion. That kind of rapid response can seem like an interruption and result in sparring. Sometimes sparring leads to successful results but it often discourages others from participating. Problem solving usually requires thoughtful debate and compromise. Pushing ideas back and forth allows teams to think together. But it is important to keep the tone to one of debate not sparring; otherwise good thinkers may shut down and not offer their input. What I learned to do was to fight the impulse to react and instead stay grounded and stay calm. Now when I participate in a problem solving discussion and that impulse to jump in strikes, I try to take a deep breath and wait to speak. I speak only after my pulse drops. This behavior has saved me many times because waiting allowed me to appreciate that my thoughts were not always well considered. Listening to others and leveraging their input enabled me to work out a more constructive comment.
I learned more from my old partner and many other leaders then they will ever know. Now, as a more mature leader, I have a set of personas, each of which is good at some aspect of leadership. Now when I get into trouble, I think, “What would she have done in this situation?” And I try her approach. My point is that some days you have to lead and some days you should follow and learn. As a leader, this is how you can foster the agile practice of continuous improvement.
Agile offers so many benefits but one of the most irresistible is the promise of higher productivity. Once you become more productive, how do you know that you are in fact, more productive? Most agile enthusiasts agree that highly performing agile teams move faster than traditional technology teams. There are many aspects to agile that provide improved performance including the practice of maintaining working software, queuing theory, eliminating waste and multi-tasking, whole team practices, and more. But given all these changes, how do you verify that it really works? I have been asked to “prove” that a team is more productive and our teams found a way.
During the intake process, each team estimates the size of the incoming request. I will call the request an “intake item” to avoid confusing the meaning of a story or an epic. Intake items can range dramatically from something that takes a team less than a sprint to something that takes a team many, many sprints. Our teams call the estimates, “SWAGs” to reinforce the idea that the estimate is an educated guess but still a guess.
I have seen teams that SWAG by dollar cost to do the work and teams that SWAG by approximate length of time to complete the work. Both methods seem to work but the important point is that the SWAG ranges are large enough to delineate typical work and reduce the error in estimation. So for instance one team could delineate SWAGs something like the following.
Small: less than $100,000
Medium: $100,000 - $500,000
Large: $500,000 - $1,000,000
XLarge: greater than $1,000,000
Similar rules that apply to user story writing also apply to making SWAG. Representatives of the team that will do the work estimates the SWAGs, the sizing is relative to other SWAG sizes, and once the SWAG is in place, they team does not change it. After the intake item is complete and rolled out into production, the item is marked as complete. The following shows a team that has used this mechanism for over a year.
The graph shows how many items the team completed each quarter standardized on time. It is quickly apparent that the team accomplished more each quarter. In other words, if the team size remains the same, then their productivity increased over time. It also shows that this team got better at doing really large items of work.
The next graph is another view of the same information but standardized on the number of items. That is, all items are the same size regardless of their SWAG size. This demonstrates that the majority of items completed are small.
The metrics show the results for one software product regardless of the size of the product or the size of the team building the product. We have tried this same approach with products developed by software teams that consist of one sprint team with less than 10 people. And we have tried the same approach with a larger team of over 150 people broken into many sprint teams. In all cases, we get consistent and believable results.
The value of this mechanism is that we show team productivity over time. Lines could be added to the chart to identify individual intake items. To add even more clarity we can associate real product deliverables to each of the items in the chart. This has proved to be a very simple way to validate that our migration to agile is having a positive impact. We typically combine this view with quality metrics to ensure that we maintain high quality as we increase output.
Here is an update to my Part 1 blog posting on whether or not teams are really DONE when they release software. Just to recap, I worry that agile teams do not have a reliable mechanism to ensure that new features or capabilities released into production succeed as planned. Without a verification tool in place, teams may not be able to confirm success. And worse, once teams get focused on new work they may not track what was released, “out of sight, out of mind”. Of course most teams respond to issues that get reported, but if nothing is reported, does that mean success or not?
A team experimenting with this decided to add a verification safeguard to their DONE criteria. Each story has to have a “plan to monitor feature success” in production. For this particular team, monitoring typically requires that the software logs success and failure data and the team has a way to track what is logged over time. Their DONE criteria ensures that they add logging abilities when they design the feature and they test that the logged data delivers the information required. When the new feature is in production, the team uses a monitoring tool to report on usage and failures. Once an average logging pattern is obtained, they add alerts to notify if there are problems.
Every team may not have this type of logging and monitoring capability in place but adding this DONE criteria can serve as a driver to make that happen. It took the team mentioned multiple attempts to get the right tools in place but the effort was very beneficial. They have already used the new methodology to find an issue (and fix it) before their users did. And by looking at success trends, they have been able to verify that uptake of their features were as planned.
