Reliable Systems

Many if not most software project leaders came up through the development ranks.  It’s generally thought of as a distinct advantage – you know the technologies you’re using, you can form your own well reasoned opinions about how hard something is, what is possible, and how long it should take.  For a long time, I felt that the best way to get results from development teams was to use my experience and knowledge to be very understanding of the challenges they faced and give them whatever time they asked for.  However, in the last few years I’ve run into several situations where I just couldn’t get them the extra time or relief from the most problematic requirements.  I predicted doom to the projects in question but instead I observed some of the best outcomes I’d ever experienced.

While the projects were successful, it bothered me that the secret sauce seemed to be a rigid adherence to schedule and delivery more than any other consideration.  This was exactly the reverse of how I wanted projects to succeed:  I wanted them to succeed because I was treating the developers how they always wanted to be, not like a stereotype from Office Space.  How could it be that better results came from ignorance of the technical details involved?

Developers Will Use All Available Time

Upon reflection, the first thing that struck me was how much an immobile deadline focused discussions and decision making. If you give a team more time, they will expand their process to consume it.  Time will get consumed by:

• Elaborate Decision Making: When you have little time, you make a choice and go with it until it appears it just can’t work.  When you have a lot of time, you sit back and look for the very best option.  That then requires defining what the best is – is it fastest, or smallest, or most scalable, or whatever.
• Development Approach: Under pressure you’ll tend to go with the proven guaranteed approach.  If you have the luxury of time you’re more likely to engage in yak shaving like investigating a new tool or approach, or writing several prototypes first before you develop the real solution.  You might even just throw caution to the wind by skipping a formal design figuring you’ll have the time to just code and test your way to a solution.

The more time a development team has, the harder it is to argue against spending it on up front luxuries.  It also can be harder to argue for long term best practices because the team has the time now to develop a solution any way they want.

Unknowns Create Boomerang Estimates

Even very experienced developers are generally terrible at estimating the duration of developing a solution.  This has been demonstrated over and over by many other parties.  The key behavior that we’ve observed is the phenomenon that from when you approach a specific development problem (like displaying a graph on a web page) until you know exactly how you’re going to solve it (and have a reason for confidence in that approach) you will tend to estimate high because in effect the only reasonable estimate is infinity.

Put another way, as long as you don’t know how you will solve a problem you don’t know for sure that it is solvable which means it will take an infinite amount of time to solve it.  Fortunately, developers are almost universally optimists so they believe they can solve anything eventually – so they’ll pull out a standard answer like three weeks or months or whatever feels like a big chunk of time to figure out the problem but not so big that it kills the project.   The reality is that until you know how you’re going to solve it, it feels like it could take forever.

Once a solution has presented itself  the development team will often find that all it will take is some cleanup and polish to be done- a very small amount of time.  What will push the team to find the answer?  We’re back to the problem of elaborate decision making when you have the luxury of time.  Finding solutions tends to not be a linear problem that will be solved with incremental development energy.  Instead, it tends to be solved by getting people together and brainstorming possible solutions until you find a few candidates and can work out what it’ll take to prove them out.  Under pressure, people tend to focus their creative energy and be more willing to compromise.   That flexibility will tend to get rid of pet requirements and developer gold-plating and focus on the most critical aspects of the problem.

What’s the alternate approach?

The key is to not let your knowledge and experience as a developer lead you to buy into the stories the team creates around what’s reasonable to get done and how long it will take.  Instead, you have to stick with the project’s goals first then the facts of the project.  The project’s goals form the objective reality of what has to be accomplished for the project to survive:  Deliver this functionality by that date, keep these people informed, solve these problems without causing those problems.

