Pawel Brodzinski on Leadership in Technology

Whatever it takes to lead a team, build a product, and run a business

Tag: project management

  • Definition of Done

    Shim Marom’s post on (low) value of industry reports launched an interesting discussion in comment section, which I took part in by the way. The point we reached was how we define whether the project is completed or not.

    And here we come to the definition of done, term which I learned from Glen Alleman.

    On Time, On Budget, On Scope

    A definition which you will hear most often is project delivery on time, on budget and on scope. And there comes a problem. If we overrun a budget for ten bucks are we still on budget or not? What about thousand? Or hundred thousand? Depends on project, right? So what about 0,1% budget overrun? 1%? 5%? Where is the border between success and failure?

    Note: I haven’t even started with time or scope.

    While this definition sounds nice it hardly responds to typical complex project environments.

    The Story of Changing Goal

    I love the Apollo 13 story. Not only because it is a great story about heroes, but also because it is a great story to learn about project management. If I asked you what was the original goal of Apollo 13 mission probably no one would answer correctly. But well, they definitely hit the space for something more to become a base for a Hollywood movie or to coin one of the famous quotes (one of famous misquotations actually). The thing we remember is that Apollo 13 mission’s goal became saving astronauts’ lives. And we all consider it a huge success.

    Were original goals accomplished? No. Probably neither of them. The money was spent however. Probably more than planned because of unexpected problems. But over the course the goal has changed.

    Recently I’ve read similar story about Sir Ernest Shackleton’s Antarctic adventure. It is 18-month long story about fighting for people’s lives. And again initial goal, which was crossing Antarctic continent, was rendered invalid just after several days and the main problem became coming back home in one piece. Thanks to his commitment and determination Shackleton was successful in rescuing every single man from his expedition. Considering conditions a stunning success.

    Was Shackleton able to pass the Antarctic? No. Failure then?

    Maybe You Tell Us About Real Projects…

    You may say that those stories aren’t about typical IT projects which we deal with everyday. Yes, these are extreme examples but the same pattern we see very frequently, but in a bit different scale. Hey, that’s what embracing change is all about. We try to adjust the course of our projects to make them better respond to clients’ needs.

    After all I don’t believe all projects you took part in were specified perfectly at the beginning and carried through relentlessly to the end according to unchanged plan. My wild guess is only few of you had a chance to work on at least one project which looked a bit like that (and yes, Glen is probably among those few).

    Clients often deliver some wishful thinking as requirements, and then vendors go through them only roughly and come up with a generic document which describes fuzzily what should be done. No surprise the real goal appears to be changing over time as everybody realizes all the assumptions and gaps in initial plan.

    Definition of Done Is Changing

    OK, so goals are changing over time. So is definition of done. We usually do a crappy job defining done. But then we’re even worse in adjusting the definition along the way. We change expected costs and schedule. We change scope. Do we change our definition of done as well?

    I mean unconsciously we do, that’s for sure. After all we’re able to follow our gut feeling and tell this project was a success and that was a failure. We know that major schedule slip will be quickly forgotten if delivered software exceeds expectations. We know that being on time on budget and on scope isn’t a reason to boast when the client doesn’t use the system at all for some reasons.

    So yes, we should know what done means in each and every project. And no, we won’t have a single, universal definition which we can use against all our ventures. It is a very individual thing.

    That’s by the way the reason why the industry reports on state of projects will be criticized over and over again. There just aren’t universal measures which would be widely acclaimed.

    http://main.wgbh.org/imax/shackleton/about-one.html

  • Kanban Basics

    I often say that you can implement Kanban in your team in a single afternoon. That’s how we did that after all. So when Andy Brandt asked me to do Kanban Basics webinar I expected that preparing it would be pretty simple. How long can you talk about few-hour-long task?

    Well, it wasn’t as simple as I expected.

    Kanban itself is very simple. But telling people they should visualize workflow, limit work in progress and measure the flow isn’t really all the basic stuff they need to know. After a while it always ends up with questions how we do this and how we do that.

    What limits should be set on board?
    What happens when a bug is found during testing?
    Should sticky notes be moved back on the board at all?
    How cycle time is measured?
    What happens when the limit is reached?
    What to do when emergency task pops up?
    How to cope with multiple projects?
    Is feature-by-feature deployment mandatory?
    How estimation is done?

