Clean Tech and Data Science Trends In The Age of Covid: Part II
Last time, we looked at how Covid and the restrictions due to the pandemic are impacting the clean tech sector and accelerating existing trends in automation, robotics and artificial intelligence.Today, let’s take a look at how the pandemic is impacting startups and funding.
For a long time, VC funding has been synonymous with innovation. Think of any of the large companies today - Google, Facebook, Uber, Tesla - they’re all products of the venture capital system. Clean technology saw a spike in VC funding in 2008-2010 and then interest and funding dollars waned after that - mainly because of a large number of bankruptcies and losses to the VC firms involved. Also, VC funding is often referred to as “impatient money” because returns on investments are expected within a relatively short timeframe, usually the life of the fund which is about 7-10 years. However, clean technology firms that rely heavily on infrastructure and hardware often take longer to exit and the returns are not as high as software firms for instance.
After VC funding decreased, we saw a lot of startups work with larger corporations in the sector, government agencies and banks to secure funding in more traditional ways. And then, in 2018 we saw a return of interest from VCs, but what they were targeting this time was different. In 2008-2010, VCs focused heavily on capital intensive industries like solar manufacturing, novel methods of producing chemicals and so on. In 2018, as cloud computing, AI and machine learning started reaching maturity, VCs focused on the “Clean Web” sector - i.e. problems and sectors in clean technology where software or a software/hardware combination would be innovative.
In the last 2 years, we saw a lot of startups that used robotics, software, analytics, data science, machine learning and so on to solve very specific problems in the clean tech sector. Examples include Farmers Business Network - a social network and operations management system for independent farmers, Opower - with it’s focus on analysis and reporting in the energy sector, Kairos with its robots for water monitoring and maintenance and many others. In fact, in the last quarter of 2019, it looked like this sector was poised to take off as climate change, regulations and innovation combined to provide a favorable environment.
And then came Covid, the shutdowns around the world and the tanking of the global economy.
Startups in the clean tech and data science space are certainly not insulated from the global trends. The economy tanking means that VCs are pulling back on funding again - so there’s less money available for startups in general. And that’s true for startups in the clean web space as well. New companies are likely to get poorer terms compared to last year and angel and seed funding is likely to be very limited. Also, this time, unlike in 2008, we’re not seeing significant investments from the government, so that source of funds is not going to supplement everything else that’s been lost. Additionally, startups that already raised money are likely to stay as lean as they can to conserve cash over the next couple of years so that they can minimize the chance of having to raise a funding round again.
However, there are several silver linings in this climate. One is that startups in this sector have traditionally focused on building partnerships and collaborations with existing large companies - and these companies are now looking at ways to incorporate greater automation, analytics and machine learning in their operations. So, as we discussed in thelast post, this is actually a great time to be in the smart sensors/predictive learning and clean web space in general.
Further, startups in the clean tech and data science field are not the ones that usually depend on “blitz scaling” - a term that came into being with Uber, AirBnB and others of the same ilk. It means that the companies require large amounts of cash to acquire large numbers of customers so that their nearest competitors are outgunned. Clean web startups typically focus on more organic customer acquisitions and business partnerships, so they can function without huge infusions of cash. In turn, that means that the startups that still have significant amounts of cash on hand are likely to survive this period and may even emerge from it stronger.
And finally, the pandemic is turning many business models and ideas about how economies should be organized upside down. It may well happen that the world’s population decides that there are better, more resilient ways to build our societies. This means that there is likely to be an increased focus on local food, renewable energy, smart cities, climate change impacts, better disaster management and other issues that are integral to clean technology.
We’re already seeing signs of this with people around the world focusing on how much cleaner the air is, how easy it is to see mountains and other natural sights that they had forgotten, how much fun it is to spot the animals that are coming into cities and other spaces humanity occupies.
All said and done, this is a very challenging time, albeit with several interesting aspects to look forward to as someone who’s working at the intersection of clean technology and data science.
Next time, we’ll wrap up this series with a discussion about jobs and skills that are likely to be in demand during this strange and challenging situation and in the future.
The last couple of months have been interesting from a climate viewpoint - we’ve seen a record number of climate related disasters around the globe - drought, floods, fires, heat waves…..and it looks like this is probably going to be what our planet will look like in the near future. Add to that the COP26 conference that is scheduled for October 31st - and climate, sustainability and technology are front page news! So, let’s talk about one of the technologies in the news - artificial intelligence (AI) and its impact on climate, water, agriculture, energy, forestry, ecosystems and other sectors in clean technology . AI and its subset of tools - machine learning (ML), data science and statistics - are being touted as one of the key technologies in solving the problems facing the planet today. And while these technologies are certainly powerful - applying them effectively to solve problems in clean tech is another issue altogether. AI has been used by scientists in different clean tech se
We're in the processes of building a couple of fantastic new offerings that many folks in our community have asked for - so blog posts will be limited for a few months. Our jobs portal will still be updated regularly to make sure that all our members can keep up with what's happening in the sector. We can't wait to share what's happening at our end!
Every Earth Day we hear from companies around the world about their sustainability efforts - the gallons of water they have saved, the reductions in energy use, the systems they have converted from fossil-fuel to renewable energy, the ecosystems they have restored and, more recently the amount of carbon they have offset. On the face of it, these are amazing and hopeful numbers - the very fact that corporations are paying so much attention to sustainability and the environment is testament to the fact that consumer and citizen pressure is yielding results. In fact, with every successive year, it seems that companies and organizations are able to sequester more carbon, minimize greenhouse gas emissions and thus mitigate climate change. What allows companies to make these claims - especially with respect to carbon and greenhouse gas emissions? The way that most companies claim these credits is through carbon markets or “cap and trade” programs. In these programs, a community or a no