How to achieve end-to-end hyperautomation?

Unlocking the value of hyperautomation and reaching enormous levels of efficiency, customer satisfaction and other benefits. This is the dream of many organizations and the promise of the hyperautomation concept. Hyperautomation, as advocated by Gartner, goes beyond individual technology implementation. It extends the scope of automation by orchestrating advanced technologies like AI, low-code, Robotic Process Automation (RPA), chatbots, and more, to create end-to-end business process automation. The results? Lower operating costs, faster response times, increased productivity, and enhanced customer satisfaction. However, fulfilling this promise is a whole other story. There are still pitfalls to the implementation of hyperautomation practices, which can lead to lost investments and frustrated stakeholders. This article aims to help you get started with a practical starting guide and help you navigate these pitfalls, and finally, arrive at the promised gains through a real use case example.

First off, let’s start with the goal of your automation initiatives. Automation should be seen as a means to an end, not the end in itself. Managing automation initiatives is a balancing act between assessing their impact and understanding the effort required. Clearly defining the way requires that you determine both the effort and impact of an automation initiative, and for the latter, you would need to align the initiative with the strategic goals of the end-to-end process. This will drive alignment between your automation strategy and organizational strategy, and creates buy-in from all stakeholders.

For our use case, we examine the purchase-to-pay (P2P) process. P2P optimization focuses on optimizing the entire procurement process. This includes optimizing contracts, invoicing via the terms stated in these contracts and automatically generating purchase orders (POs). There are different KPIs that help evaluate the performance of the P2P process, such as invoice processing time or payments on time. These KPIs help determine the value of your automation initiative.

You have determined the impact of your initiative and are ready to start. Before diving into the solution, it is critical to have a firm grasp on the whole end-to-end process and the needs of its stakeholders. This is especially relevant for our use case. The P2P process typically involves multiple stakeholders, including requisitioners, approvers, procurement teams, and accounting departments, and can be complex. There are different methods that can help with this daunting task. Process mining is one of the tools within your automation toolset that helps with a data-driven approach to analyzing the end-to-end process. Process mining offers a holistic view, bringing to light interdependencies throughout the end-to-end process. The objective with process mining is not only to expose the flow of tasks and identify pain points in handoffs but also to uncover potential areas ripe for automation and to maintain consistency in metrics and key performance indicators (KPIs). However, data is nothing without the proper business context of your stakeholders. The application of techniques, such as the development of user personas, helps your team to understand what your stakeholders need and what problems they face in the current process.

When the end-to-end process is clearly defined and you understand the problems and needs of your stakeholders, you are ready to release the power of hyperautomation. Start with defining the process in its ideal form, without any waste or inefficiencies, with no regard for boundaries. With all your automation solutions at your disposal, such as RPA, low-code, AI and intelligent document processing, the sky is often the limit. However, automating your solution right away is not always the most optimal solution. Redesigning your process or even eliminating some steps entirely might add significant value for your stakeholders, potentially even before any automation solutions are employed. Now that your ideal process is mapped, you can start with looking at the different constraints that limit the possibilities. Take our P2P use case as an example. In an ideal world you want to apply electronic invoicing for all your suppliers. However, this may not be possible and you need to process PDF or even paper invoices. This potentially requires a different automation solution.

Another key factor at this stage is finding the right automation solutions within your use case. This will mean that the most advanced solution will not always be the right one. It’s possible to use an AI model for a simple task, but why do so when a more efficient solution, like RPA, can handle it perfectly? Similarly, it might seem ideal to integrate a low-code application with an ERP system in some specific cases, it may not be the most cost-effective approach in the short term. Therefore, turning to RPA might be the more suitable solution you need at this moment. To navigate this balancing act between technical feasibility and economic viability, it is important to involve the right stakeholders. Business users, enterprise architects and security officers all bring important viewpoints to this discussion.

Let’s go back to our P2P use case one last time and see how our new end-to-end process looks in practice:

1. Creating a requisition: In the first step of the P2P process, employees looking to make a purchase requisition use a custom low-code portal to provide them with only the most relevant information. Using an API integration, the purchase requisition is finalized in the procurement system (i.e., ERP system), ensuring adherence to the internal approver’s Service Level Agreements (SLAs) and fostering data centralization. This streamlined and automated approach not only enhances the efficiency of internal workflows but also contributes to faster decision-making and improved SLA compliance. 
2. Creating and sending a purchase order: RPA then steps in to automate a variety of order management processes. It takes over duties such as order entry, credit checks, stock checks for order fulfilment, and pricing calculations. By doing so, it minimizes manual involvement in creating and sending the Purchase Order (PO), resulting in significantly improved operational efficiencies.
3. Order confirmation and tracking: When the vendor confirms the order, the system automatically checks and compares the order confirmation to the PO. Meanwhile, process mining helps monitor and analyze event logs across multiple systems and processes. For instance, identifying patterns and discrepancies in delivery times is an area that helps organizations achieve more transparency and consistency in their metrics – and is also enabling them to gain real-time insights into delivery performance. Automating actions based on this information, such as updating the planning or informing the team, can help in facilitating better resource allocation and potential cost savings.
4. Goods receipt: While receipt of goods is often captured in the procurement system, many organizations have two systems in their P2P cycle, one for placing orders and one for receiving and processing invoices. RPA automates the registration of goods, reducing manual data entry time and rework of errors needed by employees.
5. Receiving and approving an invoice: Upon receiving the invoice, an automated check is immediately conducted to align the PO, receipt, and invoice details. Though using electronic data interchange (EDI) to place orders and receive invoices is the preferred method, sometimes a structured format isn't available. In these situations, intelligent document processing (IDP) technology comes into play, processing incoming unstructured documents. It expertly classifies vital invoice details like number and amount using machine learning algorithms. Once the invoice is processed, workflow automation tools take over routine approval tasks such as receiving, booking, and transferring information to the procurement system. 
6. Payment: In the last step of the P2P process, RPA checks whether the invoice has been paid, allocates the money received and closes the order.

During the process – a chatbot can act as a virtual buying assistant, guiding employees through the requisition process. It helps to identify the right products and streamlines the requisition process, potentially reducing errors and saving time.

Looking back at our goals for this initiative: How did we do? By using the different automation solutions, we were able to drastically decrease the throughput time of the end-to-end process, leading to a lower invoice processing time and an increased number of payments on time.

This practical user guide will help you start with your hyperautomation journey, but it is just one piece of your automation puzzle. To fully reap the benefits of hyperautomation, a broader organizational transformation is needed. Navigating this transition towards digital process excellence begins with understanding your organization's current standing in adopting hyperautomation. KPMG's Hyperautomation Maturity Scan is designed to do just that. It provides an initial assessment of your organization's performance in implementing comprehensive automation strategies and contextualizes your position within the broader industry landscape. At KPMG, we understand that merely implementing tools is not enough. We delve deeper to comprehend your unique organizational needs and assist you in enhancing the value derived from your current and future automation efforts.

With the results of our Hyperautomation Maturity Scan, you will have a more concrete understanding of where your organization stands on the Hyperautomation Maturity scale, which steps you need to take to level up, and how to maximize your return on investment from the hyperautomation journey. If you are ready to unlock your automation potential and take its implementation to the next level, we invite you to leverage the KPMG Hyperautomation Maturity Scan. Let us aid your organization not only to catch up with the pioneers of hyperautomation, but also to become a leader in the digital transformation landscape.