Data really matters.
I can already feel your eyes glazing over at the thought of such a statement, but before you switch off please bear with me.
Data has brought us the internet, founded on constantly expanding data, 90% of which was generated in the last two years, which has led to the biggest transformation of society, education, our economy and the largest transformation in communications since the printing press and the phone. Data is now also enabling us to push the boundaries on sustainability.
At the organisational level, data can provide valuable insights on which a robust sustainability strategy can be constructed. My team continually mines data relating to our main environmental impacts (for us energy and travel), in order to increase the effectiveness of our response. But before sharing some examples, it is useful to reflect on the qualities of a useful dataset.
First, you need to have ‘good’ data.
Having spent over a decade now building and refining our approach to sustainability measurement and reporting, we have identified four crucial facets of insightful data:
It needs to be complete: at Capgemini, we bring together over 10 million sustainability data-points each year to directly calculate 99% of our operational carbon impacts and then estimate the remaining 1%.
It needs to be granular: we are able to see the detail in our data. For example, our approach to tracking travel emissions enables us to view travel in terms of carbon, distance and cost, and also to account for travel at countries, business unit, and even client project level.
Consistency is critical: by employing one central team to collate, validate and analyse our data, we can ensure that our data is consistently accounted for across our business.
Data needs to be accessible: the deployment of a global environmental reporting system enables our sustainability leaders around the world to individually access, analyse and report their data.
Then, you need to convert your data into useful insights.
Since the beginning of our sustainability programme over a decade ago, we have been employing data driven insights to shape our sustainability strategy. These insights from our robust dataset has allowed us to accurately predict potential future scenarios, enabling us to set an appropriate and ambitious direction. This included, in 2016, setting science-based targets which give us the confidence to know that our ambitions are in line with the level of action demanded by climate science.
One specific aspect of our dataset, its granularity, has proved particularly critical in engaging our stakeholders. This granularity enables us to communicate with different stakeholders in different languages most accessible to them. It’s fair to say, for most people carbon is not an easy currency to understand – many times I have been asked, so what is a tonne of carbon? For our global real estate team, measuring energy consumption in mega-watt hours is both more logical and relevant, and consequently we set energy targets in mega-watt hours. For other groups, cost is key, and combining carbon targets with the potential hard cost savings available from energy efficiency or travel reductions provides a more powerful motivation than solely talking about carbon.
These insights must be used to drive targeted action.
Specific data driven insights have also enabled many practical actions to be completed. For example:
Smart metering installed in our offices have enabled the tracking and alteration of switch-off patterns based on new knowledge about the patterns of building use outside standard working hours.
The analysis of travel patterns enabled the identification of specific high volume travel routes where investment in enhanced communication technologies have enabled improved virtual collaboration replacing frequent national and international travel.
Analysis of travel patterns have also enabled the targeting on specific travelers to encourage the use or rail rather than air travel in certain situations as well as encouraging tele-commuting and travel outside rush hour periods.
A data visualisation of our business travel
Data analytics is also something that we are increasing employing to address our clients’ environmental impacts. Three recent examples include:
Deploying advanced routing algorithms combined with on-board telematics to drive down fuel consumption and carbon emissions for a large trucking fleet. The combination of reducing the distance travelling together with incentivising more efficient driving behaviours lead to a significant reduction in fuel and carbon.
Developing a ‘Geo-rice’ data platform, which provides an in-depth study of land surfaces and its interaction with climate to optimise rice cultivation for farmers.
Providing an innovative dashboard for a global manufacturer to enable them to understand the end-to-end carbon impact of their global IT systems. The solutions highlighted a wide variety of significant opportunities for rationalisation and efficiency savings.
Mobilising our data for sustainability and change
In a world that has access to more and more data we need to ensure we are using it to drive change. This means making sure we are gathering good and relevant data – and using it to apply the insights which will led to action. In this way we will drive the change needed to address global challenges.
This is an extract from a feature published earlier this month in Chief Sustainability Officer Magazine. The full article can be found here.