Inventory planning is like putting on a pair of jeans before a long road trip. In other words, you need the perfect fit. Otherwise, things will get uncomfortable quickly.
If you have too little product in stock, you’ll have trouble filling orders, and customers may look to other suppliers. On the other hand, if you have too much of a certain product, you’ll wind up paying for excess storage and inventory management. Neither outcome is desirable for your company if you care about profitability.
In the past, keeping the right amount of material in stock—and ordering the correct items—was difficult. Managers didn’t have much visibility or insight into their supply chains.
However, recent advancements in supply chain forecasting and data collection make this process easier and more efficient than ever. This post explores what supply chain forecasting is, why it matters to organizations like yours, and how you can implement it into your shipping operation.
Supply chain forecasting involves analyzing various data points to uncover trends and make accurate estimates about product availability, consumer buying patterns, and prices, among other things.
Generally speaking, suppliers use three types of forecasts to guide their decisions.
This type of forecasting involves looking down your supply chain and determining how much product your partners can provide.
This is necessary for determining how much product you can order. It also lets you know when you can expect it to show up at your warehouse for storage and eventual shipping. It’s also important for sales and marketing teams. It enables these teams to create custom campaigns and strategies that are in line with the current economic reality.
While supply forecasting has always been important, it took center stage following the outbreak of the pandemic. Overnight, the market shifted, and consumer demand exceeded supply for many goods.
For example, consumer anxiety about using public transportation, plus boredom and a need to exercise, led to widespread bicycle shortages. Companies had to adjust their strategies accordingly when it became apparent that there was far more demand than supply for new bicycles, as well as parts and accessories.
Another type of forecasting involves predicting consumer demand for specific products. By doing so effectively, you can make sure you have enough product in stock during the busiest times of the year.
Effective demand forecasting requires using advanced analytics to determine when customers are likely to buy certain items.
Going back to the bicycle example, retailers needed to look ahead and predict future customer demand for these items due to COVID-19. It wasn’t easy to determine whether there would still be heightened demand for bicycles after the pandemic or whether public interest had already peaked.
According to McKinsey, forecasting based on underlying causal drivers of demand instead of prior outcomes can improve forecasting accuracy by 10% to 20% and lead to a potential reduction in inventory costs of 5%. That’s pretty incredible.
The third most important type of analysis is price forecasting. This type of forecasting involves collecting and processing market data to determine how product prices and operational costs may fluctuate over time.
Price forecasting is critical for budgeting purposes and for buying products in advance. For example, a team may use price forecasting to anticipate rising gasoline prices. That team might then change its shipping strategy to reduce the number of truck rollouts along particular routes.
As you can see, supply chain forecasting is critical for success. It helps streamline inventory. And it makes scheduling, staffing, and distribution easier and more affordable.
So, how do you forecast a supply chain?
As it turns out, there’s no single strategy for supply chain forecasting. Rather, it involves piecing together a variety of data points. With that in mind, here are some common things you can track to improve your operations over time.
Some seasonal patterns tend to be consistent year over year.
For example, people are usually more interested in buying snow tires in the fall and winter. It’s when the weather starts to change, after all. And purchases of pool chemicals tend to rise in the spring and early summer when more pools are open and in use across the country.
Understanding when consumers tend to buy certain products can help you predict when you should start stocking and shipping them.
We’re now in the digital age. Consumer buying patterns are changing by the day—and even by the hour.
Suppliers need to remain aware of these shifting patterns. That way they can respond to consumer needs accordingly and reduce costs.
To illustrate, many items that people used to buy primarily in retail stores are now commonly bought online. By identifying where and how consumers buy certain goods, providers can have an easier time forecasting inventory and storing items for delivery.
One of the best ways to forecast demand is to use insights and data from your own sales, marketing, and production teams.
Often, you can discover critical insights in conversations with customers and suppliers, as well as in industry reports and sales records. Teams need to incorporate internal insight when forecasting wherever possible.
Companies also solicit advice from external experts—such as consultants, contractors, and analysts. These sources can provide independent data to help predict market activity and discover emerging trends.
As an example, an outdoor retailer might speak with a marketing consultant. During that discussion, the retailer might learn that the majority of their target customers want winter jackets rather than coats or vests. More specifically, those jackets need to be ethically, sustainably, or locally produced.
This type of insight can go a long way in helping a company determine its sourcing and shipping strategies. With the right approach, it can lead to higher profits and happier customers.
There’s no right or wrong way to go about supply chain forecasting. Every company is one of a kind. As such, each requires a bespoke approach to supply chain forecasting. If you try a “one size fits all” strategy, it’s just not going to work. It’s that simple.
For example, a food provider is going to have forecasting requirements that are different from those of a company that sells car tires or clothes. In this case, seasonal, environmental, and economic data can be of significant importance.
However, there’s one critical need that all companies have with supply chain forecasting: a strong data pipeline. For the best results, data needs to quickly flow into the company. That way, teams can process it and turn it into actionable insights rapidly.
Vector offers custom mobile apps you can use to collect and report a variety of supply chain metrics. For example, Vector lets you track unplanned pickups in real time, gain visibility into transportation, and see how items are moving over time.
You can combine these types of internal metrics with larger economic and industry data points, enabling your team to benchmark performance and plan more effectively.
At the same time, Vector can help your company migrate away from old-school, ineffective, paper-based systems and accelerate your digital transformation efforts.
Add it all up, and Vector can turn your shipping and logistics team into a robust data pipeline—producing a variety of insights you can use to create a leaner and more effective operation.
Check this out to learn more about how Vector can transform your supply chain function.
This post was written by Justin Reynolds. Justin is a freelance writer who enjoys telling stories about how technology, science, and creativity can help workers be more productive. In his spare time, he likes seeing or playing live music, hiking, and traveling.
Digital workflows across the supply chain.
