With Big Tech becoming just a bit less Big these weeks: Facebook firing 10k employees, Twitter halving its workforce on Twitter HQ and Google is likely to follow.
The question of the moment is: “how do you determine engineers to let go?”. At Twitter HQ, the answer appears to have been lines of code. 😳
LOC-based chopping at Twitter
Elon Musk's first intuition (or at least the instinct of someone on his team) when it came to selecting who to chop, appears to have been to look at how much code developers had produced.
After further investigation, this technique appears to be dropped at twitter. You would think appraising developers based on how many lines of code they produce would be universally received with laughter, well you’d be wrong.
LOC Banks
One executive director in the engineering team of a US bank says Lines of Code (LOC) are an important part of the calculus when appraising a developer's competency and the value of keeping him/her.
Almost always, top performers have a high LOC count relative to the team or a high number of projects contributed to. Low performers tend to have low LOC relative to the team
After setting up a 'productivity analytics platform' for its developers, Credit Suisse showcased the following chart in its long-forgotten 2017 investor day presentation. It suggests that a few top-performing teams do most of the work.
Source: Credit Suisse
Moving away from simple Lines of Code measures of developer productivity is therefore very much needed if you did not do this already.
What to measure, if not LOC?
At ZEN Software we think that measuring lines of code or measuring coding efficiency is not sustainable. We feel these methods of operation are outdated for any software organisation. Our vision is to observe outcomes, effectiveness and end-to-end metrics like the DORA metrics, Error Budgets and Software Stock. ZEN Software’s Agile Analytics allows you to keep a close eye on DORA metrics and correlate them with other critical insights in your software operation: Error Budgets, Teams, and Kudos. This creates a clear dashboard overview of the organisational performance and allows for data-driven management. But more importantly: leads to higher productivity, faster time-to-market, less burnout, more engagement, and happier engineers!
