Customer experience has come to the forefront in the age of digital, social, and mobile. Consumers (and the retailers that serve them), expect every order to be delivered on time and in full. Sales order fulfillment is crucial for customer satisfaction. From supply chains, customers expect full commitment to their orders, not standing the delays and partial deliveries, all with an expectation for more speed and personalized service.
However, companies continue to struggle to keep their promise on each order. They deal with high levels of uncertainty and variability, from supply shortages to inventory management to logistical challenges. These seen and unforeseen factors negatively impact order management, causing the situations that customers hate. With cognitive automation (or intelligent automation), even companies with complex supply chains can harmonize their upstream decisions and improve downstream fulfillment accordingly.
Managing supply chains is hampered by four key problems: disparate data sources, lack of visibility and insights, business processes that rely on institutional knowledge, and barriers to change. Because of them, order management suffers from master data challenges and inconsistent data models. It’s hard for companies to achieve a unified perspective of the business process with clean, harmonized data that is not easily accessible and available.
The situation worsens with the need to have human intervention that is often not tracked or documented, leading to processes that are outside the system without an audit trail. Typically, the Availability to Promise (ATP) process runs an Enterprise Resource Planning (ERP) system when there is a new order. The system pulls reports to show order holds, blocks, and ATP exceptions that are manually updated. Then, finance and logistics confirm these changes. Many people are involved in these tasks.
Managing supply chains is hampered by four key problems: disparate data sources, lack of visibility and insights, business processes that rely on institutional knowledge, and barriers to change.
Supply planners often rely on Excel or reports to analyze orders at risk and how to resolve these situations. This can be a weekly, daily, or hourly repetitive task. There is often little to no process automation. For example, if an order cannot be fulfilled with existing inventory, reports are pulled to check if some supply can be available. If not, customer service reallocates, reprioritizes, and/or splits orders. Then, transportation book parcel carriers plan to deliver orders, prioritizing by urgency. Only at this stage, can orders be picked, packed, shipped, delivered, and invoiced to customers.
It’s complicated. And messy.
Cognitive automation optimizes the process and increases the accuracy of order management. It provides end-to-end visibility for the business performance in all the key areas:
Cognitive automation can be a more effective system for keeping the promise on order management. With its set of technological capabilities, including working with legacy systems, it lets customers see more personalization and speed, even when they deal with the supply chains that suffer from extensive complexity due to globalization.