Margot Millory of digital consultancy Artefact looks at the role of data in helping organizations to reduce their carbon emissions – in particular, in the hard-to-measure space of e-commerce.
Unprecedented weather events and record-breaking temperatures in many European countries last year are just two examples of the effect that human activity has on the climate. Global accords and agreements pave the way for future legislation, while organizations are under pressure from many sides to reduce their impact on the environment.
Consumers increasingly expect companies to play their part in tackling the climate emergency, while also altering their own behavior to make their lifestyles more environmentally friendly. For example, French food and drink company Danone is being taken to court by three environmental groups, accused of failing to make adequate reductions to its plastic footprint. Whatever the judicial outcome, the brand risks reputational damage in an environment that is increasingly sensitive to actions perceived to be harmful to the climate.
Data holds the key
While many businesses are committed to reducing their carbon emissions, doing so remains challenging, not least because it requires looking to the long-term, rather than at short-term benefits.
Fortunately, exploiting data (some of which is readily available) allows companies to measure the environmental impact of their activities. And data science can enable them to identify sources of waste and inefficiency and to analyze how to develop products, services and infrastructures to be more energy-efficient.
Reducing e-commerce emissions
Although it is not technically correct to talk about ‘carbon neutrality’ at the company level (that goal is a collective one, unmet by any until it is met by all), European supermarket Carrefour (an Artefact client) set objectives to reduce its e-commerce carbon footprint by 2030. This meant reducing its own emissions, engaging partners to lower their emissions, and encouraging customers to be eco-responsible. Their attempts to do so may be instructive.
Tackling this remit calls for the company to measure the carbon footprint of customer orders, from click to delivery. That requires huge amounts of heterogeneous data from multiple sources (warehouse energy consumption, warehouse waste, mileage data for delivery services, IT infrastructure, etc). This data spread far and wide, and the picture is complicated; a wide variety of issues must be considered (for example, is there a difference in emissions if a customer has their order delivered versus picks it up at the store?).
But a data-driven approach to analyzing carbon footprint can progress carbon emissions reduction plans, encouraging more informed decisions.
The next step is to engage consumers by publishing the carbon footprint generated by each individual e-commerce order, making it easy for customers to review their consumption patterns and choose delivery slots that optimize overall emissions.
Data challenges in e-commerce
It can be hard for companies to gather the data they need to accurately measure their environmental impact. And there are elements over which they have no control, such as how products are used, and disposed of, post-delivery.
Data isn’t always equal; companies can use different measurement methods, or different emission factors. And while industry and sector averages for emissions can quickly identify the most significant emission sources, they’re not a route to accuracy. But collecting ‘sustainability data’ is a relatively new discipline, not overseen by the same restrictions as, say, financial data.
Still, clean data is essential for enterprises to achieve their sustainability goals; data governance ensures that the data on which these strategies rely is trustworthy and accessible for analysis that enables data-driven decision-making.
Data governance is a way to set standards and policies that define how data is ingested, processed and used so that it is a valuable asset, essential for responding to strategic needs and enabling data-driven decision-making. In other words, it enables organizations to derive value from the data to which they have access.
There’s no one-size-fits-all rule for data governance, and each organization must determine its own implementation strategy based on its needs, infrastructure, and data applications. However, there is little doubt that structured data governance should be an integral part of any sustainability strategy.
New ways of operating
Legally and ethically, placing environmental issues at the heart of the company’s strategy is no longer optional; it’s becoming essential for commercial success (in a recent Brand Finance and International Advertising Association study, 79% of consumers reported reducing their use of a brand if it behaved unsustainably).
Making the environment a centerpiece of their business models is pushing organizations to think in different ways and answer to new stakeholders, including informed consumers who expect transparency and accountability. Data can be a major asset, enabling business models that have historically been linear to become more circular. This is challenging, but underpinning new ways of working with data and strong data governance can put companies on the path to a sustainable future for everyone.
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