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Three reasons AI integration is the best tech option for supply chain companies

(Image credit: Image Credit: Geralt / Pixabay)

With artificial intelligence dominating the headlines, it’s easy for supply chain companies to feel like they must constantly chase the next big tool. But trying to keep up with the latest technology trends can be expensive and exhausting, especially if the technology doesn’t work with their supply chain systems. AI should be used to support supply chain operations rather than overhaul them at every turn. Instead of replacing processes every time a new platform emerges, focusing on AI integration offers a better path.

AI is integral to this new approach. Without it, companies are ill-equipped to identify supply chain problems and anticipate new opportunities. They’ll also be at a serious competitive disadvantage. Data is everything in the modern market because it can influence anything from the client experience to inventory decisions to shipment routes.

AI’s role in supply chains

According to MarketsandMarkets research, the supply chain analytics market is expected to hit $4.8 billion by 2019. And Grand View Research expects it to grow to $9.88 billion by 2025. There’s good reason for this growth. The sheer amount of data generated daily can help businesses streamline processes, forecast profits, and anticipate disruptions in related markets. Although some legacy analytics methods can bring visibility to supply chain data, they’re not agile enough to suit the current environment. These systems facilitate discussions about insights, but they don’t allow for real-time tracking of problems and strategies.

The new supply chain landscape necessitates a shift in how companies manage tech adoption. Businesses that ignore the opportunities inherent in AI will fall behind, and it’s unlikely that they will catch up. The technology stacks are constantly evolving and last for only a few years. Without using cutting-edge technology, even the most motivated and well-intentioned change makers in an organisation will have little impact as they deal with scalability and functionality issues of older codebase.

Supply chains are complex with interactions between internal and external systems, production and inventory, transportation and logistics, and supply and demand. The relationships between and impacts of these different interactions are very difficult for traditional systems. AI is capable of addressing supply chain companies’ rapidly expanding needs. AI can transform supply chain companies’ processes because it is able to quickly find patterns and provide visibility into what has long been an opaque process. Many organisations have dragged their feet on adoption due to internal silos and fears about liability. But those that integrate AI into their workflows find that they significantly increase their operational capacity and, therefore, improve their profitability.

Implementing AI integration

Today’s supply chain executives are short on time, and having multiple meetings to discuss solution implementation is a burden they can’t afford. Integrated AI tools provide actionable insights that eliminate bottlenecks and unlock real-time value. That’s important because supply chain companies need more execution — not more analysis.

Implementing a full AI solution might seem daunting and cost-prohibitive, and it’s true that costs can range from millions to tens of millions of dollars, depending on the size of the organisation. Businesses must first undergo a full digitisation process and then implement an analytics program before they can integrate AI tools. Oftentimes, companies waste significant resources in this process because they don’t incorporate the end user feedback and end up having to backtrack to address unanticipated problems.

But there is an alternative. An agile approach enables organisations to begin implementing AI in cost-effective ways. By integrating third-party vendors, they can start where they are, learn what works for their businesses, and scale up as needed. This tactic allows for much faster AI integration than building a new platform from the ground up or building on top of legacy solutions.

Here are some of the benefits associated with agile AI strategies:

1. Maximised data

Supply chain companies excel at managing the flow of goods and services, and legacy platforms were designed to handle the data associated with these processes. But because they were built before AI and machine learning, they’re not equipped for the demands of today’s supply chain industries. Newer platforms are built with technology stacks that can handle data capture, storage, processing, analysis, and visualisation, and they’re designed for quick integration. Rather than wait for legacy vendors to build machine learning algorithms into their platforms, supply chain companies can take advantage of new tools immediately.

2. Automated critical analyses

Supply chain operations are complex, and it’s difficult for a human to recognise patterns in inefficiencies, even with the aid of traditional business intelligence solutions. Operations teams can reduce the amount of time it takes to analyse data by leveraging AI tools. AI works 24/7, and its sole job is to analyse inputs and highlight trends. Analysts can use those insights to identify potential areas of improvement, forecast demand and inventory levels, schedule maintenance and downtime activities, and predict potential equipment failures.

As an example of how this is working in another industry, consider AI's role in agriculture. Weather forecasting and smart image processing enable growers to identify pests, weeds, and disease early on so they can protect healthy crops. Predictive analytics enable them to gauge how environmental factors will influence their crop yields, and real-time soil monitoring helps them adjust water levels to optimise growth. Supply chain companies can enjoy similar real-time and predictive benefits through AI solutions.

3. Enhanced competitiveness

AI is not just a nice-to-have; it's an imperative to stay competitive. These tools reduce processing time and facilitate smarter, faster decision-making. AI provides a view into market trends and even weather patterns that might impact operations, and that data can make all the difference in maintaining strong customer relationships and industry credibility. Having a view into when, where, and why bottlenecks occur can transform a company’s workflows and radically improve a supply chain company's profitability.

By partnering with third-party AI vendors, supply chain businesses can move away from the cumbersome old model of waiting for legacy platforms to catch up with new technologies. The most successful businesses will be those that apply scalable, easily integrated solutions to their existing processes.

Bhaskar Ballapragada, chief architect, ThroughPut (opens in new tab)
Image Credit: Geralt / Pixabay

Bhaskar Ballapragada is chief architect at ThroughPut Inc. Bhaskar leads product- and technology-related initiatives and helps companies detect, prioritize, and alleviate dynamic operational bottlenecks by applying machine learning algorithms.