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Revisiting McKinsey's software engineering productivity framework, Vitaly Gordon reflects on what's changed and how to implement McKinsey's visibility recommendations within days.
Updated: August 14, 2024
Original post: August 24, 2023
Just under a year ago, I responded to the McKinsey engineering productivity article titled “Yes, you can measure software developer productivity.” The article ruffled a lot of feathers in the engineering community, but while a couple of points have been softened, in principle McKinsey doesn’t appear to be backing down.
Author Chandra Gnanasambandam released an updated take on the topic this past May, where he double-downs on McKinsey’s positions on measuring software engineering productivity. And I have to say, I’m happy to see it. I also felt it fitting to update my original piece with additional insights I’ve gained over the past year.
As I noted in my original response, Shubha Nabar, Matthew Tovbin, and I co-founded Faros AI to transform engineering into a data-driven discipline. McKinsey’s strongest critics were those who view software development as an art, exempt from the scrutiny of CFOs and corporate strategists. We have always taken a different approach.
As senior managers at LinkedIn, Microsoft, and Salesforce, we were forced to become experts at building business cases for additional budget, headcount, infrastructure, or training. We had to demonstrate engineering’s accomplishments and impact on corporate outcomes through data-driven narratives. We had to become adept at justifying engineering spend, headcount, and efficiency to the C-Suite and the Board.
But it was never easy to pull together the data or insights we needed, hence Faros AI was born. And I have to say, our timing was perfect.
Engineering has become one of the most expensive and most complex corporate functions. The business of engineering requires a pragmatic approach to maximizing ROI from that investment. Both DORA and McKinsey’s research finds a strong connection between software excellence and business success, including revenue, profitability, market share, and customer satisfaction. Thus, an organization without a top-down approach a-la McKinsey’s engineering productivity framework cannot rise to the challenges of the day, including the most recent challenge of successfully incorporating AI in our products and engineering workflows.
So what’s changed in the last 12 months? Only good things.
We launched several new engineering intelligence modules for Investment Strategy, Developer Experience, Initiative Tracking, and AI Copilot Evaluation. We built a customized machine-learning workflow that analyzes key engineering metrics against 250 factors that can impact them, so we can identify issues and provide team-tailored recommendations to address them. We also use GenAI tools (LLMs) to summarize and explain the insights to help your team understand them and take action quickly.
These new capabilities we’ve introduced to the platform over the past year make it possible for any organization to get the visibility McKinsey recommends, delivered within days.
McKinsey speaks the language of the C-Suite well. If they can get executives to commit time and effort to removing friction from the engineering experience based on what the data is telling us, I am all for it.
McKinsey’s approach is based on several key points I fully agree with:
There are three points in the original article that I would lend a nuanced opinion on:
While some folks may have had a few reservations about some of the details in the original McKinsey engineering productivity article, I remain excited that McKinsey is continuing to help elevate the importance of developer productivity metrics to their C-Suite audience. We’ve been trying to do the same, like in Shubha’s Forbes article It’s Time For Software Engineering To Grow Up.
And as the number of companies implementing McKinsey’s engineering productivity framework has grown from 20 to over 50, things appear to be shifting in the right direction. With an increasing number of companies focusing on this crucial business imperative, I’m confident that happier, more productive developers will propel business success to new heights.
If you're striving for engineering excellence in pursuit of improved revenue, profitability, market share, and customer satisfaction, reach out to our team. We don’t just provide the technology and technical expertise — we can coach you on how to communicate the work you do to management, how to tactfully roll out the metrics internally, and how to plan for the incremental adoption of productivity metrics.
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