If your team does not have a strategy to validate success of new features or capabilities, I recommend that you add this initiative to your backlog. You may have to start from the beginning – get the right design strategy in your code and then add the tools to monitor. Use this new DONE criteria as a mechanism to get started. A story is DONE when there is a defined plan for monitoring the solution in production. Check!
One of the reasons that I found agile compelling when I first heard about it was the notion that you are “DONE” with the feature when your customers were successfully using it in production and were pleased with the capability. I have coached teams to establish success criteria for user stories but have not required that it include validation of success in production. That feels like an oversight now. I am discovering scenarios where the desired feature does not deliver the success promised and there is no automatic mechanism to address the shortfall.
Now that I work in eCommerce, the business pays keen attention to data that validates that the software is successful. Even with this attention our technology teams often lose the connection between getting capabilities into production and verifying the value they do or do not produce.
I now recommend that teams take a new look at success criteria and include a measure of post-production success. Maybe teams add a “post release validation” criteria to their DONE list. The first challenge is for teams to identify useful data that enables them to track and validate success. The second challenge is to figure out when to assess the data and how to respond to it.
Solving the first problem requires that the software or customer feedback mechanism provide a way to measure success. The process to collect data is usually hardwired into eCommerce platforms so measurement should not be hard. The software could track how often the capability is used or how well the capability works by tracking errors as a percentage of success.
Success may be harder to track when there are no metrics accessible by the team. In these scenarios teams can measure speed at uptake of a new release, leverage customer surveys, or perform post-release customer feedback sessions. None of these options provide the validation that data offers but they would prove the team with a tool to ensure post release success.
It is important to re-establish our focus on post release success validation. I recommend that each story include not only success criteria for release but also for post-release.
Modified on by ScottWill
In the last post I did a quick overview of the purpose and benefits of the “daily standup” meeting. As for conducting the meeting itself, I like the idea of using "The 3 Questions” to guide the meeting:
What did you do yesterday?
What are you planning to do today?
Do you have any blocking issues?
Each team member provides answers to the three questions – keep in mind that the answers should focus on information important to other team members. Telling the team that you’ve completed a development task, and that the code is ready for testing, is something important to the team. On the other hand, telling the team that you had your weekly 1-on-1 meeting with your manager yesterday really isn’t that important. What I want to focus on here, though, is the third question...
What is your experience when a team member raises a blocking issue during the daily team meeting? Do team members immediately offer to help with getting rid of it? (It is a blocking issue after all…) Or you do hear the sounds of crickets chirping? If the latter, then permit me to make a recommendation: I would encourage you to offer to help, especially if it’s an area you know: “Hey Scott, I hit a similar problem Tuesday – I can help you with that.” Otherwise, if it’s an area outside your area of expertise, you can still offer to help: “Hey Scott, I don’t know if I can provide immediate relief for your blocking issue or not, but I’ll catch up with you right after this meeting and see if there’s anything I can do to help.” Consider it an opportunity to learn as well as an opportunity to help.
This is how an agile “whole team” should operate – blocking issues shouldn’t fester, and team members should be willing to help others on the team when needed.
While the sounds of silence may be wonderful in some instances (i.e., a peaceful walk in the woods), the sounds of silence when blocking issues are raised should be deafening. Be willing to help a team member out when needed and, by doing so, you’ll not only be setting a good example, you’ll be helping the team continue to make progress on your project.
Modified on by ScottWill
This week I thought I'd re-post an article that appeared earlier on DeveloperWorks.
Early on, when I first started coaching teams on their transition to Agile, it was quite common for teams to come to me and tell me that they hadn't completed any User Stories by the end of an iteration. Initially, teams wanted to use this as a reason to increase the length of their iterations (I recommend two-week iterations – and teams always seem to want longer iterations). What they were failing to realize is that there were fundamental reasons why they weren't completing stories, and iteration length by and large had nothing to do with it. Let me explain....
One of the first questions I'd ask a team in this situation was if they were assigning User Stories to team members with the idea that each member was responsible for completing his or her User Story independently of others on the team. Almost invariably, the answer was “Yes, but how did you know that...?” What was happening in these situations was that each member of the team would work on his own User Story and, at the end of an iteration, the team would have six, or seven, or eight partially-completed User Stories. In this case, nothing was completely “Done!” by the end of the iteration – just a bunch of partially-completed stories. Since each team member was focused on completing his own story, there was no “incentive” for someone to jump in and help another team member get a story done because everyone was focused on completing his own story.
In this situation, we would remind the team about the importance of the Agile practice of “whole teams.” Part of this practice recommends that a team should try to work together on one User Story at time, complete it, and then as a team move on to the next story on the backlog. This way, the team is constantly completing User Stories and will have, at most, one unfinished User Story at the end of an iteration.
