Accurate estimated delivery dates (EDD) are essential for customer satisfaction in today’s fast-paced retail landscape. When customers place an order, they want to know exactly when it will arrive. Misleading or vague delivery estimates can lead to frustration and lost sales. However, providing precise EDD is a significant challenge for retailers due to various factors like inventory accuracy and network optimization.
With real-time inventory availability and advanced technologies, retailers and brands can enhance the accuracy of EDD, ultimately boosting conversion by 7%, increasing customer satisfaction by as much as 5 NPS points, and amplifying customer lifetime value.
Understanding Estimated Delivery Dates
An Estimated Delivery Date (EDD) is the projected date when a customer’s order will arrive.
It’s a crucial but often missing piece of information that influences the customer’s purchase decision and overall shopping experience. Accurate EDD can build trust and encourage repeat business, while inaccurate EDD can lead to disappointment, cancellations, and negative reviews. It’s necessary for brands and retailers to fully understand what is needed to provide an accurate EDD to their customers. If the accuracy of that date is not within the industry benchmark of 95% or above, it is actually MORE beneficial not to provide an estimated date at all.
Numerous factors go into accuracy—all of which are dynamic in nature and are not static data points in the equation. These include:
- Historical shipping data
- Carrier performance metrics
- Real-time inventory levels
- Labor management considerations at the store
and more
These methods must be seamlessly integrated and regularly updated to ensure the accuracy of the delivery estimates. The question is—is the market ready to take on this lofty and rewarding goal? What are the barriers to achieving this success?
It Starts with Accurate Supplier Inventory Data
Supplier and in-network inventory accuracy is a critical component in determining EDD. This is a two-fold conversation about inventory, in that it must both be real-time inventory synchronized to the estimation tooling, but also be accurate as well. A real-time picture of an inaccurate view of inventory has a negative effect on availability/promising.
One key challenge with variability is the frequency of suppliers/manufacturers reporting and delays in updating inventory status. To mitigate these challenges, retailers can implement several strategies:
- Frequent Audits: Conduct frequent audits of supplier, distribution center (DC) and store inventories and ensure they comply with agreed standards. Cycle-counting in stores and DCs is great, but the market is moving to RFID enablement.
- Standardized Reporting Formats: Use uniform formats for inventory reporting to minimize discrepancies and improve data consistency. Understanding, through inventory-control and Omnichannel-Operations, how to speak in ‘one language’ with your inventory is paramount.
- Real-Time Inventory Tracking Technologies: Invest in advanced technologies that provide real-time visibility into inventory levels. This can significantly reduce the lag in data updates and enhance the accuracy of EDD.
Optimizing Network Inventory for Better EDD
We often observe that the typical systems that provide availability/estimates, namely order-management solutions, often have the onus of ‘fixing’ the supply chain problem of poor inventory planning. This means that inventories ‘going stale’ in certain DCs or Stores get either over or under emphasized in the availability/pre-sourcing equation, potentially causing split-shipment scenarios upfront (before the buy-button) and eroding both shipping margin while confusing consumers why they cannot just receive one package from the brand.
The missed opportunity for improving estimated dates lies in a more comprehensive look at network inventory management—strategically positioning products across various locations such as distribution centers, fulfillment centers, and in-store inventory while mastering the ability to define each Item-Location relationship by sell-through, markdown status, utilization and seasonality. When products are as close to customers as possible, delivery times are reduced, thus improving EDD accuracy.
What Role does Predictive Analytics for Demand Forecasting have?
The market has seen a rise in the past five years with the incorporation of data analytics to predict demand patterns and adjust inventory levels accordingly, ensuring that high-demand items are always in stock. Similarly, the under-leveraged inventory that is ‘stale’ in the network can also be optimized much better now, in a much more dynamic way than before. Both aspects play into EDD calculations, and the leading retailers know how to play both sides of the fence here to ensure inventory is balanced with the ability to deliver quickly to customers without causing eroded shipping margins.
What Role does AI/ML Play?
