Increasing the scale of AI in the supply chain to boost intelligence

The explosion of demands pressuring the supply chain

Supply networks can no longer operate "business as usual." The supply chains of businesses are under a lot of pressure to handle a variety of new issues and goals that, in many cases, existing supply chain skills are unable to handle as a result of a convergence of variables.

The majority of current supply chains were developed for an earlier era, when scale was attained by transporting large truckloads of products to warehouses and big-box retailers. This strategy prioritized efficiency above resiliency and depended on a high degree of demand predictability (making visibility less crucial). This approach needs to alter, but how, given the disruption of supply chains everywhere? 

Data and artificial intelligence (AI) are at the center of this change because they are ideally positioned to give businesses the insights, agility, and speed they need to create a fundamentally new supply chain that is suitable for today, tomorrow, and years to come.

Creating smarter supply chain network

A connected and fully intelligent supply chain network can be developed by businesses that can put data at the center of their supply chain and use AI at scale.

Companies can gain from an intelligent supply chain network in a variety of ways.

• They can use it to get visibility into sudden changes in demand or supply, which will provide them the knowledge they need to address problems very immediately.
• By enhancing agility, businesses may more quickly, precisely, and efficiently meet the demands of diverse customers. This improves product availability and service levels, lowers the cost of lost sales and inventory, and boosts production and fulfillment effectiveness.
• It can lower businesses' carbon footprint and overall sustainability risk while increasing robustness (e.g., maintaining On Time and In Full service criteria).

A high-level description of an intelligent supply chain is provided below.

Supply chain AI and data to grasp challenges

Despite acknowledging the strength and utility of data and AI, businesses will probably still have trouble expanding the impact of their investments. In fact, a whopping 79% of COOs admit they are able to pilot AI but find it difficult to scale it throughout the entire organization.

Overcoming difficulties to have a better impact

1.Strategy and goal: fix your objectives and how to get there

A corporation requires a clear and comprehensive vision of where it wants to go with AI—its North Star, so to speak—in order for it to have an influence on a big scale. Scaling cannot be restricted to a single department, function, or business unit. The capacity to translate this vision into the significant actions the business must lead to realize the end result is also crucial. Both are essential to taking the next steps to lay the groundwork for a business to realize both short- and long-term benefit from AI, as well as, critically, to gain C-level support for funding such a mega-investment.

2. Master your data to get a trustworthy and unique source of truth

For improved supply chain visibility, AI and advanced analytics can analyze enormous and varied data volumes from all operations. But as data sources increase, more computing power and server space will be  required. A business can connect these facts via the cloud to produce a solitary, reliable source of truth. The cloud enables businesses to access fresh data sources, expand their visibility, and increase the potential for AI to add value.

3. Talent: acquiring and developing the appropriate skills

As was already said, many businesses discover that they lack the necessary talent to scale the usage of AI in supply chains. In reality, according to Accenture data, only 38% of supply chain leaders believe their employees are prepared to use the technologies at their disposal. Therefore, it is extremely essential for the scalability of AI to upskill or reskill people so that they are adept at applying AI to specific use cases that provide considerable value.

In addition to being excellent sources of crucial expertise, ecosystem partners like technology providers and consulting firms can also provide talent that can supplement an organization's current workforce when necessary. These businesses have previously undergone the challenging learning curve necessary to scale AI and absorbed the lessons. Their advice and insights can be very helpful in assisting businesses with what is frequently a challenging and complex undertaking.

Toward smarter and self controlled supply chain networks

Any company's supply chain can gain significantly from the combination and scaling of intelligent technologies and connected end-to-end data. The combination streamlines the supply chain, develops new operational skills and efficiency, and frees up cash to reinvest in fresh business models that improve client experiences, fortify competitive advantage, and foster profitable growth.

Longer term, this potent confluence of technology and data will drive a transition toward supply chain networks that are really self-driving, elevating value and innovation to a whole new level.

Demand, supply, inventory optimization, and execution can all be automated with AI, with an emphasis on making choices automatically and without human involvement (i.e., a shift from humans driving the machines to machines guided by the humans). A supply chain's performance may be automatically predicted, prescribed, and optimized across functions thanks to machine learning (ML). Automation may also identify and address exceptions in a self-driving supply chain; for instance, ML-based algorithms can forecast exceptions and supply chain outcomes, and cognitive computing learns and adjusts as a process evolves over time.

Any supply chain might be transformed by AI, and in the current context, such a change is no longer a choice. Companies can scale AI and cease piloting it with the proper mix of people, procedures, and technology, allowing the supply chain network to start realizing its full potential value over the medium and long term.

In conclusion, artificial intelligence has revolutionized the supply chain industry, allowing for more efficient, accurate, and faster data analysis and decision-making. AI has enabled companies to automate and streamline their operations, reducing costs and increasing customer satisfaction. AI also helps companies to optimize their supply chain strategies, reduce wastage and improve operational efficiency. AI is still in its early stages and there are still many advancements to be made, but it is clear that AI is quickly becoming an essential part of the modern supply chain.