In order to pull this off, there's another practice that we recommend teams adopt – and that is the creation of small implementation tasks for each User Story. At the beginning of an iteration, the whole team goes through the process of creating the various tasks needed to complete a story (development tasks, test tasks, user documentation tasks, automation tasks, code review tasks, etc.). These task sizes should be small in size (on the order of 4 hours, 8 hours, to no more than 16 hours), which then allows for a lot of “parallelization” of the work. The concept is, for example, instead of having one developer work on a coding task for five days, you could put five developers working in parallel on five one-day development tasks and, at the end of a single day, have all the coding completed that otherwise wouldn't have been complete until the end of five days. Additionally, there should be corresponding documentation, test, automation, and code review tasks for each of the development tasks. This way, a team achieves a very tight integration between dev, doc, and QA throughout each User Story (not to mention each iteration), and the team also always has working code as the team completes one User Story before moving on to the next. By the way, this approach is not something that comes naturally to a team (especially if they're just beginning the transition to Agile), but give the team time and encouragement to try it out – the effort is worth it.
A few closing comments: obviously, piling everyone on a scrum team onto one story won't always work, especially with very small User Stories. The goal – even with a very small User Story – should be to put two or three engineers on that story while the rest of the team works on an additional story. Keep the number of stories being worked on at the same time by the team to the smallest number possible. This should go a long way to helping you consistently finish User Stories at the end of every iteration.
We welcome any comments and suggestions you may have -- thanks!
Modified on by LeslieEkas
Teams sometimes struggle to write down the first story in user stories sessions, even if it is not the first time the team has written stories together. Brainstorming often works to get the team headed in the right direction. Some of the following questions might help:
Describe the problem you are trying to solve?
What benefit will solving the problem provide the business?
What are the consequences if you do not solve the problem?
What are the critical edge cases to consider? (establish limits)
What capabilities of the solution need to be considered? E.g. security, performance, error recovery, etc?
What is the minimal problem set to solve? What is the best way to validate that a solution will solve the problem quickly? Think minimal viable product.
I have run many brainstorming sessions before we start to write stories. In the process I have come up a few rules to help the process be successful.
Rule 1: Brainstorm. What I mean by this is to allow the session to be a “storm”. Just write down everything you think of without filtering the relevance. By working this way you may discover what does and what does NOT matter. It will help you discover the limits of the stories that you need to write. It will allow you the opportunity to think “out of the box”.
Rule 2: Brainstorm with your whole team and your stakeholders. Writing stories without your stakeholders is doable but I have seen far better results with your stakeholders helping with the process. In fact I was in a brainstorming/user writing session with a stakeholder. The team started by writing the stories assuming they knew what was required. When I asked the stakeholder what problem he was trying to solve, we discovered through the following conversation, that the software already provided a solution. Frankly, it was the best user story session I have ever attended!
Rule 3: Take notes. I know we said this in our book and we may have said it in our blog but it is worth repeating. Take notes while you write stories and take notes during the brainstorming session. In fact it does not hurt to have someone take notes verbatim. How many times does someone come up with the perfect phrase but cannot repeat what they just said!?
Rule 4: Avoid getting into the “how” you are going to do it. Avoiding the “how” in user stories may sound like a broken record, so I probably do not need to elaborate further. Sometimes however it may be necessary – but proceed with caution.
Rule 5: Limit your time. Brainstorming can be very useful but don't overdo it. I suggest 30-90 minutes, 2 hours tops if the scope is large. Once you have an idea of what your minimal viable product or in this case, solution is, start by writing a story that takes the first step to achieve that.
Try brainstorming if you are off to a slow start writing stories or are just plain stuck. If it works, use it. If it does not work, skip it.
Extra Credit: Make your first few stories vertical stories. Vertical stories are harder to write because they force teams to think across the architecture and let go of their concern that the story is not shippable. But vertical stories provide so much value that it is worth the effort to try to think vertical.
Modified on by ScottWill
Years ago, waterfall projects would typically shun requests for new features or capabilities being added to a project that was underway. After all, project success was typically measured by conformance to “the plan” – and a new request was not part of the plan. These waterfall teams would complete the opening sentence something like this, “When we get a new feature request, we put it on our list of features for consideration in the next release.” Thus, an opportunity to respond to changing conditions, changing customer needs and expectations, or changing competitive situations in a timely manner was lost.
