How AI enables the cognitive supply chain

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Imagine a scenario where you have a critical client meeting and your flight is delayed due to aircraft maintenance and a lack of spare parts. Imagine another scenario where a manufacturing company cannot commit to an incremental business opportunity due to inflexible production lines. Or a promotion that results in a significantly lower uplift than estimated, leading to supply chain losses from excess inventory. The point is that supply chain-operations are far too slow to respond to changes in demand.

All of these scenarios impact market growth and cost. They drive the need to make faster and more effective decisions, drive seamless collaboration with supply chain partners, enhance real-time visibility of risks and opportunities, and create closed-loop adaptive planning. For this reason, supply chains must be highly responsive, agile, and flexible in order to meet the CXO's growth agenda.

The enterprise of the future

Technological advancements, such as the internet of things (IoT), cloud computing, big data, and artificial intelligence (AI), are able to dramatically empower supply chains. With the influx of data and access to digital technologies, supply chain management is at a new tipping point. It is now possible to capture, store, process, and share data in real-time to make faster and more effective decisions.

To survive and thrive in a world where change is constant, enterprises have to evolve in a different way. They have to approach issues within the sphere of the organization – and they have to do so instinctively.

The future of business is the instinctive enterprise, with AI at its core, which bridges the interrelation between people, processes, and domain knowledge. The instinctive enterprise uses digital technologies with internal and external data to spot patterns, create predictive insights, and act before others see what's coming. It breaks down silos and embraces partnerships, even with competitors, to become agile and improve customer experiences. And it empowers its employees with technology while creating fluid, purpose-driven career paths.

The instinctive enterprise has a supply chain that anticipates rather than reacts to changes in demand and it collaborates with suppliers across the supply chain, supported by an agile workforce. We call this the cognitive supply chain.

Enterprises also need an ecosystem of connected technologies to propel the transition to a cognitive supply chain. AI and other digital technologies enable the transition to a cognitive supply chain by augmenting and automating processes. They:

  • Integrate unstructured data and new data sources, using ML with unstructured data to drive superior performance
  • Perform tasks faster and more reliably – for example, driving higher case-fill rates by using ML to accelerate root cause analysis
  • Enable smarter and faster decisions – for example, an AI-based dynamic routing system can analyse real time status of shipments, delays, and traffic conditions to suggest routing changes
  • Recommend actions based on impactful insights – for example, an AI-based intelligent alert system can drive real-time actions to enhance on-time, in-full orders, and thereby reduce retailer penalties
  • Provide remote monitoring and diagnostics, such as using ML when interpreting signals from airplane systems to alert maintenance crews in advance of any issues

Technology adoption is a foundational element of a cognitive supply chain that supports enterprise growth.

New operating models demand an adaptive workforce

Enterprises need new operating models with centers of excellence (CoEs) that cultivate talent and provide scale to drive cost, service, and working capital management. To leverage the power of a cognitive supply chain, enterprises must have an adaptive workforce.

Talent working with cognitive supply chains will develop greater domain, data science, and digital expertise. Planners will no longer be limited to simply interpreting outputs from planning applications or exception management. They will interact more across several functions, such as finance, sales, manufacturing, warehousing, transportation, and so on.

As roles in supply chains start to merge, planners must equip themselves with end-to-end supply chain knowledge. An adaptive workforce will look at problems more holistically and strategically, solving problems that are no longer myopic in nature but span across the supply chain value network.

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The move to an autonomous supply chain

With more enterprises embracing AI and the expeditious evolution of digital solutions, we can envision components of a completely autonomous supply chain. Two current examples include transformation driven by autonomous vehicles and blockchain technology:

  1. Autonomous fleets and material handling
    • Vision-guided fully autonomous mobile robots are optimizing and eliminating the manual movement of material from one location to another. These robots are approximately four times more productive and faster than their human counterparts.
    • Semi-autonomous/autonomous trucks can coordinate their movements to travel as a platoon, remaining close together over long stretches of highway. As autonomous vehicles become more widespread, these platoons are projected to cut fuel costs by close to 20%.
    • Autonomous “ghost ships", ships without crews, will be in operation in the next few years and will initially ferry products short distances. For example, Rolls-Royce has already announced plans to launch autonomous cargo ships by 2030.
    • Drones, robots, and autonomous cars will transform last-mile delivery. Ecommerce giants are very excited with the prospects of drones making deliveries. Meanwhile, food retailers are already trialling robots and autonomous cars are delivering fresh hot orders to consumers.
  2. Safe, smart, and efficient exchange through blockchain: Enterprises expect blockchain to have the widest reach and impact on material, financial, and transaction visibility, as well as substantial impact on customer experience. For example, a large global manufacturer is using blockchain to track details from the genesis of a customer order to its purchase orders to tier two and three suppliers of raw materials. The result is unprecedented real-time visibility into material and data, with access by all associated parties.

    Blockchain will also allow consumers and food safety regulators to track the history of the product placed on the shelf at retail stores – right from the source of produce, with automated handoffs record-keeping across the supply chain, lessening errors and providing visibility and value additions made at each step, even how well (or badly) the product was handled during shipment.

The significance of a cognitive supply chain is clear. It enables employees to foresee issues associated with supply and demand, and deal with these problems in a much more strategic manner. This empowers an instinctive enterprise to stay ahead of the competition. What's more, through management of a connected ecosystem and nurturing of an agile workforce, this not only supports business growth, but it also encourages improved ways for technology and insights to work together.

This article was authored by Shantanu Ghosh, global business leader, enterprise services & consulting at Genpact. 

This article was first published in Financial Director in July 2018.