Cecil the lion and the big data revolution

‘Big data’ has been one of the buzz phrases of the last five years and has already spawned an analytics industry worth $125bn. But is it all hype or does it have the power to revolutionize the worlds of corporate responsibility and responsible investment?, asks Hendrik Bartel, ceo and co-founder of Insight 360

We live in an increasingly interconnected world. Many of us own a smartphone, tablet or laptop - if not all three - and are part of digital processes that generate around 2.5 quintillion bytes of data everyday; enough to fill 57.5 billion i-pads.1 Indeed, we now generate data at such pace it is estimated that over 90% of all the data in the world was generated within the last two years.

Big data has already become critical to the business of sustainability. The growth of corporate responsibility reporting among the world’s largest companies has resulted in vast amounts of sustainability performance data in various formats. For example, CDP requests greenhouse gas emission and other environmental data from over 11,000 companies in 60 countries,2 and over 8,000 organisations have reports published on the Global Reporting Initiative (GRI) database.3

This data provides previously unavailable information which, if analysed well, can help us better understand current trends and make smarter decisions. It seems clear that this revolution is here to stay. We have entered the age of big data.

Finding the signal amid the noise
Big data sets are often too large and too complex for humans or traditional computing methods to meaningfully understand, and much of the information generated is little more than noise.

However, those who successfully extract the value from within this noise are already reaping the rewards. For example, by analysing web searches and social media posts, Google has been able to determine flu outbreaks in 30 countries with a similar accuracy to the Centre for Disease Control - and in real-time.4

In particular, ethical and responsible investors should take inspiration from these industries. Investors are increasingly swamped by a huge volume and variety of environmental, social and governance (ESG) data. ESG data includes diverse sets of variables, such as disclosure on climate change, water management, labour standards, executive remuneration and board diversity. As more and more information on these indicators becomes available it is becoming harder for investors to extract the really useful information and thoroughly understand its material implications.

It is clear that the responsible investment sector needs technology to help it extract the pieces of data that really matter to their investment analysis and decision making processes.

That is why new breeds of computing systems, especially cognitive computing platforms which allow algorithms to adapt, learn and think, are becoming increasingly important in sustainability.
These systems enable vast amounts of data to be analysed, more dots connected and deeper trends understood.

How responsible investors are benefiting from big data
Mainstream investors have also recognised the potential of big data to provide new and additional insights to guide their investment decision-making. Large firms such as Blackrock, J.P. Morgan and UBS have all increased their spends on big data analysis in the past year, and State Street has just opened the “State Street Global Exchange” – a big data division devoted to investment analytics and data management.

Now some tools are emerging to help ethical and responsible investors reap the rewards of this exciting new data era.
For example, my team and I have been working to bring technology experts together with sustainability leaders such as Harvard academic Dr. Robert Eccles and Dr. Jim Hawley to create a cognitive computing platform useful for responsible investment. The result has been the ‘Insight360’ platform, which uses natural language processing (which means it is able to derive meaning from normal or everyday language - just as a human would) to derive quantitative data from a variety of sources. It monitors over 5,000 publicly traded companies – including all those listed on the NYSE and NASDAQ - against over 50,000 sources and extracts the relevant information on issues affecting sustainability performance.

For example, in August 2015, Insight360 was showing a downward sustainability trend at Delta Airways, due to a number of negative events including rejected labour contracts and ongoing litigation regarding the use of Dallas airports. This downward trend was halted when Delta announced a policy banning the transport of big game trophies in the wake of the killing of Cecil the lion.

After this positive action we saw an uptick on sustainability performance at Delta, and investors using the platform were able to immediately feed this information into their portfolio management processes.

What are the downsides to big data?
Like any strategy, big data analytics carries risk. Some might argue that we are developing an over reliance on data sets at the expense of company meetings and on-site visits. To try and take advantage of the insights offered through big data analytics, while recognizing that data alone is insufficient in understanding the bigger picture, Insight360 focuses on making the hands-on work by analysts more focused, productive, and up-to-date by providing them with the relevant information they need and the tools to understand their implications.

We are only just beginning to see the implications and extent of what cognitive computing and big data analytics will be able to accomplish. When used in conjunction with, and to complement, traditional investment processes, the potential benefits that arise from smart machines and big data far outweighs the risks. It is an exciting time for technology and for ethical and responsible investment.

1www.efinancialnews.com/story/2014-01-13/why-big-data-is-big-business-for-asset-managers
2https://www.cdp.net/en-US/WhatWeDo/Pages/cdp-worldwide.aspx
3 http://database.globalreporting.org
4http://medicaleconomics.modernmedicine.com/medical-economics/news/google-flu-trends-collaborates-cdc-more-accurate-predictions?page=full