Balancing Profit & Planet in the Supply Chain


A recent Gartner survey  found that more than two-thirds of CSCOs are still recovering from a previous disruption even as a new challenge lands on their doorstep. This continuous, seemingly endless series is a result of the complexity of the current global supply chain network. Moreover, decades of evolution, innovation, changing customer expectations and a burgeoning understanding of sustainability issues have led to an uneasy balance between profit and the planet.

Overcoming entrenched environmental challenges

Maintaining a sustainable and robust supply chain involves anticipating and reacting to disruption effectively with minimal impact on profit and planet. At its simplest, this means integrating potential financial and environmental repercussions into existing decision-making processes.

For instance, evaluating the carbon emissions and potential fuel cost reductions of various transportation choices entails considering not only the route but also the vehicle being used. With road transportation from commercial vehicles comprising 65% of total transportation emissions, as stated by the OECD, there is immense potential for optimisation.

We can also look to waste management, where predictive AI forecasts short shelf-life products according to weather, seasonal spikes, competition and marketing. This detailed level of forecasting means the supply chain can flex to meet demand without producing surplus inventory. A recent report by McKinsey indicates that $127bn can be saved each year through reducing food waste.

Visibility, connectivity and resistance are key to sustainability 

Implementing these new technologies involves a transformation in perspective and overcoming some of the embedded challenges inherent in legacy supply chains. Firstly, there is minimal visibility of environmental impact across an organisation’s supply chain. Without robust data related to indirect carbon emissions, for example, it is impossible to predict future impacts based on new investments or changing corporate priorities. The key is to make use of what we can evaluate and let AI to the heavy lifting, using large datasets to develop diagnostics and network optimisation to reduce waste and carbon output.

There is also usually a disconnect between corporate ambition and sustainable strategy, creating conflict between sustainability targets and profitability. Addressing this requires the alignment and analysis of agreed sustainability metrics with historical supply chain metrics, making the correlation between environmental impact and financial outcomes more visible.

Furthermore, resistance plays a part in the hardened organisational mind so making these changes is never easy, however, resistance to change is no longer an option. Customers are more than happy to make a stand when environmental issues are involved and wider legislation and regulations are mandating action. Therefore, linking profit and planet more directly is the only option, despite whatever ingrained corporate behaviour exists.

Introducing supply chain digital twins

Technology is at the heart of making progress in sustainability, particularly AI and the Cloud, which both power the concept of the ‘digital twin’. This involves building a digital replica of your entire supply chain, aligned with planning and forecasting, where you can dismantle the siloes where waste and cost gather. Indeed, EY recently suggested that digital twins could cut carbon emissions by up to half and costs by up to a third.

By implementing detailed digital twins, powered by AI and the scalability of cloud technologies, supply chain optimisation becomes more accurate, taking into account far more variables and inputs across the process. These might include lead times, demand, supply reliability, product quality, and yield, which taken together can produce a precise panorama of each product’s journey.

At the same time, cloud-based cognitive solutions can now imagine hundreds of scenarios automatically before ranking them according to business priorities, including sustainability priorities. AI can then select the ones which are most likely to produce the best business and environmental results. This richer information, available in minutes, supports a productive workforce and helps align corporate and green values.

The convergence of AI and cloud computing paves the way for a more sustainable future, without compromising profits. Incorporating environmental considerations alongside traditional supply chain goals will make future supply chains more resilient and adaptable. Thus, following years of upheaval, the correlation between profitability and environmental stewardship can be firmly established.