Hyper automation in order management

Using multiple levers for transforming Order management is critical for organizations today. This article discusses the potential of automation in order management, key use cases of automation in order management and the multiple levers for transforming order management.

Customer Experience (CX) is at the forefront of enterprise transformation and Order management, processing & fulfilment form the key pillars of higher CX. Imagine an organization has about 20,000 + corporate customers and assuming around 20 templates for each customer to do order entry, there may be 400,000 unique sales order templates that employees implement using a data capture solution. If each template takes let us say around six hours, total effort spent on order entry will be over two and half million hours, and if we multiply average $/hour salary of these associates, you get the total $ /hour salary spent, and assuming a 50% time savings via automation, the potential is immense.

As per a recent APQC survey , automation saves businesses from $5 to $15 per sales order, and reduces sales order cycle times by > 46 percent. Business leaders realize the need for this transformation as around 30% of supply chain leaders  highlighted the need to respond to customer mandates for faster fulfillment as a top business priority and around 36% identify opportunity to optimize their inventory to balance supply and demand via analytics.

A typical order management cycle comprises of steps such as order enquiry, order entry, requesting for quotation, creating a purchase order, processing of the order also known as order fulfilment followed by invoicing the customer, managing returns (if any) and mapping the customer experience.

Let us see how a complete order management cycle looks like, i.e. Figure 1: Typical order management cycle where we try to map the business value chain, as well as attempt to apply digital levers, such as RPA, Cognitive/ Artificial Intelligence and Machine learning to solve parts of the puzzle.

Using RPA, AI & Cognitive levers, the core pillars of the order management business cycle can be understood as Order entry, order validation, procurement/inventory management, order distribution & invoicing.

Given that organizations generally grapple with challenges related to People, Process or Operations, technology and business models, outsourcing non-core functions within the Order to Cash (O2C) & Order to Invoice (O2I) can be of immense value, so that the workforce could focus on larger strategic mandates. Figure 2: Partially Vs Fully outsourced Order to Cash (O2C) & Order to Invoice (O2I) highlights some of areas examined for outsourcing along with the applicability of automation with process complexities in varying degrees of High, Medium & Low.

Where does multiple levers of transformation come in? For seamless transition of elements, such as website, mobile app, sales, planning, suppliers, purchasing, manufacturing & distribution and linking them to customer, while a single transformation lever might not be able to address all touch points, multiple or a combination of levers can certainly help navigate.

• Artificial Intelligence (AI) & Optical Character Recognition (OCR) can be used for thought based cognitive automation, and when a combination of AI + OCR is applied to RPA, the resultant outcome would be a seamless analysis of semi/unstructured documents, i.e. sales orders. The combination of computer vision, optical character recognition (OCR) technology, and logic automatically extracts and enriches data while machine learning (ML) helps improve the accuracy of captured data.
• Chatbots are applied in the front office to communicate to the customers on order processing status, be it over emails, website, customer experience portal or social media.
• Dashboards and analytics is laid over the complete order management system to provide multi-level insights & dashboards on customer wallet sizes, frequency of order returns, efficiency and gaps of the order fulfilment systems etc.

Let us practically look at an end-to-end map of an order management cycle, and map multiple transformation levers. Figure 4 illustration talks about a plethora of offerings, such as process simplification, using workflow management tools to communicate across disparate internal systems, using chatbots for CX transformation, and a dedicated order management system if need be and all of these wrapped up by analytics, so as to result in an end to end transformation.

Some benefits realized from transforming the order management function could be:  

• A simplified Network Operations Center (NOC) Processes can result in 30-45% of overall productivity benefits over a two-year period.
• Automation of 10-15% of the overall order-to-cash (O2C) processes can result in savings of $300K-$350K in a span of three to four months.
• Around >95% transaction accuracy can be ensured via order processing along with a 15-45% reduction in rework due to order processing.

Considering the potential benefits that can be realized, it becomes prerogative for organizations to start the automation journey at the earliest to ensure they are not left behind in the automation wave. An ideal approach is to do due diligence and shortlist the right candidates first for automation within the order management life cycle, so that the first set of processes or queues chosen are right on the radar and set the tone for the subsequent ones to follow. It is even more crucial that the automation solution designed aims for scalability that can be ensured by setting up Centers of Excellence (CoE) so that they are [SV(M1] stable, governed, accounted for and orchestrated with a change management framework by deploying a right governance model to ensure that automation initiatives are not in siloes.