Order promising is essential to a properly functioning supply chain.

When products or services are ordered by customers, an organization's ERP solution uses its order promising capabilities to inform them of shipment and delivery dates. Well-executed order promising lets companies provide accurate estimates to their customers, in turn supporting high levels of customer service and a general reputation for reliability.

However, order promising doesn't always go so smoothly.

Common problems in ERP order promising

For starters, effective order promising requires full visibility into how fluctuations in supply and demand are affecting expected deliveries.

Even orders that don't seem like major events at the time can have profound effects on a company's ability to ultimately make good on its promises to all buyers. The so-called "bullwhip effect" shows how this can happen.

For example, say a retailer saw lowered customer demand on a particular day, leading it to order less from the distributor, which in turn requested smaller shipments from the manufacturer. However, the lessened demand turned out to be an anomaly. Once it returned to normal levels, there was a shortage throughout the supply chain, and the manufacturer had to push out its order promising dates.

Doing so can cause reputational damage, especially in a world in which consumers already have high expectations for timely fulfillment, in part due to the rapid delivery available for many products ordered online (e.g., those bought via Amazon Prime).

Indeed, a 2017 Supply Chain Management Review Survey found that "maintaining customer satisfaction" was the most-cited challenge among manufacturing, high-tech, and retail organizations. Order management complexity, inaccurate order promise dates, and rising costs across IT and the supply chain were not far behind.

These issues can coalesce in situations in which organizations order more than they forecasted, causing other buyers to see delays in their shipments. So what's the best solution to this common problem?

Solving order promising woes with ERP systems

Many workarounds for poor order promising — such as manual processing, using spreadsheets or dummy orders/reservations — aren't all that scalable or efficient. A better approach is to harness the power of a modern ERP such as Microsoft Dynamics 365 Business Central (formerly Microsoft Dynamics NAV).

Dynamics allows for careful monitoring of current supply and demand levels, with usage of basic concepts such as Available to Promise (ATP) and Capable of Promise (CTP). Whereas ATP makes calculations based on unreserved quantities in inventory, CTP assumes a scenario in which the requested item isn't ready yet and determines how long it would take to attain it.

In Dynamics, it's relatively straightforward to configure the ERP system for different order promising formulas that result in realistic delivery estimates for customers. Accent Software can help you get started with a Dynamics implementation that's right for you. Reach out to our team to learn more today.