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At a time when businesses are looking for ways to wring inefficiencies out of their operations to drive increased profit margins, sales order processing sticks out as a prime candidate for automation.

Automating the sales order process reduces costs, accelerates cycles times, enhances the customer experience, and frees staff for value-added tasks. That’s according to an APQC survey of 167 sales order professionals from businesses with high order volumes or just-in-time inventory strategies.

In fact, automation saves businesses between $5 and $15 per sales order and reduces sales order cycle times by more than 46%, according to APQC research.

In some industries, sales order automation is a major factor in keeping up with the competition in terms of customer satisfaction. Yet, many businesses still manually process sales orders that arrive as paper or via email or fax. Manual processing has a big impact on the efficiency and effectiveness of order processing at most businesses, to say nothing of the errors and delivery delays that inevitably result from manual keying.

With unrelenting pressure to reduce costs and 34% of businesses surveyed by APQC moving more of their staff to customer-facing positions, now is the time to automate order processing.

Rethink your approach to automation

Businesses cite several reasons for dragging their feet on automating their sales order process, including no capital budget, strained departmental resources, fear of change, competing priorities, a lack of IT resources, and no senior management champion. But one of the biggest barriers to sales order automation is the antiquated approach most businesses take to automating their processes.

Most businesses have taken a top-down approach to automation, where IT is tasked with installing and enabling independent systems to automate a function such as order processing. But the pace of innovation is moving very fast, resulting in a huge backlog with IT.

What’s more, enterprises are regularly deploying new systems, without retiring old ones. As a result, humans manually perform 80% of the business processes, including those that require manual data transfer between legacy systems and those IT hasn't had time to automate at all.

Just consider the amount of time staff wastes rekeying and cutting and pasting order information into various systems.

Making matters worse, traditional order-entry systems only handle structured data — the kind that comes from paper or electronic spreadsheets, databases, or standardized forms. But businesses are drowning in unstructured data, such as text messages, emails, handwritten messages, and semi-structured documents that contain a known set of data but with different layouts that make the data hard to extract. Many ignore this data because of the complexity in processing or analyzing it. In fact, this data is referred to as “dark data” because businesses simply don’t know what it contains.

Robotic Process Automation (RPA) with cognitive automation offers a better approach. RPA automates simple, repetitive tasks that can be easily replicated by instructing a software bot to copy keystrokes or to follow a defined set of rules. Bots interact with IT systems and applications, just like humans do.

This technology is largely plug-and-play and doesn't require changes to existing IT systems, legacy applications, or machines. This makes RPA ideal for sales order processing, where seamless integration with systems of record, such as an enterprise resource planning (ERP) application, inventory system, or customer relationship management (CRM) platform, is critical for eliminating process inefficiencies and information gaps.

RPA automates sales order processes such as:

  • Retrieving sales orders
  • Extracting sales order data
  • Validating sales order information
  • Electronically routing sales orders for approach and exception handling
  • Uploading sales order information to downstream systems

Leveraging artificial intelligence (AI) for cognitive automation enhances RPA with the ability to process and analyze unstructured and semi-structured documents, such as sales orders. RPA solutions with AI capabilities have built-in domain expertise to find unique, process-specific data that's required for specialized processes.

A combination of computer vision, optical character recognition (OCR) technology, and fuzzy logic automatically extracts and enriches data while machine learning (M)L helps improve the accuracy of captured data. Cognitive automation helps ensure an intelligent system extracts all the unstructured data.

Importantly, AI-powered automation delivers results faster than antiquated systems. The technology is pretrained to automate business processes.

This eliminates the need for IT and/or data scientists to design elaborate models. Business users can design their own processing models and begin operation in just a few weeks — no coding skills necessary. Consumer-grade usability and enterprise scalability help ensure strong user adoption and fast return on investment while meeting current and future business requirements.

A key to business success

The business case for automating the sales order process is proven and compelling. Nearly 90% of organizations surveyed by APQC say increased process automation and integration is very or extremely effective in driving the business entity’s success. Thanks to RPA with cognitive automation, it’s never been easier for businesses to automate their sales order process.

RPA with cognitive automation overcomes the barriers erected by traditional approaches to automation, enabling businesses to finally eliminate paper-based order entry processes and reduce costs, accelerate cycle times, better use staff, and deliver a superior customer experience.

Ready to automate 
your sales order process?

About Semyon Sergunin

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With a background in software development, B2B marketing, and sales, Semyon Sergunin has worked in automation technology for more than 15 years. He drives the global adoption of intelligent automation solutions, including Document Automation and Discovery Bot.

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