    That’s an interesting observation – I often deal with most of these questions at the end of my Kanban presentations, no matter if I cover basic or advanced material. After giving it some thought I decided this would be a good starting point to prepare Kanban Basics presentation.

    What I ended up is presentation below. It covers a bunch of scenarios visualized with (surprise, surprise) Kanban board. Additionally I used Scrum as the reference to make a basic Kanban description easier to understand.

    Kanban Basics

    If you have some basic questions which seem to be omitted in the presentation, please leave a comment. I’d be happy to both answer the questions and update future versions of the presentation.

    If you speak Polish feel free to watch the recording of the webinar.

    Also, check The Kanban Story series as it reveals all the details of Kanban implementation in my current team.

  • How to maintain backlog?

    In one of recent postings I asked you how big your backlog is. My argument was that trying to enforce small backlog size is counterproductive. Although small backlog is easier to manage throwing things away from it just to keep it small isn’t the best idea.

    However that doesn’t mean you shouldn’t do some backlog maintenance from time to time. What more, applying a few simple rules can help you to manage backlog easily despite its pretty big size.

    Keep epics, split late

    Sometimes we add to our product a big story. An epic. It is actually pretty interesting example in terms of sizing backlog. Why? Well, no matter if you split the epic into a list of smaller stories, i.e. sized similarly to your typical features, or keep it big you add a huge piece of work. A piece, which usually makes sense as long as it is completed as a whole. So yes, you need quite a capacity to add the feature, no matter which approach you choose. What do you do if your backlog is limited?

    Anyway, my advice is to keep epics in backlog as long as possible and split them in the last responsible moment. It is aligned with agile late design approach but that’s not why I advise you so. Actually as long as you don’t start working on the epic there’s no reason to keep a dozen of sticky notes on the board instead of a single one. It’s enough for you to look at epic to know roughly what is to be done. You will need more details when you start development of first epic-related feature so no need to worry at the moment.

    It is easier to reprioritize the epic over and over again if it’s in one piece. And reprioritizing is the most common task when it comes to managing backlog.

    Groom from time to time

    If you have spacious backlog you will face this situation on occasions: you will find out that one or more features waiting in the backlog are no longer relevant. Maybe you’ve changed the goal of your app or you abandoned industry which was addressed with the feature or you just don’t have a faintest idea why you wanted to build the damn thing in the first place. Either way it’s time to forget about it.

    Grooming backlog is a great occasion to do that. What exactly grooming is? A simple process of reviewing all features in backlog to verify their relevancy. Yes, if your backlog is big it takes time. But after all this is the way to make it at least a bit smaller, thus more manageable. And you don’t do it every week as you don’t change general plans for your product that often.

    Group features

    There’s an observation which can be helpful as well. Unless we work on maintenance project where priorities are usually set by the client we tend to build groups of similar features and not randomly choose one from here and another from there. Grouping features which are similar or features which touch the same parts of code can be helpful in terms of prioritizing work. Once done you can just throw in another feature from the group instead of scanning through the whole backlog to look for a relevant task to put in todo queue. That is as long as your general priorities don’t change.

    Grouping features also helps in prioritizing whole backlog. Instead of considering each and every feature separately you decide on a group which means you use the same time to judge a dozen of tasks you’d use to judge a single task otherwise.

    Dealing with big backlog isn’t that hard after all. All you need is some order and a few rules which help you to organize a long list of tasks somehow.

  • When Kanban is the Best Choice

    Kanban, as any other methodology, isn’t a silver bullet. There are situations and teams when it shows its full potential but there are others where its impact will be limited. Where Kanban suits best then?

    Micro-sized teams

    It is said Scrum works best with teams of 7 or close to this size. Sometimes we deal with smaller groups. 3 people working on a project isn’t something very uncommon. For such micro-sized teams Scrum is often too formalized. You can limit a number of rules you follow and still keep good quality. And you have a bit more time to do the real work.

    Frequent priority changes

    “Walking on water and developing software from specifications are easy if both are frozen.” Unfortunately we deal with a lot of changes as we build software. There are new features; importance of tasks changes, new top priority bugs requires instant attention. Our response is moving to more flexible approaches. We try to avoid BDUF projects. We switch to agile methods employing short iterations. We even make iterations shorter and shorter. It allows us to change priorities frequently. Once every couple of weeks if we take typical Scrum implementation.

