Effectiveness, (noun) : the degree to which something is successful in producing a desired result; success.

Over the years, I have tried experiments, read books and watched several talks in a bid to improve my effectiveness. After a series of burnout and recovery cycles, I finally have a 3-pronged approach that seems to serve me well.

1. Learn to estimate well

2. Use the big picture to seek opportunities

3. Continuous Improvement

Lets discuss these three.

1. Estimation – the bane of software development

Reliable coding estimates accurately forecast when feature work will be done. But when is a feature done? Is it when it is code complete? Test complete? Or deployed? Most developers wrongly associate code complete with test completion or deployment ready. This explains arbitrary estimates like: “Oh… I’ll be done in 2 hours”; such estimates typically miss the mark by wide margins due to error compounding. Let’s take a simple bug fix scenario at a fictitious software engineering company.

• Bug is assigned to developer John SuperSmartz
• John SuperSmartz reads the bug description, sets up his environment and reproduces it
• He identifies the cause but does some light investigation to find any related bugs (he’s a good engineer)
• John designs, implements and verifies the fix
• Gets code review feedback and then checks in

Any of the intermediate steps can take longer than estimated (e.g. code reviews might expose design flaws, check-ins might be blocked by a bad merge, newer bugs might be discovered in step 3. etc). Without such an explicit breakdown, it becomes difficult to properly give estimates. Don’t you now think the 2-hour estimate is too optimistic?

Personally, I use kanbanFlow (I love their Kanban + pomodoro integration) to decompose work into small achievable 25-minute chunks. For example, I might break down some feature work into 8 pomodoros as follows:

• Requirements clarification – 1 pomodoro
• Software design and test scenario planning – 2 pomodoros
• Coding (+ unit tests) – 3 pomodoros
• Testing and code reviews – 1 pomodoro
• Check-in + estimation review – 1 pomodoro

Some of the things I have learnt from using this approach:

• I grossly underestimate feature work – the good side though is that this planning enables me to improve over time
• I know when to start looking for help – as soon as a task exceeds its planned estimate, I start considering alternative approaches or seeking the help of a senior technical lead
• Finally, it enables me to make more accurate forecasts – e.g. I can fix x bugs per week…

2. See the big picture

A man running around in circles covers a lot of distance but has little displacement. In optimal scenarios, distance covered equals displacement while in the worst scenario, it is possible to cover an infinite distance and have a displacement of zero.

Imagine working for several days on a feature and then discovering major design flaws that necessitates a system rewrite; a lot of distance has been covered but there has been little displacement. Working on non-essential low-impact tasks that no one cares about is neither efficient nor effective. Sure they might scratch an itch but always remember that the opportunity cost is quite high; the lost time could have been invested in higher priority tasks with a larger ROI.

Whales periodically surface for air and then get back into the water to do their business; so should engineers periodically verify that priorities align with company’s goals. It’s possible to get carried away by the deluge of never-ending feature requests and bugs fixes; an occasional step back is needed to grasp the whole picture. Here are sample questions to ask:

• Where are the team’s goals?
• Does your current work align with company goals?
• Skills acquisition and obsolescence check
• Opportunities for improvement?

Personally I try to create 3 to 4 high-impact deliverables at the beginning of each week and then focus on achieving these. Of course, such forecasts rely heavily on productivity estimates.

3. Continuous Improvement

Athletes consistently hold practice sessions even if they don’t want to because it’s essential to staying on top of their game. The same applies to pretty much any human endeavor – a dip in momentum typically leads to some loss in competitive edge. The software engineering field, with its rapidly evolving landscape, is even more demanding – developers have to continuously and relentlessly learn to stay relevant.

Staying relevant requires monitoring industry trends vis-à-vis blogs, conferences and newsletters. There are a ton of resources out there and it’s impossible to follow every single resource, rather it is essential to separate the wheat from the chaff and follow a select high-quality few.

Learning and experimentation with new technologies naturally follows from keeping abreast of developments. A developer might decide to learn more about the software stack his company uses, logic programming or even computer science theory. Even if his interests are totally unrelated to his day-to-day job, independent learning would expose him to new (possibly better) ways of solving problems, broaden his capabilities and might even open up new opportunities. I prefer learning established CS concepts to diving into every new db-data-to-user-moving framework.

Opportunities abound such as learning IDE shortcut keys, terminal commands, automating mundane tasks and so on. Ideally you want to start simple by selecting the area with the highest impact-to-effort ratio and then dedicating a few minutes to it daily. Over time, the benefits start to pay off.

And that’s about it! Do you have other suggestions?

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