New call for Innovation Co-Lab and old lessons learned
We’ve written before about how we pivoted in the middle of our last accelerator programme with GCHQ and The Landing MediaCityUK. We switched incredibly quickly to deliver our content online and maintained our networking using social tools. So what have we learned in the process?
One size never fits all
Our mission is to help the businesses we work with progress in ways they can’t by themselves. To do this we treat every programme on its own merits. We design the content and experience of each programme around the cohort we attract and their specific needs. This means we rapidly iterate content once the cohort is selected rather than expecting the cohort to engage with boilerplate “here is what we picked earlier” material. We keep our content fresh and relevant.
Contracting time results in tighter content
Having half a day for a full workshop now seems like a luxury. Nearly all of our masterclass speakers felt that being forced to fit their content into a 120-minute online slot with Q&A forced them to really sharpen their output. So the sessions were dense and focussed. We will continue this model for the Co-Lab.
Collaboration software works — mostly
We used all sorts of different tools and in general, most of them worked pretty ok. We’re guessing there is going to be speedy evolution in these tools to really improve the remote working experience. We finished our Demo day with pre-prepared presentations that the cohort had done in Picha Kucha style — and that worked really well for our judging panel.
Making fast changes in challenging times resulted in more patience
We’ve always emphasised tough love and empathy in our work in UP and empathy proved really important in understanding how different founders were coping with their challenges. It’s incredibly hard spending long hours doing video calls as well as juggling everything else including family life so we provided as much support to the cohort as possible. This included probably more one-to-ones than previously. And this is something that will continue into our next cohort.
Iterating and developing new ways of working is really important
So our next challenge is shifting the accelerator model to one of an Innovation Co-Lab. We announced details of that call this morning and you can find more information here
And on some more general observations for tech life in Covid 19?
Well, it’s a burning platform for sure and innovation has really increased in some areas that were lagging behind. Ed Tech has seen accelerated adoption according to this recent Wired article. Wired feature Century an AI education tool that helps teachers tend to each individual student’s needs “very clever but often too forward-thinking for traditional schools”. It has seen a global explosion in growth. Interestingly too Century is a social impact company, not for profit so is this a new turning point on the ethical front as well? Social distancing technology of course also enjoying a surge of development which we saw up close in our last cohort with the great work done by Tended.
And some of the losers?
Looks like the VR barriers to entry still remain too high. While there has been a surge in demand for headsets ironically there are manufacturing issues because of the virus. While it would seem like the time for VR to shine its worth remembering that only 8% of Britons own a headset while more than 95% have a phone. Use of headsets was always going to be an issue in a virus environment but there are some who remain hopeful for the growth in VR for Telehealth. This mobihealthnews piece has a good in-depth analysis of the future role of VR in health.
What we hope to see emerging as part of the Co-Lab
Given the acceleration of interest in AI, Machine Learning and Data Science as part of the global Covid-19 response, we’re really looking forward to seeing companies put themselves forward for selection. We are sure it’s going to be an exciting and innovating 12 weeks so please share with any of your networks working in these disciplines (Data Science, Machine Learning and AI). In the end, we want to create a positive social impact through data science. So come join us.
