How data analytics can help you better understand your supply chain

We’ve all heard and seen the realities of freight rate increases. In 2021, domestic freight rates for transportation of goods by road and rail in the United States increased by 23% compared to 2020. But the real problem is that even if you can afford this increase, the product and capacity may not be available. Obviously, the demand is there, but the supply on the transportation side to meet that demand may not be.

Given this increase in both cost and demand, there has never been a more important time to build a file Data analytics The strategy that helps you find ways to highlight when your products will arrive – and the true cost of not knowing.

Start by understanding the big picture

The old phrase “information is power” has never been more true. In terms of product availability, this means having real-time breakdown of the entire supply chain allows for quick adjustments that have a measurable impact on both revenue and margins. Shipping costs are a growing piece of the profitability puzzle. The other side of the coin is revenue. Are you now also losing revenue due to not being able to get your products on time – or at all? Or can you create a competitive advantage because you have products available? Your customers are still ordering, but if you can’t fulfill those requests, what is the actual impact of this issue on your business?

People (your customers) will find another way to fulfill their orders, and those are the customers you may never get back. The first step is to view this problem not as a “it will pass” challenge but as a serious threat to your business. The next step is to build a data analytics strategy to solve these problems and make your data actionable.

Define a demand forecasting model

When your job hinges on sourcing raw materials or products and then shipping the product back, it becomes a real challenge when you don’t know if/when a particular shipment will arrive. These unknowns can become the cause of product delays and diminished customers — but they don’t have to. The cost and speed of building predictive analytics and cloud data platforms has decreased dramatically in the past 18 months. Businesses no longer have to spend a small fortune to generate value from their data.

By understanding what factors matter – everything from economic financial models, to what’s cyclical, to movement of people geographically, to what’s unique to your industry, you can build an order model to see what you need to plan for in the next three to six months. This information, when combined with lead times for raw materials, production time, and shipping time, can become the backbone of your logistics strategy for what to order – and when.

Learn about the actual impacts on your margin

We often call this ‘profit margin attribution’. Without the ability to understand what contributes to an expense, it is nearly impossible to make changes. Freight expenditure analysis tends to reveal the main insights and the need to improve this expenditure. Are you using the right vendor for the right shipments? Does the shipping lane, origin or destination location, customer or product type cause a disproportionately positive or negative impact on margin? Do product characteristics, such as weight, SLA dimensional weight, and distance from distribution center to name a few, have an effect?

These and other ideas can have a significant impact on how the seller prices the shipment. Making the wrong delivery decision could have a significant impact on gross margins. We have clients where there has been up to a 20% potential cost saving due to choosing the wrong vendor. By understanding shipping expenses — and where the hidden costs are, you can decide which vendors to use, for which products, and for which customers.

When you’re looking to control unknown factors, it’s not about getting to the perfect state. Instead, it is about continuous improvement and moving towards it. The direct result is increased revenue and reduced costs. The strategic result is that when you can meet your customers’ demand, you have an enormous competitive advantage over everyone else in your field.

Dave Taddei is Senior Vice President, North America Data Analytics Practice Manager, at AllCloud.

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