Pawel Brodzinski on Leadership in Technology

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

Tag: project management

  • Is It Possible to Over-Communicate In Project?

    While explaining another thing which I thought was obvious for everyone in the team but appeared as not clearly communicated the question came back to me: is it possible to over-communicate in project? I dropped the question on Twitter and expected answers like “Hell no!” Or “Maybe it is possible but no one seen that yet.”

    Responses surprised me though. Author of Projects with People found problems of being too detailed for the audience or revealing facts too early. Well, what exactly does “too early” mean? When people already chatter on the subject at the water cooler is it too early? When managers finally become aware of chatter is it still too early? Do we have to wait until management is ready to communicate the fact (which is always too late)?

    Actually gossips are powerful and spread fast. The only way to cut them is bring official communication on the subject as soon as possible. Hopefully before gossiping is started. Which does mean early. Earlier than you’d think.

    Another thing is being too detailed. This can be considered as unnecessary or even clutter. Clutter is an issue raised by Danie Vermeulen. If something doesn’t bring added value it shouldn’t be communicated. If we kept this strict we could never post any technical message on project forum since there always would be someone who isn’t really interested which framework we’re going to use for dependency injection or how we prevent SQL injection and what the heck is the difference between these two. And how do you know what is a clutter for whom anyway.

    John Moore looks at the problem from different perspective – over-communication can be bad when it hurts morale. I must say I agree with the argument to some point. Some bad news isn’t necessarily related with people’s work (e.g. ongoing changes in business team on customer side) and can be due to change. Then keeping information for you may be a good idea. However if bad news is going to strike us either way the earlier means the better. One has to judge individually on each case.

    Although I don’t see easy way to deal with above issues they remain valid. Actually I can agree it is possible to over-communicate yet there’s no concrete border or clearly definable warning which yells “This email is too much! You’re over-communicating!” at you whenever you’re going to send unnecessary message.

    The best summary came from Lech who pointed that risk of over-communicating is lower than risk of under-communicating. I’d even say that much, much lower. How many projects with too extensive communication have you seen? One? Two? Personally I’ve seen none. On the other hand how many projects suffered because of insufficient communication? I’ve seen dozens of them.

    On general we still communicate too little. Yes, we can over-communicate from time to time but I accept the risk just for the sake of dealing a bit better with insufficient communication which is a real problem in our projects.

    How does it look like in your teams?

  • Sure Shot Method to Improve Quality of Your Estimates

    That’s the old story: we suck at estimating. Our schedules tend to be wrong not only because there are unexpected issues but mostly because we underestimate effort needed to complete tasks. There’s one simple trick which allows improving quality of estimates. It’s simple. It’s reliable. It’s good. On the minus side you need some time to execute it.

    Split your tasks to small chunks.

    If a task lasts more than a couple of days it’s too big – split it. If it’s still too big – do it once again. Repeat. By the way that’s what agilists came with over years – initial size of user stories was intended to be a few weeks long, now it’s usually a few days at most.

    Why it works?

    • Smaller tasks are easier to process in our minds. As a result we understand better what we’re going to do. As a result we judge better what means are needed. As a result our estimates are better.

    • Smaller tasks limit uncertainty. In smaller room there are fewer places to hide. The fewer places to hide the fewer unpredicted issues there are. The fewer unpredicted issues the more exact are estimates.

    • Small tasks mean small estimates. A month-long task should be read as “pretty long but it’s hard to say exactly how long” task. Bigger numbers are just less precise. Splitting tasks ends up with smaller chunks of work. Small chunks of work end up with small-sized estimates. Small-sized estimates mean more precise estimates.

    As a bonus, during task-splitting exercise, you get better understanding what should be done and you early catch some problems which otherwise would appear much later and would be more costly to fix.

    And yes, the only thing you need is some time.

  • Evidence Based Scheduling – One More Way to Improve Your Estimates

    Somehow my recent discussions are mostly about estimating. Last discussion on PM Clinic happens to be on the very same subject. It reminded me about great technique which can improve your software estimates. It is called Evidence Based Scheduling and I’ve learned this from Joel Spolsky’s article.

    The basic concept is pretty simple. Jack the Developer gets the task. Actually a bunch of them. He delivers his estimates basing on his guts. Estimates are most likely crappy but at the moment it doesn’t matter much. As Jack does his work he tracks how much time he really spends on the task. It may happen it takes two days instead of planned 4-hour effort. Velocity for this task is 0,25 and it goes to the history of Jack. When Jack’s history is long enough you can use it to judge how crappy his estimates are.

    Evidence Based Scheduling uses Monte Carlo simulation which takes some effort to calculate results. However Joel brings some good news here:

    “Most estimators get the scale wrong but the relative estimates right. Everything takes longer than expected. (…) This common estimator has very consistent velocities, but they’re below 1.0. For example, {0.6, 0.5, 0.6, 0.6, 0.5, 0.6, 0.7, 0.6}”

    After completing a dozen of tasks you can get pretty much insight which number you should use to multiply Jack’s estimates to get something close to reality. Of course full-blown simulation will probably lead to better results but you get the idea.

    There’s one more gem in Joel’s posting which is worth stressing:

    “Fix bugs as you find them, and charge the time back to the original task. You can’t schedule a single bug fix in advance, because you don’t know what bugs you’re going to have. When bugs are found in new code, charge the time to the original task that you implemented incorrectly. This will help EBS predict the time it takes to get fully debugged code, not just working code.”

    I know it brings quite a lot of effort for Jack the Developer, since sometimes he fixes bugs really fast and accounting time spent on each bug fix to proper original task adds enough hassle to be reluctant to do so. However the ends are worth means this time.

    I strongly recommend you reading whole article as it delivers all the details about Evidence Based Scheduling.