When it comes to innovating and disrupting your own processes,  there's never really a good time to try to improve something that is already working. There's always a reason to wait for another quarter, to defer until that deal is closed or just to simply discuss it until it goes away.

However, for those who do try and improve, or even change what they do it can quite often seem fortuitously good timing, in retrospect.

This thought came to me when discussing how in the time of the COVID-19 pandemic, many factories have re-tooled to produce face masks, and I started wondering how many manufacturers have already invested in flexible, dynamic smart workplaces.

In 2017 PWC released this vision of 2020, suggesting that companies were expecting 12% gains in efficiency through development in 'digital factories' and Industry 4.0. More recently in 2019, ABI Research concluded that technology investments into Industry 4.0 were worth $59 billion, and could climb to $375 billion by 2030.

Moving towards the concept of Industry 4.0, factories and industries are witnessing a significant rise in the number of autonomous and semi-autonomous devices through artificial intelligence (AI) and robotics, along with enhanced capabilities and awareness using technologies like Virtual Reality (VR) or Augmented Reality (AR). The two other massive shifts here are connectivity (such as 5G and Low Power Wide Area Networks) to allow more flexible set ups and reconfigurations, and data and analytics.

You can install as many fancy pieces of automation and robotics as you like, but somehow you need to transfer the human know-how into those systems. Even if your robots are augmenting and enhancing your human staff (as many do), understanding how the humans do what they do can be a major effort that mustn't be overlooked.

This is why this AI computer vision company I spotted seems to be on to something very interesting indeed.

Invisible AI develop an easy to deploy computer vision based system that can quickly learn how human workers go about their processors. They say there's no code required to get it working and can be set up in minutes.

Understanding how humans work is incredibly valuable in both the adoption of smart factories, but also for resilience planning. Take for example the COVID-19 situation, where all of a sudden some of your best workers were out sick, and you needed someone else to skill-up and stand-in. If you had the level of detail provided by a system like Invisible AI's that process could be a lot faster and much more efficient.