I’ve seen it play out so many times.
A growing, well-established manufacturing company decides to take its business processes to the next level by implementing an ERP system. The company evaluates solutions, makes the best choice for its needs, and begins the implementation process.
Months later, the new system is live, and the company’s planners begin building their business processes into the system. Based on their years of experience in the field, planners come up with an average lead time for each major category of supplies. They punch this information into the system.
And then they run their business based on these assumptions for the next five to 10 years.
Sometimes, suppliers deliver sooner than the estimated lead times, resulting in overstocks and the need to clear out inventory at reduced prices. Other times, suppliers fail to meet the expected lead times, resulting in missed orders, disappointed customers, and a loss of business.
Most planners figure this is just a fact of life. You make your best guess about lead times, and you take the good with the bad. After all, who can see the future?
You can. With predictive lead time.
How Predictive Lead Time Works
Don't get me wrong—implementing an ERP system can be a huge step forward for a manufacturer or distributor. But if you’re entering estimated lead times into the system and then working off these assumptions for years to come, you’ve only just begun to enhance the performance of your supply chain.
By using predictive lead time functionality to increase the accuracy of your lead times, you can optimize your ordering in ways that boost your customer service levels and minimize your inventory levels.
How does it work? Predictive lead time revolves around tracking every line item of every transaction in your system and running that data through a powerful forecasting engine. The resulting analysis enables you to determine a lead time for any item you’re ordering.
Mind you, this lead time isn’t just a one-size-fits-all estimate. It’s actually tailored to the time of year. So if you’re ordering widgets in March, you’ll likely get a different lead time than if you were to order in September.
Predictive lead time takes into account that for a particular item in your supply chain, from certain suppliers, the lead time from order to having the goods available for sale takes 70 days as a rule, but at certain times of the year it is taking, for example, 85 days. Based on all of this information, your system will prompt you to order stock at exactly the right time to receive the goods by the delivery date you require.
With this kind of granularity, you also can pinpoint problems in your supply chain and address them with the partners who are directly accountable. For example, you may gain the insight to know that a particular vendor takes an extra 30 days to deliver goods in November and December. In your conversations with the vendor, you may determine that someone in their supply chain works a reduced schedule during that time period. By discussing the issue, you can find a workaround to the problem—or simply change vendors.
So, not only does predictive lead time help you deliver outstanding customer service without holding excessive safety stock, but it also helps you work toward continuous improvement in your supply chain.
Finding Predictive Lead Time Tools
Predictive lead time is a capability that manufacturers and distributors have craved for years. Unfortunately, few systems actually deliver it. You are unlikely to find it in ERP systems, and few supply chain planning vendors have delved into the world of predictive lead time. If you’re really serious about improving your service levels and reducing safety stock and want a solution that can help, ask your potential supply chain software vendor if they can deliver a predictive lead time tool.