As 2021 draws to a close it’s worth reflecting on what’s happened during this first year of recovery from the pandemic and how this might shape what we do in 2022.
The vast majority of us are working from home, for at least part, if not all of the week. And whilst I’ve noticed more and more people taking the train into Waterloo in the mornings and afternoons that I’ve travelled in, everyone I’ve spoken to have confirmed that they are just travelling in on the ‘odd’ days. We’ve also heard that companies are planning to halve their office space or at least totally reconfigure it – away from dedicated desks to ‘hot’ desks.
I’ve also not noticed a drop in the number of virtual meetings and this could be a consequence of this hybrid mode of working we are still in (as it’s the only way to ensure everyone can attend, regardless of where they physically are). But have you also noticed that we are still now having shorter meetings than before covid struck? A typical one-hour F2F meeting has now become a thirty-minute meeting on Teams or Zoom. Whilst this encourages us to all be very efficient on call, are we missing out of all of those random side chats and social banter we used to enjoy on the longer calls?
I’m guessing we are all still trying to work out how best to collaborate in this hybrid world and how to stay in touch with what’s going on. And we can no longer swivel round on our chair and ask a colleague for their advice or help. These opportunities are sorely missed and hard to replace.
But, if this is the way it’s going to be, then we must adjust. Indeed, several of the firms we represent have, in a funny sort of way, ‘benefitted’ as a result of covid. For example:
We were all given very little notice to leave our offices and work from home. No one was prepared for this, at all, yet we made it happen. We were lucky to have access to high bandwidth internet connections and tools like Zoom, Teams and Miro. But as mentioned earlier, covid time pressures required one of our firms to make a medical grade app in as short as time as possible, as lives were at stake. Isn’t it remarkable how quickly we can move when we need to. It begs the question, “why can’t we move this fast always?”
One of my hopes is that as the covid dust ‘settles’ we won’t revert to our old ways and timescales; that we will want to continue to do things more quickly than before. If the experience of one of our firms is to go by, this appears to be the case. This firm has spent the last ten years developing bespoke mobile apps with some considerable success. If I recall about 120m people use their apps which process $bn per annum. This company has taken all of their experience and used it to build a tool (called App Rail) which would allow people to develop native mobile apps with zero code in hours and days rather than weeks and months. Judging by the interest in this product, people do want things more quickly than before!
It’s no good developing something quickly if it doesn’t work. Can you imagine what would have happened if the covid app didn’t work, or gave false results when finally released? It would have caused havoc and a loss of creditability. Which is why we are very excited about Digital Twin technology which not only reduces the time it takes to design a product but also allows you to see how the product will perform before you even make it! Powerful stuff. Car designers no longer have to have a design rejected because it will be too costly to make or fail a crash test or not meet performance criteria. This can all be determined as one combined effort rather than a sequential process with occasional re-designs. That’s a huge benefit
Can you imagine how much money has been spend building and filling data lakes and all the effort that has gone into cleaning, summarising and aggregating data before it enters the lake? I would guess trillions. But just how much value have we extracted from those data lakes? Again, I’m guessing, nowhere near enough to justify the money sunk into them. And just how important is it to clean all of your data first? With AI, it turns out, it’s not so important. Indeed, the opposite appears to be the case. The more you clean and scrub your data, the more value you lose. Let me give you an example of what I mean.
At the outset of covid we were approached by No 10 to see if we could help them make sense of all of the covid data flying around; some of which was contradictory and some of which could be wrong or misleading. We were ‘handed’ about thirteen different data sets from internal and external sources and asked to find the truth and patterns. Within six weeks our firms had stood up a data platform that could ingest and correlate all of this data (suitably anonymised) and written the algorithms that would provide the truth and explain what was happening, where and why. We didn’t have to clean any of the data nor make sure it was consistent. AI helped us make sense of what we had.
With the increasing power of AI we should stop building data lakes per se and start building data pipelines from source to user, applying AI on the way, to make sense of that data. In fact, I’ve coined the following phrase – “stop staring at your data lakes being filled. Instead look at the sky. Find a use for your data and get into quickly into the hands of those that need it now.
And finally that we all have a super Xmas and see the back of covid!