AI-Powered Fulfillment and Distribution

The modern retail and CG supply chain must be smart and nimble. It is imperative that it reacts to changing market conditions on the fly to ensure product is where it needs to be when it needs to be there. In addition, it needs to be capable of not only moving large-scale orders destined for warehouse, DCs, and stores, but also single orders to fulfill individual consumer orders.

To make this intelligent supply chain a reality, retailers and CGs are equipping their supply lines with AI/ML solutions that take humans out of the decision-making process and automate operational shifts. CGs and retailers were asked the main benefits (up to three) an organization can expect from an AI/ML-powered supply chain and 70% said automating and improving planning and execution — a clear necessity in today’s in-flux market. More than half of respondents named automating physical processes for distribution and logistics (56%) and improving agility/responsiveness to changing demand as other key benefits.

With these game-changing benefits, what is stopping every retailer and CG from investing heavily in AI/ML for their supply chains? The simple answer is budget. Sixty-seven percent named budget concerns as a main challenge to broader AI/ML adoption. Other key challenges holding companies back from wide-spread AI/ML use include lack of expertise (52%), unclear ROI (44%), and the absence of a capable IT or data infrastructure (44%).

While the benefits of leveraging artificial intelligence and machine learning in the supply chain are plentiful for both retailers and CGs, most organizations rank themselves as trailing the competition in terms of AI/ML maturity. In fact, 67% report that they are lagging the competition in the use of AI/ML, with just 4% of those surveyed bestowing a “leading” grade on their efforts.

With such a gap between internal capabilities and the perceived capabilities of the competition, retailers and CGs have a keen interest in bolstering their AI-powered prowess. As they look to improve their capabilities, 26% report they are working with solution provider partners. Another 22% are looking to acquire the systems and solutions they require, and 11% are using a hybrid approach of internal and external sources. Just 4% are building the internal capabilities needed to deliver AI-based solutions.

While the source of new AI/ML supply chain solutions varies by company, nearly three-quarters (71%) place the IT department as primarily responsible for development, implementation, and acquiring these new capabilities. Twenty-five percent of respondents report that this responsibility lies with the supply chain department, and just 4% have a dedicated AI/ML business unit.

AI/ML is the future of the supply chain, and that future is going to arrive very quickly. Currently, AI/ML maturity is still in its relative infancy, but it looks to scale significantly over the next two years.

Today, retailers and CGs are up-to-date or currently upgrading their AI/ML-powered fulfillment (23%), demand planning/forecasting (22%), and drop-ship management (19%) capabilities. Over the next 12 months 30% of retailers and CGs report they will invest in AI/ML-infused replenishment, transportation management, and demand planning/forecasting technology.

When the timeline is stretched to 24 months, around 1 in 3 will invest in replenishment, and 1 in 4 will upgrade their transportation management capabilities.

There is significant investment planned in the AI/ML-driven supply chain over the next 12 to 24 months; however, retailers and CGs report that their DC/fulfillment operations are already leveraging the technology at elevated levels. In fact, 33% are deploying the technology for non-robotic, material-handling, 26% for vision recognition for inventory, and 26% for predictive labor planning.

On the horizon for retailers’ and CGs’ DC/fulfillment operations over the next year are AI/ML enhancements to process optimization and orchestration (30%) and predictive labor planning and management (15%).  

Within the next two years, a significant number of survey respondents expect to upgrade their predictive inventory planning (37%), predictive labor planning (30%), and robotic systems for picking and material handling (26%).

Methodology

This study was conducted in April and May 2021. The survey was sent to retail and CG executives at both large-scale and SMB chains and manufacturers. Two-thirds of respondents (67%) self-identified as retailers, with the remaining 33% coming from the consumer goods side of the house.

Seventy-eight percent of respondents are director-level or above, with 30% holding C-suite titles. Forty-one percent of those surveyed are employed at brands with revenue north of $500 million.

The respondent pool hails from across the industry, with the highest concentration of retailers working in specialty retail (47%), while the biggest group of CG are employed at manufacturers that serve the mass, grocery, convenience, drug and dollar markets (71%). Forty percent of all survey takers work in IT/technology.

Conclusion

Artificial intelligence and machine learning are powerful elements of the retail and CG tool kits as they look to build the supply chain of the future. Currently, the technology is being leveraged to effectively predict demand and execute delivery quickly, seamlessly, and economically.

The technology’s role is poised to increase throughout the supply chain in the near future. Look for industry leaders to invest heavily in the deployment of AI/ML in key operational areas like replenishment, transportation management, process optimization and orchestration, inventory planning, labor planning, and distributed order management.

Key Takeaways

• 70% of CGs and retailers named automating and improving planning and execution as a main benefit of implementing AI/ML in the supply chain.
• Budget concerns are the main challenge to broader AI/ML adoption, according to 67% of respondents.
• Only 4% of retailers and CGs have a dedicated AI/ML business unit.
• Over the next 12 months, 30% of retailers and CGs will invest in AI/ML-infused replenishment, transportation management, and demand planning/forecasting technology.
• 67% self-report as lagging the competition on the use of AI/ML, with just 4% granting themselves a leading grade.
• Retailers and CGs expect to supercharge warehouse/DC operations with AI/ML investments in predictive inventory planning (37%), predictive labor planning (30%), and robotic systems for picking and material handling (26%) in 24 months.