Other waterfall projects have tried to add the new feature in along with the work that was originally committed in “the plan,” but that would often spell disaster since teams were typically already working feverishly just to meet the original commitments. In order to add something else to an already booked plan, there were very few options – mainly overtime and/or cutting corners – neither of which is a good thing. Oh, sure, there was always a planned “buffer” added into “the plan” to account for such contingencies, but when have you ever seen it work out the way it was intended? The skeptic in me would guess rarely, if ever… These teams would complete the opening sentence something like this, “When we get a new feature request, we add it to the plan and start mandating extensive overtime.” Pretty soon, employees are burnt out, frustrated at not having a life, and begin to actively seek employment opportunities elsewhere.
Mature agile teams complete the sentence something like this: “When we get a new feature request, we see it as an opportunity to get ahead of the competition as well as make our customers happy and successful.” Typically new requests surface because of changes in the competitive landscape, changing customer needs and expectations, new market opportunities, or even some combination of these and other factors. And when these new requests arrive at the door of an agile team, there’s no drama at all, no worries about overtime, no cutting corners, no consternation about not meeting “the plan,” etc. Agile teams have great flexibility to handle new requests because they are always working on just one thing at a time – not numerous features in parallel. Waterfall teams typically worked on lots of features in parallel since all the features were committed up-front and since teams typically had to show progress on all the committed features from the very beginning of the project. Thus, if a new request arrived, there was no flexibility to drop a less important feature from the plan since everything was already underway.
Agile teams, however, work on one thing at a time. And the way they do this is by having the features rank-ordered from the most important to the least important. If a new request arrives, the team finishes working on the feature currently in progress – it then has complete freedom to begin working on the brand new request. If a particular ship-date has to be met, then the team drops the least important feature from the list and replaces it with the new request. This way, the team is always working on the most important feature and has incredible flexibility to handle changing circumstances. After all, conformance to “the plan” is not the right measure of success – meeting customer needs and adapting to changing market conditions is a much better measure of success.
To summarize, working on one thing at a time (always the highest-ranked, most important item) and getting it done before starting on something new is the most efficient and effective way to work. It also allows for the greatest flexibility – especially in markets where changes can occur lightning fast.
One thing at a time, one thing at a time, one thing at a time...
Modified on by ScottWill
No doubt you’ve already heard about DevOps. What you may not be aware of is how DevOps builds on Agile principles and practices. For example, Software-as-a-Service (SaaS) projects have adopted DevOps in order to have the ability to frequently update their websites with additional features and capabilities. Some SaaS offerings are updating their production websites multiple times a day – which is a far cry from the once-a-year-release cycle that was rather typical for products built using waterfall.
You might be thinking to yourself, “Multiple times a day…? How does that happen…?” I’ll touch briefly on three essentials of Agile that contribute to this capability. The first is breaking work down into small batches and completing one small batch of work prior to moving to another. You’ll no doubt recognize this as a Lean principle derived from queuing theory. Simply stated, Lean has shown that small batches of work transitioning through a system are far more efficient than an occasional big batch of work. For our purposes, this means that having small amounts of code written, tested, and automated, where any defects have been fixed, and where any necessary user-documentation has been written, is far more efficient and productive than just having a large batch of code written that hasn’t been tested or documented.
The second point is Agile’s emphasis on “working software as the primary measure of progress” (see the 7th Principle of The Agile Manifesto). This ties in directly with the previous point – as small amounts of code are written, the goal is to get that code to production-level status as quickly as possible (“working software” that is “Done!”) so that the new code can be provided to customers with high confidence that it will work as desired, have the right level of quality, and help customers address a particular need.
The last point regards the tremendous emphasis in Agile on automation. With DevOps, the need for automation increases significantly because of the desire to deploy new features and capabilities on such a short timetable. Not only are builds and testing automated, but test environments are automatically provisioned, code that passes the automated test suite is automatically deployed into production and, if a problem occurs anywhere along the way, the process is stopped, the code is automatically rolled back, and appropriate personnel are automatically notified of the problem. The ultimate goal is to make a small code change, “push a button,” and have the new feature or capability automatically rolled out without any further human intervention.
No doubt you can tie additional Agile principles and practices to the DevOps initiative, but I thought I’d touch on just these few to show how DevOps is nothing more than a logical next step after Agile – they are not two, independent approaches to building software. As always, please feel free to share your thoughts! We look forward to hearing from you!
Modified on by ScottWill
Just like the drip, drip, drip of a leaky faucet, we lose productive time by being regularly distracted. Some distractions can't be eliminated, but many can... I recently wrote an article for InformIT that was adapted from one of the chapters in the book that Leslie and I co-authored entitled Being Agile. The article discusses a pervasive form of regular distractions that many people have taken for granted nowadays. I thought I'd pass along a link here:
I hope you enjoy the article and that it provides some food for thought... As always, comments and questions are welcome. Thanks!