More Than Just Hype: 4 Ways to Use AI to Optimize Supply Chains

Supply chains are rapidly becoming digitized, though, they’re not yet as advanced as they could be.

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Supply chains are rapidly becoming digitized, though, they’re not yet as advanced as they could be.

A shift from historical manual data analytics to artificial intelligence-powered mechanisms will not only find and fix issues proactively, but it will also give you powerful end-to-end supply chain visibility. Artificial intelligence (AI) intercepts "unpredictable" issues and turns them on their heads to effect enhanced outcomes.

Until recently, the industry has shied away from technologies such as artificial intelligence and machine learning. These technologies offer a means to break through supply chain bottlenecks, reduce inefficiencies and enhance throughput.

Obstacles to Adoption

Supply chain decision makers face mounting pressure to improve their forecasts. However, one survey found that 43 percent of surveyed retail supply chain professionals were hindered by their current tools that can’t keep up with changing industry standards.

Yet many decision makers are reluctant to embrace more advanced tools because they’re uncertain how they would be incorporated and whether they can be trusted. Others might feel overwhelmed regarding where to begin with AI and are scared off by the cost of hiring data scientists.

However, you must consider the returns you’ll achieve with this technology.

Many new programs are designed to be intuitive and secure, so you can reduce processing times and boost throughput quickly once you’ve implemented them.

AI also facilitates a sequential review that gets to the heart of your forecasting and processing issues. A smart platform can help you investigate where and why bottlenecks occur, as well as why you’re losing revenue at a given point in the workflow.

End-to-end supply chain visibility and the power to intercept previously unpredictable issues will mean nothing but gains for your company.

Stop Solving the Wrong Problems

Decision makers often suffer "analysis paralysis" because they don’t know which problems to solve. A smart program will run constant algorithms to pinpoint exactly where inefficiencies crop up, enabling you to direct your resources where they’re most needed. Running these analyses manually can take years and millions of dollars that might be more wisely invested.

Maximizing throughput is a key concern across the supply chain industry, and emerging technologies are critical for achieving that. You must be bold enough to try unorthodox methods if you want to take the lead in this area. You will need to abandon cost-centric analyses for time-centric paradigms if you really want to remove bottlenecks and drive better results.

There’s another reason to embrace advanced technologies, and that is the talent acquisition crisis that's plaguing the supply chain industry. The Leadership Network reported that there is a 61 percent shortage in middle-management decision-making. Therefore, it’s all the more important that you leverage technology that provides real-time, accurate insights. AI and machine learning support you in prioritizing your concerns, calculating system waste and identifying areas that are ripe for automation.

Implement AI Effectively

Manufacturers are moving toward more tech-driven strategies, with 60 percent of manufacturers studied by the IDC saying they’ll implement analytics platforms. However, Gartner predicts that three out of five factory-level AI initiatives will stall, largely because of a lack of skills.

The path forward must involve automated solutions that your company can integrate into its current workflows without incurring substantial adoption costs. By selecting a platform that can assess all of your relevant metrics — such as transportation costs, expenses associated with various product lines, raw material data and other key data points — you get a comprehensive overview of your processes. Using a smart supply chain assessment platform can increase data preparation and analysis speeds by a factor of 10 and lead to millions of dollars in savings on stock management.

Here’s how to make AI work for you in practice:

1. Use inventory stock-keeping unit data to build predictive models.

You can achieve 95 percent accuracy in stocking decisions and tag slow-moving or specialty stock for trade-off analyses via AI. This helps you understand where your dollars are tied up in real time so you can improve warehouse load balance and stocking levels.

2. Leverage machine run time and worker logs to optimize planning.

This enables you to more efficiently schedule equipment maintenance, safety meetings and worker trainings.

3. Apply sales and operations planning data to improve accuracy.

Doing so provides a more accurate picture of external demands, allowing you to prevent the company from stocking excess products and raw materials.

4. Forecast capital expenditure needs.

AI will be able to project your expenses based on under- or overutilized assets within your warehouses, factories, rig and site environments.

Artificial intelligence represents the next evolution of the supply chain industry, and it's a transformation that's coming on fast. Supply chain vendors must embrace new technologies that increase their speed and reduce expenses, and AI is at the forefront of that.