“A whopping 85% of consumers are willing to change their purchasing habits to positively impact the environment, according to a recent study by Deloitte.”

In a world propelled by innovation, businesses are redefining the landscape of sustainability.

From the manufacturing floor to the consumer's doorstep, industries are revolutionising their supply chains. In this blog, we'll unravel the transformative impact of cutting-edge supply chain technologies like blockchain, AI, and ML, as they not only streamline operations but become catalysts for a more sustainable future.

‍

How can businesses build sustainable supply chains?

‍1.  Reducing Wastages: Unlocking Precision with Predictive Analytics

‍The food and beverage industry grapples with significant food wastage due to inaccurate demand forecasting. The perishable and short shelf life nature of products requires real time accurate predictions that are comprehensive of the changing market conditions. Manual planning processes fail to capture this effectively. 

AI's predictive analytics, however, dives deep into historical data, and other external factors like seasonality, cyclicity, pricing changes, marketing promotions, holiday and weather enabling precise demand predictions. 

“According to a study by the World Wildlife Fund, AI-driven demand forecasting can cut food waste by up to 20%.”

This not only optimises production but curtails overstock, reducing food wastage. 

‍‍

2.  Responsible Sourcing: A Transparent Journey with Blockchain

The cosmetics and apparel industries face challenges related to responsible sourcing and ethical production. Poor traceability into sourcing has often led to difficulties when there are unfortunate quality concerns with certain batches of products. 

Blockchain revolutionises the supply chain by providing an immutable and transparent ledger of a product's journey from raw materials to the end consumer. 

“A report by Statista indicates that 33% of consumers are willing to pay more for brands with transparent and sustainable practices.” This technology fosters trust and aligns with consumer preferences for sustainability.

Supply chain automation software also helps screen multiple vendors based on crucial factors like price, lead time, fill rate etc making the evaluation process seamless. This helps in identifying those vendors that align with the business needs in real time. ‍

3.  Embracing Collaboration: Streamlining Communication with AI

‍Businesses often grapple with communication gaps among stakeholders leading to siloed processes and poor coordination. AI-driven communication platforms enhance coordination between manufacturers, suppliers, and distributors. This collaborative approach not only reduces delays but also optimizes resources, contributing to a more streamlined supply chain.

Inventory imbalances often occur as a result of lack of effective communication between the marketing and operations departments. AI bridges that gap by providing a platform where marketers and ops folks can collaborate for seamless execution of sales promotions. It also enables collaboration between decision makers and executives; stakeholders within the same department.‍

4.  Good Storage Practices & Management: Precision Inventory Control with ML

In the Retail and E-commerce sector, excess stock can lead to environmental impact and financial losses. Dead stock increases storage costs and ties up the working capital that can be used for other value adding activities. This also is an indicator of poor sales performance and  low inventory turns. 

Machine Learning algorithms analyse historical data to predict demand patterns, continuously optimising inventory levels. 

“A study by McKinsey found that ML-based inventory management can lead to a 20-50% reduction in forecast errors, preventing overstock and improving sustainability.”

They also give proactive alerts on excessive inventory and suggest optimal prices at which this stock can be liquidated. ‍

5.  Streamlining Logistics: Fueling Efficiency with AI

Q commerce companies and Restaurants often face challenges in timely deliveries due to inefficient logistics. AI optimises transportation routes, enhancing fuel efficiency and reducing emissions. 

“The European Environmental Agency estimates that AI-driven logistics optimisation can reduce greenhouse gas emissions in the transport sector by 10-15%, contributing to a greener supply chain.”

Companies also struggle with truck space constraints and often end up overestimating or underestimating the replenishment quantities.

AI tools help optimise truck loads to align with the maximum truck and corresponding warehouse capacities. 

‍

5 Key Takeaways

1. AI's Role in Predictive Analytics: Harness the power of AI-driven predictive analytics to optimise production and reduce wastages.
2. Blockchain for Responsible Sourcing: Utilise blockchain for transparent and traceable supply chains, especially in industries where raw material origins are crucial.
3. Collaboration through AI: Foster collaboration among stakeholders using AI-driven communication platforms to enhance coordination and reduce delays.
4. ML's Impact on Inventory Management: Implement Machine Learning for precise inventory management, reducing forecast errors and minimising overstock.
5. Efficient Transportation with AI: Leverage AI to optimise transportation routes, leading to fuel efficiency and a significant reduction in carbon emissions in logistics.

In today’s world, supply chains are stepping up to lead the way in sustainability. Through tools like predictive analytics, blockchain, and AI, businesses are reducing waste, ensuring responsible sourcing, and optimising collaboration. Machine Learning refines inventory management, while AI streamlines logistics, reducing environmental impact.

This isn't just a transformation, it's a commitment to a greener future. Technology isn't just a helper, it's the driving force behind a promise for a more sustainable tomorrow.