Building Smarter Supply Chains with AI – Part I

March 7, 2021

The global market for artificial intelligence in supply chain is expected to grow at a compound annual growth rate (CAGR) of 39.4% from 2019 to reach $21.8 billion by 2027.

More than ever, businesses are recognizing the need for solutions that allow them to be resilient in the face of uncertainty and proactive when anticipating future trends. Unsurprisingly, this has caused accelerated adoption of AI-based supply chain solutions to mitigate disruptions, drive agility, and maintain business continuity. A recent survey by MHI showed that nearly 60% of supply chain professionals anticipate that their departments will rely on artificial intelligence in some manner by 2025.

Supply chains are comprised of multiple actors that rely on tremendous amounts of data to ensure smooth production and transfer of goods from manufacturer to customer. Businesses are continuously turning to AI-powered analytics to understand and forecast demand patterns; streamline inventory and order fulfillment; enhance visibility and coordination within the supply chain to predict and prevent risks; and  discover new opportunities for cost savings.

Artificial intelligence opens limitless possibilities for supply chain enhancement. This two-part article focuses on  transformational use cases that can help organizations build future-ready, intelligent supply chains. This list is by no means exhaustive; it is important to remember that  use cases  may vary based on the industry or specific business challenges. As a member of the Scale AI community, Adastra welcomes innovative ideas for AI application in supply chains that can help secure funding for eligible projects.

Smart Supply Chain Predictions and Planning

While it cannot always forecast ‘black swan’ events like the COVID-19 pandemic, AI can provide significant rapid response capabilities for various kinds of anomalous events. For example, AI can be used by  Adaptive Neural Network-based Flight Control to take over piloting to stabilize a damaged aircraft. AI can also be used to quickly respond to and initiate damage control in the event of a supply chain disruption.

The year 2020 proved that uncertain market conditions can seriously impact consumer demand. Despite the pandemic, market dynamics continue to change.  rapidly Because of this, demand forecasts based on historical trends and patterns often fall short of the real picture.

Machine Learning solutions can analyze new sources of data to sense demand changes and allow businesses to proactively plan and intelligently optimize their demand and supply forecasts. Demand planning processes can be made smarter with predictive Machine Learning-based algorithms that can create forecasts at product or store level for different periods. Moreover, these solutions can incorporate data attributes like competitor pricing, store traffic, and weather to make demand forecasts more accurate. With smarter planning, organizations can seize new demand opportunities, leaving their competitors to play catch up.

However, fast, accurate, and quickly-adaptable supply and demand forecasts are only few of the benefits that AI can provide for inventory management. There are many other challenges where AI can play a crucial role. For example, improved inventory management can not only decrease storage and scrap-related costs, but can also ensure that your business minimizes stock-outs and is always prepared to meet changing demands.

Additionally, supply chain leaders have replaced manual data collection with AI-enabled automated workflows. This has accelerated time-to-insights, minimized resource utilization, and alleviated human error risks  in  forecast planning.

Overall, Machine Learning can predict future supplier interactions based on historical deliveries, delays, and accidents; and allow for improved supplier selection.

Logistics Planning and Optimization

Disruptions and delays in supply chain logistics come at a heavy price to the business. Even small delays can mean empty shelves, lost customers, unhappy channel partners, or all of the above. However, most supply chains have multiple moving parts, and disruptions are often difficult to predict and mitigate.

With AI, organizations can leverage the power of data to predict and plan for future disruptions. Organizations already use AI solutions to connect the dots between their logistics and different data sources ( weather, flight logs, traffic, etc.) to predict delays, identify next-best actions and respond quickly to mitigate disruptions.

AI and optimization models can  help design better supply chain networks to reduce delivery costs, increase efficiencies and reduce shipping delays. AI-enabled solutions help reduce logistics costs for businesses with instant shipping quotes that reflect current market rates.

For organizations that manage their own fleets, AI-based fleet management solutions can analyze copious amounts of real-time data and provide analytical insights for more efficient transportation management. In some industries, drones could soon become an important part of the supply chain . A combination of truck and drone delivery – together with the management and predictive capabilities of AI – will minimize downtime and speed up deliveries in urban environments.

Shipment damage can jeopardize profits Advanced AI solutions can automatically determine the likelihood and expected amount of potential shipping damages based on past behavior and shipping conditions. This predictive solution allows  organizations to  account for damages in the overall cost.

As a leading player in the data and analytics industry, Adastra designs and builds customized AI solutions to enhance the efficiency and predictability of your supply chain. Our experts work in close collaboration with your team to understand your specific  challenges and objectives to create tailored solutions that will provide you with a winning edge. We leverage our deep technical expertise – coupled with two decades of academic and industry experience – to create valuable, specialized solutions geared towards your particular use case.

When it comes to the possibilities of using AI to transform supply chains, these use cases are just the beginning. AI can also play a key role in improving supply chain transparency; strengthening collaboration with suppliers and vendors; and in ensuring safe and efficient storage and organization. These use cases will be covered in our next blog. Stay tuned!