Why ESG and Sustainable Investing are good for Data Scientists and Engineers
Sustainability & its cousin ESG both give us a “why” that appeals and inspires. The transition from shareholder to stakeholder capitalism is long overdue and I am delighted with the Investment industry’s rapidly growing focus on ESG, Sustainability & carbon footprint reduction. Covid19 has also shown that to bring about accelerated change, there needs to be a mission that inspires. In this blog, I refer to ESG, but my points apply equally to Sustainability and the need to reduce our carbon footprint.
ESG investing will have a profound impact on Wealth & Asset Management firms in ways that have yet to be fully recognised. The thing about hard things is that they are hard. With my engineering hat on, I believe that doing ESG is already hard but doing it well will be very hard as firms and their teams will need to master 3 complex skills of Big Data, Continuous Experimentation & DevOps.
Big Data – ESG involves lots of data. Lots. Structured data. Unstructured data. Huge datasets. Complex tagging. Just figuring out what data to use is a hard but crucial phase in data gathering. Then it needs to be sourced, stored and cleaned up. But not just as a 1 off exercise, but as a new digital supply chain.
Continuous experiments – ESG falls firmly into the “it depends” category. Ask 6 people and you will get 6+ opinions as to what is of value & how to do it. The thinking, approach and success for each company will evolve better if their teams embrace a continuous learning way of working.
Actionable Insights “DevOps” – ESG investing will generate many new insights. But, if these insights cannot be acted upon, then their value decays rapidly. Having a “paved path” to production is vital to avoid the risk of the Lab Trap. Today’s insight is tomorrow’s commodity.
Bruce Forsyth told us that “Points win prizes”. My suggestion is to run an experiment on your ESG project and/or big decision r.e ESG. Opinions are worth 1 point. Observed insights are worth 3 points. Data led insights are worth 5 points. Double the points if these are done by your teams, using your data. It is rarely the case that the HIPPO (Highest Paid Person’s Opinion) is right. Try it for yourself and see.
ESG investing is about data and this will create a new “War for Talent”, with fierce competition for the top Data Scientists and Engineers. There is already an acute shortage of talented Data Scientists & Engineers, especially those with cloud-native skills. According to 2019’s Stack Overflow’s Developer Survey, Python is now the 2nd most loved programming language in the world. Blimey! Databricks in a recent blog, predicted that Open Banking will do to banking what open source did to software. I agree. I also predict that ESG will have a similar impact, namely:
- Accelerate innovation
- Launch new business models
- Create massive value for disrupters and adapters
For the foreseeable future of years (not months), then firms will need to roll their data sleeves up and get dirty with the data. For sure, more sophisticated solutions are coming, where most of the heavy and complex lifting will have been done by others, but realistically that is a long way off.
Without talented Data Scientists & Engineers, then a firm’s future success will be constrained. Many firms in FS have got away with an Excel and Email approach, which whilst sub-optimal is known and proven. But good luck to those who continue with that approach when working on huge datasets, from multiple sources and providers. It is not going to work. However, doing nothing now and being late to the party is a huge risk given the rapid in-flow of AUM into ESG Funds.
We live in an age of wonder. Where multiple coronavirus vaccines can be created at a speed and effectiveness, that would have been unthinkable only 3 years ago. Whilst ESG may not have the same impact on innovation and collaboration, I am confident that there has never been a better time to be a skilled Data Scientist or Engineer.