The problem with running a team at full capacity

I shared this earlier on LinkedIn, but thought that it was worth sharing it here too as a reminder to myself: Six Myths of Product Development

I came across the article above while researching why a team that traditionally does great work may sometimes stumble (yes, mine). The past few weeks had been a whirlwind of activity, with team output close to or at an all time high. We were publishing and developing things left and right, and everyone was running close to capacity. It was great.

Then came an e-mail that questioned the quality of the output. Then another. Much of the great work threatened to come undone, but thankfully most made it through unscathed. We were still, generally, in a good place. But this was a wake up call. Something needed to be done.

After I explained to her my conundrum, my knowledgeable friend, Google, suggested an article from the Harvard Business Review website called “Six Myths of Product Development.”

It was a most excellent suggestion.

The article highlighted six myths or fallacies:

1. High utilization of resources will improve performance.
2. Processing work in large batches improves the economics of the development process.
3. Our development plan is great; we just need to stick to it.
4. The sooner the project is started, the sooner it will be finished.
5. The more features we put into a product, the more customers will like it.
6. We will be more successful if we get it right the first time.

It didn’t take long for me to realise that our problem was very likely linked to #1: I’d neglected slack.

You see, I normally tend guard slack time jealously as I know time-pressures are often a big cause of low quality output. But given the myriad of “urgent” business needs had allowed myself and the team to run too close to full capacity.

We have seen that projects’ speed, efficiency, and output quality inevitably decrease when managers completely fill the plates of their product-development employees—no matter how skilled those managers may be. High utilization has serious negative side effects… Add 5% more work, and completing it may take 100% longer. But few people understand this effect.

It’s funny how bringing down the amount of expected output may actually increase it.

(As an aside, I love point #6 – I’m a big fan of “fail fast, fail often” as I believe strongly in “the wisdom of crowds”, where we can aggregate feedback and iterate quickly, especially for early development. But it’s not always easy to get business buy-in, especially when all they see in “fail fast, fail often” is “fail”!)