Modernize Your Order-To-Cash Processes With Digitalization And Automation

Thomas Dobis

Finance managers are at a crossroads. They want to lower costs, boost efficiency, and improve the cycle times of their order-to-cash (OTC) processes, but there’s no single path to achieving those goals. Should the finance managers stick with what they’ve got and wait for incremental updates, adding third-party bolt-ons wherever they can? Or should they start anew with a digital platform that incorporates automation?

Most companies have core enterprise resource planning (ERP) platforms to process and manage a majority of the transactions in their finance ecosystems, such as accounts receivable, credit, payables, financial statement preparation, and others. Many of these have been in play for years and they have added functionality to support new digital formats and produce better results. There are also bolt-on tools available.

Whether updated or integrated with new applications, the retooled platforms are delivering results. Additionally, they offer companies a homogenous platform to manage not only finance transactions but also similar generic activities in other domains where administration of transactions is important. And, while these platforms have become more flexible, they can be time-consuming to configure or reconfigure because they are often multidimensional. Furthermore, they are still limited in their ability to improve processing efficiency.

Also, OTC is customer-sensitive and therefore involves important impacts on customer satisfaction and future customer relationships. Often, using the standard functionality of an ERP system is not possible when managing line-item or customer invoice information, where there may be thousands of transactions a month that need to be processed and converted to digital. Bolt-ons take too much time to configure and require too much data-transferring and reconciliation to maintain.

The lure of the new

Companies typically don’t like to rip and replace systems that are core to their business operations. But technologies such as data digitalization, robotic process automation (RPA), machine learning, artificial intelligence (AI), and digital agents or chatbots, as well as newly designed workflow/case management tools, promise to improve efficiency and cycle times and lower costs more quickly than reconfigured ERPs and bolt-on tools can.

Upgrading the IT landscape and adopting the new tools can be challenging. As companies experiment with these new tools, they need to manage the necessary integration with their existing platforms and tools to achieve real results. How can corporations leverage the power of digitalization and automation to achieve optimum benefits at a price point and a project timeline that makes sense for the organization? Various generations of systems will need to be configured and reconfigured in a smart way so they all work together efficiently to deliver the new capabilities that are possible.

Just as processing power needs to be sorted out, companies will also need to determine which types of generic activities to target for digitalization and RPA. Scattered across these activities are common characteristics (size small, redundant copy-paste, repetitive rounding of numbers, reversing transactions-accruals, etc.), that make them better candidates because they don’t need to rely on ERP platforms for processing. Here are a few examples of OTC activities to consider for RPA:

  • Entering data in all systems
  • Checking data/entries for compliance with business rules
  • Extracting data from multiple sources
  • Merging multiple data sources
  • Reconciling/validating data between sources and within defined business rules
  • Creating, combining, and amending documents within Adobe
  • Uploading files to applications
  • Managing files
  • Reporting
  • Sending, reading, and receiving emails

The next step will be to concentrate on specific types of transactions and design an integrated approach, using all available tools, to tackle the efficiency gap that exists from receiving many different types of inputs to process certain transactions. Until now, the low-hanging fruit for RPA has been in the source-to-pay domain, focusing on e-invoicing with suppliers, supplier master data, and blocked and parked invoices. But we’re starting to see more complex domains targeted, and OTC is a processing area seen as ripe for redesign.

The case for automating OTC

Taking information that comes from customers and converting it into a digital format for use with RPA, AI, digital agents, and machine learning solutions is fertile ground for harvesting digitalization and automation opportunities. While there are certain processing requirements that make OTC unique and require analog data (like telephone contacts) as well as digital data (payment information from banks), there are also some very generic, everyday activities that happen at the core of the OTC process. These include document processing, master data creation and maintenance, adjustments to orders and invoices, changes to pricing details, application of promotional offers, etc. Some of these, mentioned in the list above, are key to processing transactions.

Not only could transactions be more efficient, but enterprises could also glean new business insights through predictive reporting, such as identifying potential credit exposures and write-offs or forecasting cash-flow revenues. The OTC process certainly could stand to benefit considerably if all information flowing through it were digitalized, identified, and used in various ways to drive new information from raw data. With a well-designed and maintained RPA solution, an enterprise could potentially save more than 30% through efficiencies.

Since it is likely that most enterprises will move to replace their core operating platforms or ERP systems, they will need a harmonized approach that works across the different systems and tools. And, they’ll need to extend their core systems so they can add RPA and other digital technologies to improve processing capabilities, either running them alongside bolt-on tools or instead of them. Also, consider that much of the processing and data required to create meaningful new insights in OTC reside outside the core operating systems (e.g., emails, algorithms, unstructured data, manipulated information, etc.). And these change daily, if reported accurately.

DXC Technology is an SAP platinum partner. This article originally appeared on and is republished by permission.

Thomas Dobis

About Thomas Dobis

Thomas Dobis is DXC Technology BPS Global Advisory Finance and Accounting (F&A) lead, with more than 30 years’ experience in F&A. During his time with DXC, he has been involved in implementing managed services solutions, business outcomes, analytics platforms, automation frameworks, and various advisory activities focused on improving client operations for more than 50 clients.