Let’s continue where we left last time.
The other extrema – typically found in “management level” PowerPoint presentations, showing absolutely nothing useful at all. Avoid it.
As a it project manager you should be familiar with the language your team is using. Even if you come from a different language and were a professional coder yourself, it doesn’t always mean that you will know which problems the team using that specific language will encounter.
Since beginning by reading books is quite terrible and boring idea the best way to learn a new language is to write a program that covers a lot of topics (and in turn, this topics could lead to serious problems). You need a standard program.
It should cover:
- (Console) line in / output
- Retrieve data entered by user
- Simple algorithms
- Long term data storage
- Standard data structure like linked lists
- How to deal with exceptions
- How will the program scale, will it adapt to new requirements
A wonderful solution is provided by the animal game (I’ll cover that on an extra page).
Each product has only one goal – to suffice the customer’s demand.
Even the smallest projects tend to grow and expand. If you omit integration process the entropy will finally win.
Convince your superiors to provide you with best people possible for the integration process. Every project needs its “king of deployment”.
Continuous integration and version control are your tools to go – someone messed something up? Just revert his/her commit. You need a build every night with all tests up and running? CI is your friend.
Avoid “we’ll write a script for this problem” at any cost. Scrips are fragile and are hard to debug. Your road to hell is paved by scripts that got out of control.
While integrating there are only few ways to do things right and a lot more to mess stuff up. Take the integration seriously, invest every possible minute in it.
The two most important thing you’re obliged to do as project manager – keep your project within initial borders and don’t let it die a slow feature-death.
I think everyone knows the basic triangle – volume, resources, time (pick two). Marasco however adds a fourth dimension – quality (nobody will care a year later on if you delayed your project or exceeded budged, only quality will remain).
At this point a small digression – Marasco now translates this thoughts into some mathematical formulas. Although I’m not a fan of stuff like “If we assume normal distribution we can calculate the probability of our project to fail…” – please don’t do that. If you ask every team member “can we do that project?” – their answers is your best probable guess, not some distribution. However some conclusions are to be considered:
Like Brooks said – most project fail because of lack of time compared to all remaining reasons combined(!).
You can’t compensate lack of one parameter by the other (in big volumes).
You should adjust parameters equally (you can’t add a ton of quality with just one week development time)
As a project manager it is your duty to create an atmosphere of confidence – nobody should be punished for not being able to give a perfect time estimation. This only leads to defensive mechanisms and developers will often increase the estimation to be on the safe side which in turn is bad, because you can’t rely on this numbers.
What is the main source of all
evil project problems? Basically every project manager sees the working time estimation (for the whole project) as a working document, while their superiors see the time plan as a contract. Often it arises two types of time plans – one for the outside world and one for the inner development. This is a little fraud and Marasco recommends using one honest time plan.
What are main reasons for bad planning? First of all – there are almost never known all connections between certain software parts. Just use some simple combinatorics – if there are two parts that needed to be connected, there are only 2! = 2 ways of doing that. If there are three parts we have 3! = 6 ways of combining them. Let me just tell you, that n! increases really fast… You can prevent that by using small iterations, because by forcing to release a working product at the end of an iteration you can reveal hidden dependancies.
Second main reason is that delay may sneak in unnoticed. Brooks said – a delay by a year starts with a delay by one day.
If time estimation was given honestly your usual project delay should be around square root of remaining time. Let’s say you are at time point 0 and your project is estimated by 16 weeks. This means that you will probably finish between 16 and 20 weeks from now on. If you are in week 12, meaning that 4 weeks are remaining (and everything went fine so far), project delay should be around 2 weeks, meaning total development time between 16 and 18 weeks.
If you end up being faster than square root of a given estimate – you have a typical example (and problem) of someone being too defensive. The only right thing to do is to fire those people.
So basically you have following: ideal time estimation = ITE = good.
ITE +1*sqrt(remaining time) = help required.
ITE – 1*sqrt(remaining time) = excellent.
ITE +/- 2*sqrt(remaining time) = both cases very bad
How to achieve honest and objective estimation? Note every estimation (good thing is, nowadays every task tracking software supports such features) then write down each result based on given estimation. This will help you calibrating your project and the work of each individual project member.
Remember – not the result is important but rather its predictability.
Just like a lot of stuff in our lives, even software projects follow certain rhythm. Compare it to a learning curve – at the beginning development process is slow – you are planning a lot of things, organize them and do research. Then you gain speed – the main process begins. When reaching the end state you might encounter speed decrease because a lot of little problems pile up and now is the time to solve them.
I bet you can confirm it on an intuitive level – projects start heavily, then accelerate and then stick in sort of swamp. Sometimes a feeling arise that you cross the finish line barely walking.
If we translate this into iterations we can encounter that there is negative “force” at transition points. This is where you as a PM should invest your energy to get the project curve up again.
Some interesting derivative information from that research – about 60% of required knowledge you receive during the first 40% of the project, but at that point only about 25% is effectively done. It lowers the risks (because you are investing time in planing and research), but on the downside you can’t show a real progress. To discuss the importance of the “learning” with your superiors you should prepare for example a list of risks and how the learning might reduce or even completely remove such risks.
Right now, as I’m finishing the second part I realize that it just takes too long to write such a detailed summarization and, what bothers me even more is that it makes it even harder for my rare visitor to follow such an analysis. Therefore I will switch from now on to shorter, more personal articles.