The dynamic nature of the underlying data changing means that the availability rulesets and pre-sourcing logic should also adjust to the fluctuating variables involved in the decision. Where OMS solutions 10 years ago were mostly heuristics based (If/then/else logic, static rules), we now see a shift in leading solutions to a much more dynamic outcomes-based approach to availability and sourcing. With AI beginning to take more of the mundane task that the team would typically do, the opportunities to offload the administration of the roles to AI and free-up time to focus on proactive problem identification and solutioning has never been greater, specifically in three key areas:
- Identifying Problems: AI is now being applied at leading retailers to understand what inventory is ‘stuck’, identifying patterns of fulfillment likelihood at potential nodes and making recommendations to strategy changes (in natural language).
- Dynamically Addressing Decisioning, Proactively: As mentioned above, with an increased acceleration in the velocity of data changes, the engine doing the sourcing must also now become dynamic in nature. OMS engines are now being built to dynamically change decisioning based on factors like spikes in demand, the weather for that day, and the amount of foot-traffic in the stores.
- Identifying Patterns: With an EDD made in the pre-purchase phase, the onus shifting to the post-purchase solutions is now even greater to execute against the promise. AI is now being applied to proactively identify risk to previously promised dates and dynamically recover the order (while keeping margin in balance).
A Layered Conversation: It’s not just about Systems
Staying updated with industry trends and technological advancements is crucial for continuous improvement. Retailers should be adaptable and ready to pivot strategies based on market changes and customer needs. Four key layers must come together to ensure an accurate estimated delivery date is made then executed on.
Customer Experience Layer
Different channels may require different strategies for promising, especially for retailers that are also manufacturers and who sell online. Across all customer touchpoints, the estimated date should be available and ready to share with customers. With clear strategies for each customer, the conversation then shifts to where and how the estimated delivery date is displayed. A/B testing may be required here to understand if “Next Wednesday” is better for your customer, or “Wednesday May 22nd” is instead. Regardless, the “in 5 to 7 days” is now a thing of the past!
Operational Control Layer
Largely this is the systems layer which administers the decisioning. Data objects within the system range from the labor aspects, facility operating aspects, carrier aspects, and exclusion/inclusion rules of the articles (items)—and most importantly, the inventory itself. All these configurations and decisions must come together, dynamically, to consistently produce accurate dates.
Operational Oversight Layer
With a great CX and operational controls set, the ability to oversee all aspects of the accuracy become critical. While dashboarding is a given in this layer, what is often missed in the communication mechanisms is to ensure that the retailer is constantly talking about the accuracy, adjusting based on decisions within the organization, and proactively discussing and mitigating risk to the supply chain.
Underlying Data & Signal Layer
At its core, inventory is the largest variable in this equation and the underlying basis for the decision. As the B2B world begins to adopt these EDD capabilities, the ability to promise against On-Order (PO) and In-Transit (ASN) inventory becomes even more important, as does the accuracy of the inbound inventory. Where the above is operational oversight of the orders, it is equally important for the organization to spend time defining reporting around inventory oversight—both for the timeliness and accuracy of the suppliers inbound into the network.
Conclusion
Accurate EDD is vital for ensuring customer satisfaction and loyalty. By focusing on supplier inventory accuracy, optimizing network inventory, and integrating advanced technologies, retailers can significantly improve the precision of their delivery estimates.
But remember, in order to provide customers with a truly accurate EDD, the right order management system is essential. Not all OMSs provide the technology, speed and agility that is needed to accomplish this. That’s where a platform like Fluent Order Management comes in—one that drives growth, flexes with your business needs and importantly, provides a real-time, accurate view of inventory across all channels, markets and regions.
Investing in these strategies to provide customers with an accurate EDD will not only enhance the customer experience but also drive long-term success in the competitive retail landscape.
Every business is unique. If you need to gain executive support to explore a new order management system, please reach out to Zach Zalowitz at Perficient.
About the author
Zach Zalowitz is the Principal, Order Management Practice at Perficient, the leading global digital consultancy. Zach is considered one of the leading voices in the post-purchase experience space, and has an expertise in order management solutions in the market. Prior to Perficient, he was VP of Digital Technology and Digital Experience at Foot Locker where he oversaw a global team of digital experts focused on the website and mobile app experience.
