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Six steps to solving the sustainability data challenge
29 June, 2021 | Written by: Anthony Day
Categorized: Artificial Intelligence | Blockchain | Topics
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Six steps to solving the sustainability data challenge
Over the past 18 months, uptake of some of the United Nations sustainable development goals has accelerated, with some very prominent global enterprises making commitments to environmental and social change.
The target date cited by these announcements is 2030. That gives businesses less than nine years to halt a plethora of climate and social impact issues that continue to grow exponentially.
There is growing pressure on enterprises of all sizes to make commitments to reducing carbon dioxide emissions, lowering or eliminating plastic waste, committing to clean water and clean energy, gender equality, sustainable communities and other UN SDGs. ‘Net zero’ is just the start, as true leaders talk about creating regenerative effects with their business operations, not just cutting the carbon.
The very recent pressures of COVID-19 have further tested enterprises in terms of their supply-chain resilience. Business leaders are now demanding greater visibility and transparency to support the immediate challenges of supply and demand, requiring better data integration and intimacy with their suppliers.
And finally, there is increasing government and regulatory targets around reporting for all manner of business operations, which is driving a significantly increased need for data measurement, capture, aggregation and integrity, and seeking ways to automate verification and regulatory reporting as compliance and oversight increases.
The good news is that most, if not all, of the digital capabilities required are available and proven today. It is a matter of understanding how to bring them together – not pinning your hopes on a single ‘tool’ – and designing for a collaborative ecosystem across buyers and suppliers that can work together to drive change.
Here are some of the capabilities you will need:
- Standards are needed to ensure that the data is meaningful and comparable across networks. A consortium approach is likely to bear fruit here, with GS1, WBCSD and Climate Chain Coalition doing valuable work on standards.
- Internet of Things (IoT) devices can support the data capture side. Sensors provide a means for logging real-time, machine-generated data that can improve data throughput and integrity and allow for creating specific machine, vehicle or device IDs to enable more intelligent reporting or enable machines and systems to transact with each other.
- Blockchain provides a means for building consensus around the validity of data. It provides accurate, trusted transaction records that offer a shared view of the truth without requiring suppliers to port volumes of potentially sensitive master data. This data layer works well to augment existing ERP systems. You can read here how Mitsui Chemicals are promoting a circular economy with blockchain.
- Analytical tools enable automation and help humans make decisions, whether tracking and reporting live data against pre-defined standards or KPIs or using Artificial intelligence (AI) to make inferences and allow for optimisation where the issues we face are less clear or less structured. You can read here how Yara are using these tools on their farming platform to feed a growing planet.
Now comes the hard work. As a global enterprise, how can you prove that your ESG strategies are being implemented on the ground and are having an impact? Will you have the data, and can you use it and share it with confidence?
Here are 6 steps you should consider taking:
1. Create new data where it doesn’t currently exist.
It may be that you need new kinds of data. And you need to gather it frequently in an automated way, rather than with periodic, manual assessments and interim assumptions. Checking the odometers on a fleet of cars once a month isn’t a viable way to determine your carbon emissions. What you want to know is how much of the time the fleet is using electricity versus petrol.
The more data an organisation has, and the more granular that data is, the more accurate your understanding of your actual impact on the carbon emissions or any other sustainable development goal.
2. Bring data together from multiple sources, verify them and report on them.
You need to start aggregating existing data that you may not ‘own’. Start talking to your suppliers about their operational data to create a shared view of your supply chain and a near-real-time understanding of what’s happening. Ensure that your source data can be trusted by capturing it, storing it, and logging it. And be able to report on your data both internally and externally.
Be mindful that suppliers may be reluctant to invest if they don’t see the benefit, so constructing value assessments and incentive models may be required. Some data may also be sensitive (trade secrets, data that procurement functions could use to gain an edge). Using technologies like Blockchain to gather ‘proofs’ without logging master data can be effective. You can read here how organisations like Nestle and Carrefour are using these solutions today.
3. Then, make decisions with that data.
Today, ‘control towers’ are designed to optimise fulfilment, reduce the cost to serve or maximise profit. They gather and provide actionable data that help supply-chain managers deliver on time, as planned. What we’ll see in the coming years is a control tower that optimises business operations for multiple additional considerations such as carbon footprint or the use of plastics. It will help decide who you buy from, how you deliver, what routes you use and more, based on a constant assessment of your ESG impact.
You might choose different couriers and haulage providers based on their contribution to your emission targets. A local courier that uses a fleet of electric rather than petrol vehicles may win a contract even if they’re more expensive if their emissions data can contribute to your strategic sustainability goals or regulatory requirements.
4. Bring your finance or treasury teams on this digital transformation journey.
For enterprises that are net carbon-positive, we anticipate a further transformation within their financial operations so they can work with carbon credits. Credits can be traded on the open market, turning carbon capabilities into a profit centre. But that may require engagement with treasury, accounting and tax, bringing sustainability directly into an enterprise’s finance operations.
5. Help drive digital transformation beyond enterprise boundaries.
Interacting with carbon markets presents a challenge that will require an ecosystem mindset to address. Today, allocating carbon credits is typically project-based. Enterprises submit actions to a registrar who periodically audits these enterprises and awards carbon credits. It’s not digitised or automated, and it’s not scalable. When 50% of big businesses are looking to register their carbon efforts, the registrars will be overwhelmed unless the process is automated and standardised.
To comply with carbon trading, enterprises need to move to a data model with reporting and verification standards in near real-time so that carbon credits can be issued daily rather than bi-annually. This will increase liquidity, the scale of the market and lower the cost to regulate. However, no single party will design or implement an effective system at scale – co-creation, collaboration, and constant iteration will be required.
6. Solve cost-and-efficiency data and get sustainability reporting at the same time.
This sustainability data problem may seem large and intractable. But this is the same data challenge that enterprises need to solve to optimise cost, efficiency and resilience moving forward. The KPIs are different, but the need for data platforms required to make good decisions to reduce costs, gain operational efficiencies or achieve growth can just as easily enable sustainability tracking and reporting. This realisation will help organisations with the ‘business case’ for change if the regulatory and societal imperatives are not already strong enough.
In summary, driving exponential improvement in ESG impact can only come with better data, automation and collaboration. The tools we need are readily available today and can address the triple bottom line of people, planet and profit. To learn more about how IBM and our clients drive this new way of working with data, check out some of the links and references below and start thinking about the importance (and absence) of data in your sustainability journey today.
Anthony Day is an IBM Partner and Blockchain Leader. He will be leading a client workshop in September to share IBM’s insights into the importance of data and technology for transforming supply chains – and to help organisations find a sustainable path forward. Contact him to find out more – or read more from our experts on the future of Supply Chain, including this article on the importance of data for transparency and traceability in supply chains, published through The British Retail Consortium.
Visit IBM Blockchain Services & Consulting or IBM Supply Chain Consulting
Blockchain Partner at IBM Global Business Services, UK and Ireland
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