Retailers are investing in the latest analytics technology such as AI & machine learning in their supply chain to help manage an increasingly costly, complicated, and inefficient system.
Today’s reality is that most companies (95%) are projected to fail at equipping end-to-end supply chain resilience by 2026, according to Gartner.
Supply chain ties to overseas countries such as China and India mean increased uncertainty brought on by unpredictable factors – weather events, geopolitics, partnership compliance, and so on.
Investing in sustainable supply chains is the only way retailers can realistically stay in the game.
A technology which has been revolutionary in predicting demand and streamlining inventory flow has been machine learning in retail analytics.
What is machine learning? How can it be used in the supply chain? And Why is it so revolutionary?
What is Machine Learning?
Machine Learning (ML) is a type of AI that can make intelligent decisions without external instruction.
Here’s how it works,
ML uses algorithms and statistical models to learn from data, identify patterns, and then make decisions or even predictions without additional manual input.
This technology is being harnessed in every industry from education to medicine, and of course retail.
How can machine learning improve retail supply chains?
ML has become indispensable for supply chain management delivering immediate and tangible benefits.
Retailers surveyed by Gartner ranked ML among the top 3 disruptive technologies in the supply chain, alongside Big Data Analytics and AI in general.
Let’s dig a little deeper into some compelling reasons why retailers should consider using machine learning in their supply chain operations.
- Improved demand forecasting
The typical retailer is overwhelmed by data, which can not be efficiently analyzed.
Opportunities are left on the table, and problems are missed due to ineffective forecasts.
By using machine learning to analyze historical sales data, market trends, and other variables, retailers can better predict future product demand.
This can help retailers,
- Optimize inventory levels
- Reduce stockouts
- Avoid overstocking
- Improve customer satisfaction
- Decrease lost sales
Ultimately resulting in bottom-line profits.
- Faster and more efficient order fulfillment
Consumer expectations and competitive fulfillment practices from giants like Amazon and Walmart have put a lot of pressure on retailers.
Without an analytical approach, meeting today’s order fulfillment expectations is often cost-prohibitive.
Machine learning can be used to optimize delivery routes, warehouse layouts, and other aspects of the supply chain to ensure faster and more efficient order fulfillment.
In addition, this can help retailers,
- Reduce shipping times
- Minimize costs
- Reduce negative environmental impact
- Improve customer satisfaction
- Better inventory management
Managing inventory across an omnichannel business is a mammoth task.
Retailers are often faced with bad inventory management issues that are difficult to identify and fix.
By using machine learning to analyze real-time inventory data, retailers can gain deeper insights into inventory levels, product performance, and other factors that impact inventory management.
This can help retailers,
- Reduce waste
- Improve product availability
- Streamline vendor relations
- Optimize allocation and replenishment
Discover: How AI and ML improve stock replenishment in real-time.
- Optimize warehouse management
Manually tracking, sorting, inspecting, and processing products across numerous warehouse locations requires a lot of manpower.
Staffing shortages, safety issues, and human error are debilitating issues for effective warehouse management.
Machine learning algorithms help optimize warehouse operations by predicting which products will sell and where they should be stored for maximum efficiency; as well as automate warehouse operations such as sorting, inspecting, and preparing products for shipment.
This can help retailers,
- Maximize warehouse space
- Minimize storage costs
- Reduce product damage or loss
- Decrease product processing costs
- Enhanced supply chain visibility
Aligning operations across often siloed departments, manufacturers, vendors, and distributors is complicated by the lack of visibility. This ultimately leads retailers to ineffective supply chain plans and practices.
Machine learning can monitor supplier performance, track shipments, and identify potential bottlenecks or risks in the supply chain.
This can help retailers,
- Proactively address issues before they impact their operations
- Reduce human error
- Decrease costs
- Improve efficiency
- Increased agility and responsiveness
Once a sales plan is put into action it is difficult to identify and fix issues.
This is especially true when planning for a seasonal sales period, which is especially short and volatile.
By leveraging machine learning in their supply chain operations, retailers can be more agile and responsive to changes in customer demand, market trends, and other factors that impact their business.
This can help retailers,
- Stay ahead of the competition
- Adapt quickly to changing market conditions
- Pivot mid-sales season to contain an issue
Overall, machine learning can help retailers to optimize their supply chain operations, reduce costs, and improve customer satisfaction, which can ultimately lead to increased profitability and long-term success.
Benefit from machine learning in your supply chain
At the end of the day, a retailer’s goal is to increase profits and market share. With today’s heightened expectations and scope of business complexity, retailers will require the assistance of cutting-edge technology just to stay relevant.
By investing in retail solutions powered by machine learning, you will gain insights into your supply chains, improve demand forecasts, increase agility, optimize inventory levels, and improve customer satisfaction resulting in sales.
On top of that, you will create a more sustainable, resilient, and profitable retail business overall.
Don’t get left behind in the race for efficiency and cost-effectiveness – contact our team today to learn how AI-powered analytics and machine learning can help your supply chain operate at its best.
