Top 5 Digital Factors Influencing Supply Chain Performance

1

Shift from Demand Planning to Demand Sensing

Today, due to frequent last-minute adjustments in logistics, forecasting demand is a big challenge. Siloed operations across supply chains result in knowledge gaps across upstream and downstream activities. This causes major discrepancies in inventory reconciliation, making it hard to ensure enough stock is available to meet demand and prevent stock-outs.

Machine learning takes demand sensing to the next level by enhancing real-time information by aggregating data from multiple internal and external sources, including the use of demographics, weather, online reviews and even social media (e.g., brand mentions). ML can also improve forecasting for new products being introduced, which lack historical data, by identifying trends from similar products and using that data to make better predictions.

Traditional inventory forecasting relies primarily on historical data. But with advanced, tech-enabled demand forecasting for supply chain management, companies can forecast demand more accurately, optimize inventory levels efficiently and replenish accordingly. Tech-enabled demand forecasting, sensing and planning can reduce supply chain errors by 30% to 50%.

2

AI-Enabled Decision-Making

Considering both internal and external factors for business decision-making is complex, tedious and error-prone. Technology options help businesses understand complex information and enhance human performance by taking over time-consuming, routine tasks. However, complex scenarios and cross-operational approaches are still manual and individual-centric.

AI enables more visibility and integration across networks, which allows brands to expand their supply chain while keeping everything streamlined. Further, it applies algorithms to detect patterns, trends and gaps across an entire supply chain – leveraging vast cross-operational data lakes, providing insights to enable better and faster decision-making.

The transportation and logistics industry stands to gain 89% incremental value over time through AI adoption. A recent study showed that 61% of executives reported reduced costs and 53% stated they saw an increase in revenues after implementing AI in their supply chains.

3

Optimized Shipping with Hyper-Automation

With complexities and intensive manual decision-making, shipping often gets the least attention for investment opportunities. Optimizing a shipping strategy to save costs while meeting customer expectations is challenging, with a variety of shipping options and methods to choose from.

AI-enabled hyper-automated shipping solutions take the complexity out of shipping by automatically putting customer orders that need to be fulfilled in a queue and eliminating some of the manual tasks involved. Shipping technology can be as intricate as the use of robots or as simple as adding a layer of software or installing infrastructure like advanced conveyor belts.

Significant investments back the development of self-driving trucks (currently in beta) to improve last-mile delivery.

4

Robotics in Warehouse Operations

Without implementing technology of any kind, it’s a challenge to maintain a high order accuracy rate (between 95%-98%) when managing a high volume of orders. Order picking can account for 50% or more of warehouse labor costs, and it leaves less room for warehouse staff to focus on improvements and implementation of new processes.

Advances in supply chain technology continue to cut out time-consuming, manual tasks that are prone to human error. For instance, warehouse robotics are designed to minimize mistakes by picking, packing and sorting orders based on accurate data. By combining technologies like AI, ML and predictive analytics, businesses can automate warehouse operations, improve delivery times, efficiently manage inventory, optimize third-party communication, and create new customer experiences that increase satisfaction and boost sales.

Implementing robotics to cut down on the manual labor and time spent on order fulfillment (e.g., physically moving products from one side of a fulfillment center to another) frees up logistics teams to focus on more complicated processes, such as packaging innovations and workflows.

5

Ensuring Information Security with Digital Measures

With global e-commerce sales expected to reach $4.89 trillion by the end of this year, supply chain security continues to be a top concern. Expansive supply chains are a prime target for cyberattacks due to the interconnected nature of supply chain ecosystems and the data sharing required. Regardless of whose information is being exposed, cyberattacks can cause major security breaches throughout the supply chain, putting customer data at risk.

Modern security technology reduces risk and enhances data protection. Encryption, tokenization, on-demand access and automatic alerts are all security enhancements that should be used within modern supply chains.