When the team runs into a wall and needs more time, instead of buying into the story of needing a lot of time, set a specific and tight goal that keeps a solid amount of time pressure on the team to solve the issue and prevent the problems above from showing up.  Ideally, find a way to give out one or two day chunks to answer incremental questions if necessary to emphasize that time is precious and has to be invested carefully.  This is where you can leverage your experience in a way that a non-developer can’t:  The team knows they can’t snow you with tech details, and you can define a specific, measurable result that can be achieved in a short period of time that they can’t argue with.  Despite this, you are bound to have to assert a few times that the time limit is the limit – solve the problem in that time.  It’s very hard because you’ve been on the other side of that conversation and it can feel like you’re the Pointy Haired Boss, but it’s fundamentally your job on the project.

What will nearly always happen is the team will surprise itself – a solution will be presented within the team that they can live with and can be done in the time they have.  It may be incomplete or have some risky shortcomings, and you’ll want to ask how long it’d take to address those.  You probably shouldn’t address them in the first round, but the team will feel better that you’ve considered through things and will buy into the outcome more if you ask.  You’ll also want to make a record of it so that the team can in the future recognize what was a predicted shortcoming vs. an accidental defect.

Do you want it solved right?

This is a question that often gets voiced within a team as a rebuttal to external time pressures and is very dangerous.  The challenge is that most non-technical people don’t get the number of ways that a problem can be solved: instead, each problem appears to have a single solution.  Take away your technical knowledge and imagine you’re the paying customer:  What’s the alternative – were you going to solve it wrong? If that’s the case, what else have you done that’s garbage?  If you took your car to a repair person and they said it’d be $500 to fix it, then when you came back they said well, if you want it fixed right it’ll actually be $1200, wouldn’t you wonder what the hell the $500 fix was?

Usually this statement is uttered in desperation when a team believes they just need more time to figure out a problem.  Nobody wants a problem solved wrong.  Skip the hyperbole and get down to action:  break down the problem into small chunks of time that can be invested for a specific measurable result, and make sure the team gets that overage time is the most precious commodity.

Side Note: This is an advantage of SCRUM in practice.  If you’re following an Agile Development practice, particularly SCRUM, this fits right in:  Focus on making each sprint deliver the user stories it was supposed to even if you have to leave some special cases for a later sprint.  The daily stand up meetings are a great place for the different team members to apply team pressure against over engineering and doomsday estimates.

Cleaning Up and Closing Out

At some point you need to close out your release and ship it. For each of the areas where you’ve had to make compromises and taken shortcuts you have to choose to either:

• Ship as Final: Decide the implementation is close enough to the intent of the end-user functional requirements that it can be the final implementation (at least until new information contradicts this decision)
• Ship as Temporary: Decide that something is better than nothing and ship the feature with limitations.
• Cut the Feature: Hold back the feature until it can be reconsidered or reimplemented.

You’re nearly always better off shipping the feature, often as a final feature pending more information because it’s very hard to gauge the true impact of each limitation.  This is particularly true of user-facing features and environments where it’s possible to evolve the software rapidly.  Inevitably once it’s in the hands of your users you’ll discover aspects of it that you didn’t think of that will require rework and you may discover that the killer feature you were sure would be the hit of the release is hardly used.  In either of these cases if you’ve invested a great deal of time in making it foolproof the team will tend to resist changing it.  It’s a natural product of the presumed relationship between effort and value.  If necessary, you might put in some temporary safeties to detect and catch the limitations you’re worried about.

The major exceptions to this approach are areas that are too dangerous to deploy if less than fully trustworthy.  For example, if your team is developing a data storage system, software deployment system, or other critical infrastructure your choices likely resolve down to making it as right as possible or holding the feature until it can be reworked.

If it turns out that the solutions that are viable within the schedule have significant limitations, you should make sure these caveats are known to the business – provided you can express them in business terms.  For example, knowing that an algorithm won’t work if your userbase doubles is probably not a significant caveat, unless you know the business plans to double in a relatively short period of time.  Every system has limits, and every software change has risks.  Business representatives don’t like to hear the same items covering the same ground repeated every time you discuss software, and it tends to make them not hear the new and important information as well as sound like you’re attempting to transfer accountability from your team to them.