How to get started with AI-powered automation

Sales order entry initiates a complex series of processes at multiple touchpoints to fulfill what your business has promised. Sales order management challenges include:

• Complex and ever-changing supply chain conditions. Your business relies on multiple suppliers, each with its own systems, processes, and requirements.
• Inventory management is a synchronization nightmare. Varying stock levels and replenishment cycles demand careful planning and forecasting to avoid stockouts or inefficient overstocking.
• Order size and processes vary by channel. You must systematize as many workflows as possible while allowing flexibility to handle order size, product types, and changing customer demands. If you have 1,000 reps completing 30 orders a day, your systems must handle and coordinate more than 30,000 data points — each one unique.
• Speed and communication are symbiotic. Order management requires seamless communication to resolve fulfillment issues affecting customers.
• Returns and post-sales service add another layer of complexity. Efficiently managing reverse logistics to handle returns is one problem. However, you also must ensure customer satisfaction—a time-consuming and delicate dance.

Each touchpoint in the chain is an opportunity for inefficiencies and errors, particularly if you rely on human workflows.

Despite technological advances, many companies continue to use manual processes, which create risks and are time-consuming. Consider that manual data entry has a generally accepted error rate of 1%. Many purchase orders (POs) arrive via email, requiring the customer service representative (CSR) to manually enter the data into an order management system (OMS). Even a 1% error rate can negatively affect a low-margin, high-competition business.

Some of the negative effects of manual sales order processing include:

• Errors. Manual order entry processes can be slower and more prone to errors, especially when compared with automated systems. Mistakes such as incorrect product selection or shipping address inaccuracies can lead to delays in order processing, resulting in longer lead times, dissatisfied customers, and an unhappy sales team.
• Kills repeat business. Keeping and growing an existing customer account is much more cost-effective than prospecting for new ones. Manual order entry and fulfillment processes may not provide the same speed, visibility, and accuracy that customers expect today, increasing the risk of a suboptimal customer experience.
• Harder to keep up with demand spikes. Manual processes may limit a company’s ability to handle large order volumes or sudden demand spikes. Manual data entry, order verification, and fulfillment create bottlenecks and capacity constraints.
• Custom orders are unwieldy. Complex or customized orders often result in delays, as manual processes make it harder to accurately capture and fulfill intricate product configurations, special requests, or order variations.

As customer demands grow and unexpected disruptions increase, organizations must adapt their internal operations to streamline processes and improve accuracy – both critical variables in determining the profitability of a business.

The answer is integrating AI-powered automation into these workflows. For example, documentation automation helps businesses manage unstructured documents, such as PDFs or scanned documents, more efficiently. Order entry automation reduces the risk of error by populating customer details, the latest pricing, and even real-time inventory data without toggling between systems. Process automation removes the need to key orders into the ERP system by hand, freeing customer service reps to spend more time building relationships with customers.

Where to start with order management automation

But how can organizations start the journey toward an automated order management strategy? It’s about more than technology. They must align their people and processes with the right technology to get the most from automation.

Start with a systems readiness check to ensure your existing systems are ready for a change; look at factors such as compatibility, sizing, integrations, and business processes.

Also, implement a data cleanse using tools that are designed to clean inaccurate customer and material data. If your data is inaccurate, inconsistent, or incomplete, you won’t get the ROI that you’re seeking from intelligent automation.

Conduct a custom code usage analysis to understand compatibility, performance impact, and quality. Most organizations use only a small percentage of their custom code.

As important as a solid technical foundation: You must prepare your people for the change. It’s human nature to default to the system we already know vs. leaning into a new solution. Implement change management strategies to increase buy-in; automation is not something you can stick your toe in the water with. The system learns with volume. Companies must take a leap of faith. Ongoing training is critical to get the most from intelligent automation.

Communicate the tangible benefits at the user level and calculate the costs of doing things the way they’ve always been done. Maintain clear goals. Make sure the team is reminded of why they are doing this:

• Fewer errors
• Reduced order processing time
• Reduced customer service costs
• Better customer experience
• Greater profitability

A key part of the sales productivity toolkit

Outdated technologies lack integration and scalability, creating manual workflows and redundant tasks that serve as an anchor for companies seeking growth.

In the right areas of your business, automation can correct sales orders when they start to go wrong, improve processes, and boost your bottom line. Automation is an important piece of the solution, but organizations must be strategic in their adoption of these tools. They must recognize the challenges of implementing them, even as they reap the benefits of their use.

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