    The problem is when priorities happen to change even more frequently. Once every few days. Or even every single day. And yes, there are such projects. Kanban is a great answer for them. Feel free to change priorities every day. As long as it is well-grounded it shouldn’t ruin your project.

    Maintenance projects

    A typical maintenance project routine looks like this:

    1. Whenever high-priority bug is submitted fix it as soon as possible
    2. Low-priority bugs becomes high-priority ones when resolution deadline approaches; then see above
    3. Whenever a client orders change request (CR) and there’s no high-priority bugs – try to do it as soon as possible
    4. If there are more than single concurrent CR ask project manager about priorities
    5. If there are no bugs or CRs do some refactoring or other improvement job

    Sounds like ideal Kanban playground, doesn’t it? That’s typical case of event-driven development (not event-driven programming) where you don’t actually have a roadmap or something but you do whatever new day brings. After all you don’t expect to have a bug submitted tomorrow, or do you?

    Multiple small projects

    Working on several rather small projects or sub-projects with the same team at the same time is pretty difficult. Resources (what a nice name for your people) are usually insufficient since it is harder to synchronize stream of small orders to keep it at the same level all the time and bringing more people just-in-case isn’t the best business strategy around. This ends up with (surprise, surprise) a lot of priority changes and trade-off games. “We can complete this additional project on time but we’d fail to meet a deadline here or there.”

    With standard structured project management approaches coordinating different threads with ever-changing priorities becomes pretty much a hell. What Kanban does is it organizes workflow so the main, well almost the only, thing you should care about is setting priorities at the beginning of workflow.

    Common part

    The common part for all of environments above is they don’t require many constraints to work. Few simple rules which come with Kanban should be enough to get things done. Another common thing is mid- and long-term planning is hard or even close to impossible, which is another problem hardly resolvable with more structured approaches. These two things are the most specific for environments where Kanban shows its full potential.

    This isn’t really a post which is a part of the Kanban Story but if you found it interesting you should like the story as well.

  • Why We Don’t Write User Stories Anymore

    There was a time when we were writing user stories to describe requirements. I’d say they worked fairly well for us. But we don’t do this anymore.

    We were using user stories as a technique which allowed us to describe bigger chunks of functionality. There was one bigger sub-project or module and it had more than 10 user stories attached (usually closer to 20) and a handful of non-functional requirements. During development we were often going through several stories at once as technical design didn’t map directly to the stories. The stories were more of input to design session and a base for test cases than stand-alone bites of functionality.

    Then we switched to Kanban. One of consequences was we reduced the size of average feature which was going to development. It no longer had 15 stories attached, but it wasn’t a single-story task either. If we were still writing user stories to each Minimal Marketable Feature we would probably have few of them. My guess is 2 or 3 most of the time.

    At this level stories become pretty artificial. I mean if you think about 2 stories connected with one feature, i.e. administrator can configure this magic widget and user can use this magic widget to do, well, the magic, you can pretty much tell these stories intuitively in your head. Writing them down becomes overkill.

    Besides that I think the often cited role of user stories which make usage scenarios completely clear is overrated. If you can talk with developers in language closer to the code, and functionality description is much closer to the code than telling user story, you’ll be better understood. The standard problem here was that functionality description wasn’t precise and it often became disconnected with usage scenarios.

    The answer for this problem is: make features as small as possible (but only as small as they still does any difference). Small features are easy to define, easy to understand (even for a developer) and easy to chew. It is pretty hard to screw them.

    There’s one more reason why I don’t consider user stories as a must-have. If you happened to create software which will be used by other developers or administrators at best, like some magic box with a lot of APIs and command line interface as the only UI, you should know what I’m talking about. If you write stories for this kind of software you end up with a bunch of “as a developer I want to call the magic function which does the magic” stories. Doesn’t API specification make more sense?

    I don’t say user stories are bad. They aren’t. But they don’t add value all the time and in every situation. This is just another practice which should be used only as long as it does make sense in your specific situation.

  • Manual Testing Is a Must

    The other day we were discussing different techniques aimed at improving code quality. Continuous integration, static code analysis, unit testing with or without applying test-driven development, code review – we’ve went through them all. At some point I sensed someone could feel that once they employ all this fine practices their code will be ready to ship as soon as it is all green after build on a build server. I just had to counter strike:

    “I’m not going to ship any code, no matter how many quality-improving techniques we use, unless some human tester puts their hands on it and blesses it as good. Not even a chance.”

