How to Navigate Disasters in Tech (Part 1)

by McMurchieApril 8th, 2022

Too Long; Didn't Read

Some of the biggest disasters in tech have a common underlying theme, these include the lack of long-term thinking, prioritisation of the wrong things and a failure to adapt. This is known as playing the finite game, rather than the infinite game.

featured image - How to Navigate Disasters in Tech (Part 1)

Did you know: more than one-third of workers changed jobs or were fired in the past two years.

To say that the Tech & Finance industries are undergoing some challenges would be an understatement. We are facing mounting pressure on all sides with supply chain issues, the Energy Crunch, a global talent shortage and war in Europe to name but a few.

Yet, we aren't exactly making it any easier on ourselves, from Alexa telling a 10-year old girl to touch a live plug with a penny - to regulatory breaches from Uber test-driving autonomous cars without state permission, running 6 red lights as a result.

Finance hasn’t been spared the controversy either, multiple institutions have lost significant wealth from poorly deployed AI, and there has also been colossal investment wastage from backing the wrong AI sectors.

Video - Material sourced from my recent talk in London

So what's going on here? Is it the leadership? Are the staff lacking? Maybe it's just external factors like market conditions to blame? These reasons are all valid, but they are merely symptoms of the underlying cause which can be traced back to a strategic failure in short-term thinking. Let's look at some concrete examples first...

Table - Fintech Vs Enterprise hiring tendencies during Covid.

During the pandemic, both Enterprise and Fintech froze headcount during the first downtick but they decided it would be a good idea to keep those new projects rolling in.

Then, the second downturn came and both decided to slash headcount. Fintechs thought it would be a good idea to cut their staff and transfer all the responsibilities over to a single rockstar (a.k.a 10x developer). That developer would get a small pay rise and a pat on the back, and everything would be dandy.

Enterprises were a bit more sophisticated in their approach, they still cut headcount but they decided to renew toxic service agreements that they had planned to terminate and they filled in the gaps of fired staff with new tooling automation.

Surprise surprise their strategies backfired, within a matter of months when things began to settle the companies found they could no longer meet their project targets.

HR immediately scampered back into recruitment drive, phoning up staff they fired just 10 months ago, “hey long time no see, do you want your old job back?”

This blog and my associated talk can be thought of as taking Simon Sinek's infinite game philosophy and peppering it with real-world case examples.

This is a classic act of balancing the books via mass layoffs, a redundant strategy from the 80s and 90s when the economy was undergoing the boom years. Today all this has done is to make a disloyal workforce even more disgruntled and untrusting.

What is the solution? Sometimes the simple answer is the correct one. If companies place longer-term strategic value on their staff ahead of pleasing the board with short-term quarterly profits, they can maintain a more stable and resilient business.

Bad Leaders Make Bad Business

Figure 2 - In my , I discuss the rise of bad leaders in tech and discuss some shameful examples.

Do remember the Volkswagen emissions scandal where they were caught using special software to get around emissions regulations? Well, the CEO at the time Michael Horn blamed a couple of developers for the whole thing calling them “rogue employees”. Those who may be in leadership positions know, even if that was the truth (which Congress highly doubts), as a leader it is your role to take responsibility and shield your employees as best as possible, it’s why they get paid the big bucks!

Michael Horn certainly isn’t the only leader blaming others around him, Tim Armstrong from AOL also threw two employees under the bus in an announcement to staff over an unpopular change that had been implemented in the company.

Then we have bad influencers such as Siraj Raval who is the #5 most followed developer on GitHub out of 32 million registered accounts. In the early days of modern ML, Siraj had made a name for himself by producing consistent, high-quality AI content and showcasing it on YouTube. People were curious,

“How is this guy producing so much high quality projects each week?”

It turned out that he plagiarised them all. He would do videos like ‘watch me build a blockchain trading app’ which was 100% copied code from other on GitHub. He only got stopped after the open source community finally mobilised and the number of accusations grew too big to ignore.

It didn’t stop there, he released paid ‘high-quality courses’ with promises that he failed to deliver, including the promise of certain high named teachers who did not turn up, content that was not taught and special mentoring services that were not given. To make it worse, thousands claimed their money back (as the sites promised) with very few of them ever seeing that $500 return to their bank account, I was one of them.

Again, Siraj is not the only one playing this game. There have been shameful scandals with more recent Tech bloggers and YouTubers such as the , who again use their position to rip off and in this case bully others.

It’s not just leaders and influencers that are rocking the boat, in part 2 I will cover some more whoppers by showing you what negligence in Data, Architecture and business looks like.