Capgemini Exclusive: Mobilise your data for sustainability
Dr James Robey, Global Head of Environmental Sustainability, leads the Capgemini’s sustainability programme across 40 countries and is responsible for the delivery of a new ambition to help Capgemini’s clients save 10 million carbon tonnes through leveraging technology. In this column, he gives his perspective on the criticality of good data for driving change and engagement.
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.
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Before going further, an admission – with a background in maths and economics, I have always had a fascination with numbers. More recently, in 2016, my research with Henley Business School culminated in modelling responses from sustainability leaders in 200 of the world’s largest companies to understand the business case drivers for their investment in sustainability. And the organisation I work for, Capgemini, is a major technology and consulting house, which continuously provides analytics and data insights to help clients across the globe transform their businesses. So, I know that data matters – and it is because of this that I am such proponent of data for sustainability.
One powerful sustainability dataset is curated by the Global Footprint Network [ https://www.footprintnetwork.org ]. Based in California, it collates a vast array of sustainability trends from around the world to provide instructive insights into the combined environment impacts of humanity at the global and country level. Ultimately, this extensive data set can be represented in the following graph:
The graph illustrates in a simple yet effective way, that since the 1970s humanity has been living a collective lifestyle beyond its means. This is graphically conceptualised above as the number of planets like Earth that would be required to support humanity’s current consumption patterns. Today that is 1.7 planets and based on current business-as-usual trends it will hit two planets in the next few years. Good data tells a story, and the Global Footprint Network’s dataset tells a story while issuing a very clear warning.
At the organisational level, data can also 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.
Accelerating solar transition with robotics and automation
Professor Tadhg O’Donovan, Head of the School of Engineering and Physical Sciences at Heriot-Watt University Dubai, shares his views on how robotics and automation can deliver a real impact in leading the Middle East’s transition to solar energy and in advancing the overall sustainability agenda
As the world grapples with diminishing supplies of oil and the need to reduce carbon emissions, the adoption of disruptive technologies such as robotics and automation can be an important catalyst for the proliferation of renewable energy. Current applications and research show that robotics and automation help simplify the processes involved in support of renewable energy generation, especially for solar energy sources, which results in increased productivity, and cost savings.
Solar panel placement
Robots and automation can help unload and place solar panels onto racks at huge utility-scale sites. Thanks to outdoor, autonomous robotic technology, the process for solar field assembly can be made more efficient. Moreover, due to the fragile nature of solar cells and wafers, high-speed impact robots are more suitable and gentler than manual handling which helps ensure higher throughputs with better yield. Robots support solar construction crews, not replace them which means utility-scale contractors are able to reduce large amounts of repetitive tasks and improve productivity, bolster worker safety, and produce more MegaWatt-hours, faster.
Solar panel cleaning and maintenance
Crucial tasks such as removing dust from solar cells can be automated with the help of self-cleaning robots which is otherwise risky for people. Dust removal is critical in high dust-density regions such as the Middle East to maximise the irradiance incident on the panel and to ensure the solar panels provide maximum power output and energy yield. Water-free autonomous cleaning system can save billions of litres of water over the lifetime of a plant situated in arid regions.
Manufacturing of solar power systems
Robots in the PV manufacturing process make a significant contribution due to their ability to reduce costs considerably and enhancing precision and accuracy when compared with human intervention. Manufacturers can deploy robots and automation to make smarter and swifter production decisions, which ultimately increase precision, reduces the cost of production, and improves productivity. Silicon ingot, silicon modules, solar cells, and silicon wafers are some examples of delicate components that can be produced with high precision through robotic automation.
Integrating robotics into the renewable energy industry comes with a few of challenges too. One of the largest challenges being the power grid itself which is primarily designed to transport energy from large, centralized power plants fuelled by non-renewable sources such as natural gas and oil. Hence, the current power grid requires an overhaul before solar and other forms of distributed renewable energy can be truly integrated as a viable source of power.
Fresh power grid designs
Propelling the energy industry into the future requires fresh approaches to the power grid design. The answer lies with smart power grids that can integrate various renewable energy sources and help utility companies achieve greater efficiency and sustainability.
An increase in the integration of robotics and automation in the renewable energy industry could lead to an eventual total shift from other sources of energies such as oil to greener alternatives such as solar. Finally, this will spur the creation of “jobs of the future” – especially in high-growth data, digital and robotics engineering.