    I’ve seen the situation quite a number of times: a team of developers who are all into the best engineering practices, but unfortunately at the same time sharing a belief this is enough to build top-notch applications. I have a bad news for you: if the answer for a question about quality assurance team is “we don’t need one” I scream and run away. And don’t buy any of your apps.

    It just isn’t possible to build quality code with no manual testing at all. You may build something and throw it against your client hoping they will do the testing for you. Sometimes you can even get away with this approach. Be warned though – you’re going to fail hard way soon. The next customer may not like the idea of doing beta-tests for you, actually most of them won’t, and then you’re screwed.

    Manual and automatic testing is fundamentally different. With automated testing, no matter if we’re talking about unit, stress, regression, integration or end-to-end tests, you go through predefined tracks. You had to create the test in the first place so it does exactly what you told it to do.

    On the other hand humans pretty often had their own minds which they happen to use in unpredictable ways. They may for example make up some test scenarios on the fly or they may sense a subtle scent of a big scary bug hiding around and follow their instinct to hunt it down. Every now and then they will abandon beaten tracks to do something unexpected, i.e. find a bug which would be missed otherwise.

    Note: I don’t say what kind of procedure you should follow in manual testing. Personally I strongly believe in value of exploratory testing, but any good tester will do the job, no matter what your manual testing procedure look like.

    Actually this post was triggered by recent discussion between a few bloggers including Lisa Crispin, James Shore, Ron Jeffries, George Dinwiddie and Gojko Adzic. The discussion, while interesting and definitely worth to read, is a bit too academic for me. My approach is that there is no universal set of techniques which yields indisputably best results. While I like James arguments why they dropped acceptance testing and support his affection for exploratory testing I share Lisa point that even in stable environment our “best” approach will evolve and so would techniques we employ.

    You may exchange acceptance testing with exploratory testing and that’s perfectly fine. As long as some fellow human put their hand on the code you want your users to touch with mine that I’m good with that. I don’t care much which approach you choose or how you call it. It is way more important who does the job. Experienced quality engineer with no plan at all will do way better job than poor or inexperienced tester with the best plan.

    Just remember if you happen to skip the manual testing at all I’m afraid your app may be good only for machines as only machines tested it.

  • The Kanban Story: First Issues

    So we were doing great, everyone was happy and we were delivering on time on budget and on scope. Except it wasn’t exactly how things really looked like.

    First two projects were late. Not much but still. It was expected since these were our first estimates in the team and at that time we decided not to do anything about that yet. Slips were reasonably small, which was a good sign when we talk about our developers’ estimation skills. Nothing to be worried about.

    Another issue however appeared to be a real pain in the ass. One of applications got stuck somewhere in the middle of first iteration of tests. It looked like there was always something more important to do. Everyone was doing high-priority things and the application wasn’t touched even with a stick. There was no mechanism which would add an incentive to finish things and not leave even less-important tasks for later.

    We also had a problem with our Product Owner. The guy was trying to catch many parallel threads and organize team’s work but unfortunately he was pushing in a bit too many new things. At the same time he was losing some of nice ideas on the way. Before some of them could be implemented guy was coming back from another meeting with a client bringing new, better and higher-priority tasks and the old ones were fading into oblivion. For those of you who can’t wait to ask who this crappy Product Owner was the answer is: yes, it was me.

    A general conclusion was we need some more organization not at project level but at team level. Something which would help us finishing things and limit chaos generated by rapidly changing business environment. Specific of our team was we were doing a number of very small projects simultaneously so coordinating these projects was crucial to avoid falling into chaos.

    We were about to do first process improvements…

    Read the whole story.

  • The Kanban Story: Initial Methodology

    You already know how our team looked like and what concerns I had with implementing plain old Scrum. You also know we chose “take this from here and take that from there” kind of approach to running our projects. Our base method was Scrum but we were far, far away from accepting it the orthodox way.

    What we finally agreed on within the team can be described in several rules:

    1. Planning
    For each application at the beginning we were deciding what we want to see there in the next version. We were trying to limit a number of features but didn’t set any limits how long development should take. The longest cycle was something between three and four weeks.

    2. Requirements
    When we’d known what we wanted to do we were creating user stories and non-functional requirements. Each session took whole team, even when someone wasn’t going to develop that specific application. As it usually happens the scope was being changed as we discussed different aspects of planned work. We were adding (more often) or cutting off (less often) features. We were building a coarse-grained architecture as we discussed non-functional requirements. At the end of the day we had a whiteboard full of stories which were a starting point for development.

