Order Promising: How Distributors Can Do It Better in Today’s Uncertain Environment

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Distributors’ customers depend on them to keep their own production lines, construction projects, and facilities running efficiently and effectively. As a result, distributors need a holistic approach to improve delivery—on time, and in full, when they promise an order will be there.

Unfortunately, this is no easy feat in today’s unstable supply chain environment. While customers are more understanding these days, their expectations remain high. Distributors must consider accurate order promising a high priority.

What Is Order Promising?

As the name suggests, order promising is providing reliable shipment and delivery dates to customers. Those dates are based on stock availability, known demand, planned supply, lead times, customer’s location and so on. A promised date may also incorporate priority factors such as the customer you’re working with. Are they one of your largest, most important customers? Or a one-off purchase by a customer with no urgency?

An important component of order promising is flexibility. To uphold their promises, distributors must ensure flexibility is built into the rules when determining estimated delivery dates and before communicating these dates to customers. This helps safeguard distributors and promote customer satisfaction.

What Challenges Do Distributors Face with Order Promising?

Ecommerce giants like Amazon have made it common to submit an order and instantaneously receive a precise delivery date. In many cases, buyers can view their delivery date before they even place their order. That expectation in the B2C world has bled into the B2B market.

But despite its ubiquity, accurate order promising can actually be quite challenging, especially in the midst of recurring supply chain disruptions and instability.

Sikich’s study with IndustryWeek found that 93% of companies responding experienced supply chain challenges in recent years. The main issues were:

  • Late deliveries from suppliers (73%)
  • Inventory shortages (63%)
  • Missed/late deliveries to customers (61%)
  • Increased inbound supplier lead times (58%)
  • Increased customer delivery lead times (50%)

Supply chain woes have continued to be largely out of distributors’ control and add a layer of complexity to reliable order promising. Visibility has been, at best, fuzzy in recent years.

Many have employed strategies to mitigate some of this uncertainty to mixed results. They’re increasing stock in key product areas, leveraging alternative suppliers or substituting products when it makes sense, as well as improving communication with customers so that they too can plan better.

However, manual methods are still somewhat the norm for allocating inventory and tracking supply. Microsoft Dynamics 365 Finance and Supply Chain Management’s Order Promising module ups the ante on a distributor’s ability to calculate and communicate reliable delivery dates to their customers.

How to Promise Reliable Delivery Dates

What do distributors need to successfully execute order promising so they can retain customer satisfaction? Before all else, they need to cultivate a resilient supply chain.

Supply chain resiliency is characterized by a distributor’s ability to adapt to disruptions and minimize the impact they have on operations. The global health crisis of 2020 — and its effects, which are still felt today — is an obvious example of a disruption in the supply chain. But less-obvious issues can also cause turbulence, such as a plant shutdown, unexpected material shortages, natural disasters or labor shortage.

That said, any disruptor big or small has the potential to wreak havoc on a distributor’s reputation if it isn’t navigated properly.

When supply chain disruptions are handled well, however, distributors can provide accurate and reliable delivery dates to their customers. Distributors can improve visibility into their supply chain with better data.

They can also leverage the Order Promising module of Microsoft Dynamics 365 Finance and Supply Chain Management.

Order Promising in Microsoft Dynamics 365 Finance and Supply Chain Management

The order promising functionality in the Microsoft Dynamics 365 Finance and Supply Chain Management ERP system calculates accurate ship and receipt dates using the following delivery control methods so that distributors can reliably fulfill customer promises:

  • Sales lead time: The time between order creation and shipment of the items
  • ATP (available-to-promise): The available item quantity that can be promised to a customer
  • ATP + Issue margin: The ATP date plus the time required to prepare the items for shipment
  • CTP (capable-to-promise): Considers both material availability and capacity

The Order Promising module enables you to promise an order to be shipped or delivered on a specific date – and meet that promise. The tool calculates the date that an item is available to promise or capable to promise, and order lines are created for those dates that you accept. The functionality calculates the earliest possible date that an item is available for shipment or delivery. It also creates requisition lines, in case the items must first be purchased or produced.

Learn more in this video:

To learn more about setting up and optimizing the Microsoft Dynamics 365 order promising module of Supply Chain Management for your organization, contact an ERP consultant at Sikich. We can help you improve your delivery process, keep your customers happy and get future-ready.

This publication contains general information only and Sikich is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or any other professional advice or services. This publication is not a substitute for such professional advice or services, nor should you use it as a basis for any decision, action or omission that may affect you or your business. Before making any decision, taking any action or omitting an action that may affect you or your business, you should consult a qualified professional advisor. In addition, this publication may contain certain content generated by an artificial intelligence (AI) language model. You acknowledge that Sikich shall not be responsible for any loss sustained by you or any person who relies on this publication.

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