The iPod would probably have been just another MP3 player when Apple launched it in 2001 if Jony Ive hadn’t been promoted to Chief Design Officer by Steve Jobs during the dot com crash a year earlier. Warren Buffett said it best, “Be greedy when others are fearful.” In the torrent of headlines screaming “RECESSION”, “LAYOFFS”, “GREAT RESIGNATION” it’s important to cut through the noise and see who’s expanding while others follow the herd and discard great talent. In this Punks & Pinstripes Insights article we track which tech companies are swimming against the tide and hiring the talent that is being discarded by others.

We analyzed 2,936 LinkedIn records of people who left 7 big tech companies (Meta, Google, Amazon, Apple, Oracle, Netflix, and Microsoft) over the past 90 days, and tracked who hired them after they left. From this analysis we were able to see which big tech companies are hiring more talent than they are losing. Here are the key takeaways (and if you’re interested in learning how we did it and what we’re doing next, then keep reading)

1. The Talent Headlines Are Bullshit - The headlines of “MASS LAYOFFS” are lazy journalistic clickbait. After people leave these companies they quickly get new jobs. Our data demonstrates why the monthly BLS jobs reports show such consistent labor resiliency. Certain companies are amassing a talent arsenal during the downturn that will enable them to emerge stronger than before once the recession subsides. 
   

2. Amazon is winning, and Meta is losing - if measured by which companies are attracting other big tech talent. Amazon (including AWS, and Prime) has attracted 133 new members of staff from its big tech rivals, the only company with a net gain. Conversely, Meta lost 511 people, followed by Oracle, which lost 382.

3. If Entrepreneurship were a company, it would be more attractive than Apple. 118 people left Big Tech to start their own venture, more than the total number of people who joined Apple. The biggest contributor to this entrepreneur exodus is Google with 42 employees leaving to launch a new venture. 

We have a lot more work to do. In this next section we explain how we conducted this analysis, where we’re going next, and where we’re going after that. 

A little less opaque. Our small victories so far:

1. Culture Eats Strategy for Breakfast. Anyone who has ever tried to build anything meaningful in a huge company knows that Peter Drucker’s adage is true, “Culture eats strategy for breakfast.” But investors and stakeholders have very little quantitative insight into a company’s cultural health, and whether it can attract, retain, and empower the talent it needs to generate great results. Put another way, the war for great talent is all-important, but it’s hard to know who’s winning. We’re very proud to pry open the black box of corporate culture and make it a little less opaque.

2. Hiring Against The Current. This analyzes which companies are are successfully attracting the talent that is leaving their competitors. It only examines the people these seven companies hired from one another. It doesn’t analyze talent they hired from other companies. That fuller picture of talent inflows is next.

3. Data mining is the hardest part of this endeavor. We have found ways to mine data from LinkedIn to track who is leaving and where they go next. Our insights will expand exponentially as we deconstruct the data more. 

What we’re doing next:

1. Are the employees that are leaving actually talented? We’re building an AI layer to evaluate how senior these people are, what products they worked on, their gender/race, and what technologies they’ve used. Eventually we can start ranking talent based on their skills, performance, and diversity and see which companies are attracting the best, most diverse talent.

2. Retention + (inflows - outflows). What we have now is the ability to measure talent inflows from tech rivals. What we’re working on next is the ability to compare how effectively companies retain high value talent, and how much high value talent they attract in any given period. From this we can develop a richer picture of bench strength, and talent burn rates. We will start evaluating which companies are understaffed, and facing a talent exodus.

3. Talent x investment - We’re getting ready to compare who a company is hiring/ retaining to the startups in which it is investing. Does it have the talent it needs to deliver ROI on its acquisitions, VC investments, and partnerships? For example if a company invests heavily in the blockchain but is losing 3 blockchain employees for every one it hires, with only 100 blockchain experts on staff, it is unlikely to deliver a meaningful return on the investment. 

4. From snapshot to time series. We are in the process of building a long term time series to evaluate how a company’s talent expansion or contraction in a specific period compares to previous periods. Currently we can only look back 90 days. 

5. Is Apple becoming a car company? Is Amazon becoming an investment bank? We are next analyzing which talent is leaving other sectors for big tech. For example, is Apple expanding into mobility by hiring people from Rivian and Tesla? Is Amazon poaching talent from bulge bracket investment banks? This will shed valuable light on companies’ product roadmaps.

What we’re doing after that:

1. How does talent affect financial performance? We know talent is important but what performance metrics change when a company gets it right or wrong? For example, does a company with a low concentration of talent, poor retention, and high net outflows underperform its peers? Is their stock more volatile? Are they less efficient as measured by return on assets? We’re eager for our readers, especially our readers who are investment analysts to help us pinpoint how talent affects earnings.

Thanks! Stay Punk!