    3. Tasks
    Since user stories were rather big we were splitting them to smaller pieces – development tasks. This was changing view from feature-wise to code-wise. Development tasks were intended as small pieces of work (possibly not bigger than 16-hour long) which were a complete wholes from a developer’s point of view. Ideally a single user story should have several tasks connected to it and single development task should be connected with only one user story or non-functional requirement. It wasn’t a strict rule however and sometimes we had many-to-many relation since specific changes in architecture (single development task) were affecting many usage scenarios (many user stories). Development tasks should make as much sense as possible for developers so they were defined by developers themselves and by those who were going to do the job. Tasks were stored in a system which was used company-wide.

    4. Estimation
    At the very beginning we had no strict deadlines but we were estimating anyway. There were two goals: learn to estimate better when there aren’t huge consequences for being wrong and getting into a habit of estimating all of planned work. Our estimates were done against developer tasks, not user stories. The main reason why we went this way was that tasks were smaller so estimates naturally were better than they would be if we did them against user stories. A specific, pretty non-agile, thing we were doing with estimation was a rule of estimating each task by a developer who would be doing it. More on this in one of future posts.

    5. Measuring progress and work done
    Current progress could be verified by checking actual state of tasks connected with a specific app. Nothing fancy here. The thing which was important here was writing down how much time it took to complete the task. When completed each task had two values – estimated time needed to complete the task and time it really took to do it. At the end of the day we knew how much our estimates were flawed. The important thing here was official announcement that no one is going to be punished in any way for poor estimates.

    That was pretty much all. No stand-ups since we were all sitting in one room and we discussed issues and work progress whenever someone felt like it. No Scrum Master since, well, we weren’t doing sprints and within specific project things were rather self-organized. A kind of Product Owner emerged, impersonated by me, as we needed a connector between constantly changing business environment and the team working on different projects. You could say we needed one to bring some chaos to our work which would be equally true.

    We were going to build a few small projects that way. At the same time we were prepared to improve the way we create our software as soon as notice flaws and find a way to fix them.

    Keep an eye on the whole Kanban Story.

  • The Kanban Story: The Beginning

    So I found myself in this small team, part of a bigger company but working pretty independent of the rest of people here. Kind of start-upish environment. I knew every single person I worked with. Well, actually I’d chosen most of them and hired them here. The team was great (if you guys are reading this: no, it is not a reason to come for a raise) and personally I didn’t feel an urge to strictly control everything. On the other hand some order is always a nice thing.

    Initially I gave a lot of thought to project management practices and didn’t come with a solution I was happy with.

    I rejected PMP-based heavy-weight process which works for many projects in the organization. We didn’t need all the hassle they bring. At least not at that stage. A natural idea was Scrum which I didn’t like either. Scrum is pretty formalized methodology too and I wanted to avoid formalisms as much as possible. Actually with a lot of R&D work, pretty much prototyping and priorities changing all the time I needed something more flexible.

    I didn’t want to be time-boxed since we were planning to work simultaneously on a few independent small projects which would be hard to synchronize if we wanted to put them all in one team-wide sprint. Creating independent sprints for each of projects was a complete overkill since you don’t really need Scrum sprint for a one-and-a-half-person project.

    Actually I’d say we were at the point where we were too flexible for agile methods. Now, go burn me in flames for being iconoclast.

    After some discussions we collectively agreed we wouldn’t adopt Scrum as a whole but would use some of techniques used there and some other ideas we thought were good. In the next post in the series you’ll find more details how we initially organized our development.

    Keep an eye on the whole story.

  • Random Thoughts on Estimation

    A lot of discussion on estimation recently. A lot of great arguments but a lot of good old mistakes we’ve already went through. This brought me to a few random thoughts on estimating techniques.

    1. Estimation technique which involves discussion between different people is better than one which just simply uses their estimates as input.
    2. Using factual recorded historical data is better than basing just on experience.
    3. Smaller tasks can be estimated way better than big chunks of work.
    4. Every estimate starts with some kind of guess at the very beginning.

    I know these should be obvious yet I’m surprised how often people:
    – forget about them
    – deny these are true

    Then they head towards wild guesses with some magic number applied, which may have some sense but not when used instead of real estimation.