Predictive data analytics for solving food supply chain crisis
Predictive data analytics for solving food supply chain crisis

It’s easy for us to take many of our everyday essentials for granted, food included. Unfortunately, the world’s food supply chain is exceptionally volatile. Organizations and consumers depend on this crucial conduit for end products and raw materials, including food and beverages manufacturers, retailers, distributors, restaurants, and other businesses involved in the food industry.

In early 2020, the global pandemic broke the food supply chain as we once knew it. While food and beverage manufacturers and distributors faced their fair share of challenges and bottlenecks in the past, COVID-19 amplified those tenfold. Shutdowns and labor shortages significantly disrupted harvests, logistics, processing, transport, and sourcing procedures. Additionally, out-of-stock items doubled in value, imported meat prices rose by 16%, and retail food demands skyrocketed as consumers stockpiled items for the lockdown. To this day, those demands remain high.

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However, only 22% of organizations have a proactive supply chain network, even though this boosts visibility. Luckily, it’s not all bad news. Businesses can use predictive data analytics to spot potential supply chain issues before they occur and avoid downtime.

Implementing the right manufacturing analytics technologies has never been more paramount. Here are some of the most significant food supply chain problems manufacturers face and how capacity planning and data analytics can limit and eliminate downtime and drive ROI.

Top Four Food Supply Chain Challenges Modern Manufacturers Face

While much of the effects of the pandemic have subsided and the world is finally finding its footing, manufacturers are still facing big problems. 

Here are the top four issues the manufacturing industry is up against.

1. Labor Shortages

One of the biggest hurdles manufacturers must overcome is a massive industry labor shortage. There could be as many as 2.1 million unfulfilled manufacturing jobs by 2030.

The COVID-19 pandemic caused mass industry layoffs. Furthermore, millions of baby boomers—2.6 million, to be precise—have retired or are planning to. With a lack of qualified candidates, plants are struggling to fill their empty positions.

2. Shifting Demands

While consumer buying habits are constantly changing, the overall trajectory has only continued to rise since the global pandemic. The global market value is predicted to grow at a compound annual growth rate (CAGR) of 6.2% from now until 2027.

Manufacturers are struggling to keep pace. As such, foresight and early preparation are crucial to conquering this obstacle.

3. Capacity Constraints

A third challenge for modern manufacturers is distribution capacity constraints. Rising freight costs, port backups, trucker shortages, and more have caused this problem, which shows no signs of going away anytime soon. As a result, both consumers and companies have become frustrated with shipping and delivery delays.

It’s imperative for manufacturing organizations that oversee their own distribution to mitigate these logistical issues.

4. Transparency

Today’s consumers are more concerned about the origin of their food now than ever before. They expect crystal-clear brand transparency, both from retailers and manufacturers. Food safety and traceability are among the top focal points for risk mitigation by key decision-makers.

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How Data and Analytics Can Help Manufacturers Solve Food Supply Chain Challenge

Leveraging supply chain management software and data analytics is essential for overcoming food and beverage supply chain challenges. Data can help manufacturers maximize operational success, eliminate downtime, and see potential issues long before they can happen.

Data and analytics can help manufacturers overcome supply chain issues in the following ways:

Protecting and Attracting Employees

Advanced data analytics can help manufacturers attract and retain top talent while keeping workers safe. Today’s workforce embraces technology. Manufacturing plants that harness the power of the industrial internet of things (IIoT) are more likely to land tech-savvy applicants.

Manufacturing analytics also automates tedious tasks. This allows manufacturers to maximize employee and machine capacity, allowing employees to concentrate on more challenging duties.

Manufacturers can also better protect their teams by closely monitoring their data. This helps them stay on top of recurring areas where safety concerns might arise.

Using Predictive Data Analytics to Monitor Demand and Capacity

Modern manufacturers must be flexible. Capacity planning and forecasting data help manufacturers plan for the future by pinpointing potential capacity challenges and spikes in consumer demands. They can then plan for future resource bottlenecks, capacity constraints, and shifting demands. This allows manufacturers to balance supply with demand better, avoid truck capacity and port problems, and prevent downtime.

Data Analytics in Action

Many companies are using predictive data analytics to overcome food supply chain obstacles. Here are just a few examples.

Home Depot

Home improvement brand Home Depot saw an increase in empty shelves during the early days of the pandemic when DIYers were looking for home improvement projects to keep them busy during the lockdown. These empty shelves led to unhappy customers, and Home Depot needed better solutions to keep up with growing demands.

The company used what it calls an omnichannel algorithm that allowed it to unite consumer preferences with capacity, inventory availability, and assortment. This helped the brand to effectively meet customer needs while optimizing the use of its supply chain.

Seara

Across the world, Brazil-based meat supplier Seara was experiencing its own supply chain challenges that affected its daily operations. To combat these issues, the company launched its SuperAgroTech platform to integrate 9,000 growers seamlessly. Farmers could easily access digital data inputs and communications to monitor performance, animal health, environmental factors, profits, and social impacts.

Advanced Data Analytics for the Manufacturing Industry

Sightline EDM is the optimal solution for manufacturers to overcome supply chain problems. Our advanced software effortlessly integrates with your existing software and machinery, enabling you to uncover valuable insights in minutes. Use our solutions to better predict consumer demands, avoid downtime, and keep your employees safe. Discover the value of live data collection, clear visualizations, and real-time monitoring in keeping your organization nimble and responsive in a quickly-changing global marketplace.

Connect with the Sightline team today!

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