Supply chains are a complex and significant function especially in retail.
Ensuring the availability of the right products at the right time and at the right place requires complex processes that need to be constantly tuned. Any failure to do so results in in-store shortages as has been observed during calamities, both natural and man-made.
Even though it is generally possible to tune designed processes to near perfection, external and unforeseen events like pandemics (COVID-19), and trade route disruptions (Suez Canal blockage) have derailed the smooth functioning of supply chains. Over the years, organisations have used in-house human-centric expertise to recover from such disruption based on past experiences and learnings. However, with recent advancements in artificial intelligence (AI), retailers can use hybrid intelligence (HI)–human and artificial intelligence working in synergy–to overcome these challenges. Hybrid intelligence can help supply chain teams in retail overcome, or at least minimize, the impact of trade disruptions.
While the use of AI in supply chains is still in early stages, the complexity of the processes and the dynamic nature of the sub-functions offer a perfect space to consider the induction of hybrid Intelligence.
Before we dive into the application of hybrid intelligence in supply chain, here’s a quick look at its maturity model. We have identified five stages, each with unique characteristics, that can help improve the supply chain process with AI.
The hybrid intelligence maturity model offers a strategic lens to assess and advance the AI capabilities for retailers looking to transform supply chains.
The AI value wheel demonstrates the use-cases in these five stages of hybrid intelligence.
Action on the five-step framework: Managers can begin with automating routine tasks like workforce allocation and dock assignments using assisted intelligence to boost efficiency. In the augmented stage, AI can help enhance decision-making in areas such as demand forecasting, improving storage utilisation, and eventually move to collaboration and more complex tasks such as co-creating solutions for various challenges ranging from optimizing slotting to managing supply chain transparency. In the advanced stages, we foresee systems that are adaptive, autonomous and context-aware, dynamically adjusting pricing, inventory, and delivery routes in real time all the way to self-operating supply chains.
For optimal results, retailers must evaluate the processes and ensure effective implementation of AI for supply chain.
Here are a few considerations to achieve success:
The AI value quadrant is a powerful and intuitive tool for prioritising and allocating resources.
The horizontal axis of the quadrant charts feasibility to measure the relative ease of execution, while the vertical axis–business value--qualifies the potential impact of a business value. The quadrant also has two additional dimensions--time to market and time to value, which help project viability evaluation.
Here's a three-step method to ensure better actionable insights using the quadrant:
The top right corner represents the low-hanging fruit, the areas that can quickly adopt technological inventions and are ideal for a quick pilot project. This exercise can help retailers create a phased road map.
The hybrid intelligence-first supply chain approach, powered by AI value quadrant matrix and AI value wheel, is a strategic framework designed to transform traditional retail supply chains into intelligent, adaptive ecosystems. At its core, this methodology focuses on identifying, evaluating, and prioritising AI use cases that deliver measurable business value.
While the approach is conceptually straightforward, its application involves significant challenges.
Some of these include:
Prioritise and go
The journey toward a human-centred AI supply chain is as much about adopting technology as it is about reimagining the way people and machines collaborate to solve complex challenges. Embracing hybrid intelligence can help retailers unlock agility, precision, and resilience across their supply chain operations. As organisations move through the maturity stages of assisted, augmented, collaborative, adaptive, and autonomous intelligence, they gain the ability to shift from reactive problem-solving to proactive orchestration. Going forward, this can help organisations prioritise what matters most, accelerate what works, and build an intelligent, human-centred, scalable, and future-ready supply chain.