Decision making with intelligent processes in SAP S/4HANA
It has been 20 years since Parasuraman, Sheridan, and Wickens published their seminal paper on the levels of human interaction with automation1. In the age of intelligent processes and artificial intelligence (AI), their findings remain as relevant as ever. To mark the anniversary, this post considers the balance of automation in the decision-making process and how the end-to-end business process view influences the approach to automation. For when a business process becomes intelligent, the outcome is put into focus.
As humans, we understand the benefits of lifelong learning: broadening one’s horizon typically improves the ability to adapt to change, or, better yet, create the change. The same principle applies to businesses: markets evolve, regulations change, and new technologies emerge. In both cases, learning starts with data which, when processed and put into context, becomes information. Ultimately, information can become knowledge. And so, the continuous learning from data enables the continuous improvement of business processes. In both contexts, this continuous improvement is considered a key aspiration.
Humans play a major part in this process of learning and improving. Specifically in the business context, we can think of them performing a task somewhere between being fully manual to fully automated. Therefore, we design intelligent processes around three core capabilities: assisting end users in their decision making, adapting business processes based on new information, and automating tasks both within and in between systems.
A vision for intelligent processes in SAP S/4HANA
Intelligent processes are based on four key principles:
- Enterprise-grade AI offers the scalability, robustness, and lifecycle management to run intelligent processes at some of the largest companies on the planet.
- Outcomes describe the tangible value of intelligent processes and capabilities.
- Trust is central - be it the domain expert's trust in the predictions, decision proposals, and results, or how we acquire, handle, and process data according to laws and regulations (e.g. GDPR) and adhere to the SAP guiding principles for Artificial Intelligence (AI).
- Native embedding and integration of intelligent technologies in end-to-end business processes in SAP S/4HANA as well as the integration between these technologies result in ease of use and ease of expansion.
Intelligent end-to-end business processes in SAP S/4HANA
SAP supports a business user's decision-making and helps them become more efficient with each incremental step towards automation and intelligence. That support can be in the form of reducing manual and mundane tasks, solving complex ones more quickly, or simply providing contextual, proactive information at the right time.
What, whether, and how to automate – and to what degree?
These are the typical questions that customers bring to conversations about automation. To answer them, let's borrow from the field of human interaction with automation1. There are four stages in every decision-making process: information acquisition (in our context: data acquisition), information analysis, action planning (in our context: decision making), and action execution. The same applies to our concrete case of making business processes more intelligent. There are some tasks in which a business user just needs to upload a file into the ERP system, for example an invoice. Other steps, such as approvals, require the user to make a more complex decision. For each of these four stages, you can describe the level of automation: From fully manual (level 0) to fully automated (level 5), and interim levels (comparable with autonomous driving). A level of required or desired automation must be determined for each task. User research and expert interviews are great tools for finding that balance.
Automation levels of human decision making
To be clear: Full automation of all tasks in a process might not be required, might not be feasible, or it simply might not even be desired (e.g. for legal or ethical reasons). Introducing a low level of automation to a manual task or increasing existing automation from level 2 to 3 or from 3 to 4 can already yield significant business benefits. While this might sound logical, it is still quite abstract. So, let's make it tangible and look at a concrete example from the shared services space where SAP customers have implemented these ideas and concepts.
Example: How a global car manufacturer has reduced effort for vendor inquiries by 25% using intelligent processes
Imagine you are running a shared services organization that is transforming into a truly customer-centric organization, enabled by processes that are digital, intelligent, and highly automated. Your goal is to provide services for any key business process out of any regional delivery center. Naturally, you're expected to increase service quality while reducing costs at the same time. As your business grows or encounters challenging times like in the current pandemic, this likely means an influx of additional inquiries to deal with. Long gone are the days of receiving just e-mails, tickets, or phone calls. The reality today is omni-channel, multi-format with easy extensibility of long-tail processes via form-based low-code capabilities. So, if all the core business processes run in your ERP system (e.g. SAP S/4HANA), why exit this environment to manage your shared service processes? Shared Services Framework for SAP S/4HANA provides a natively integrated solution, and a one-stop shop for your customers and agents.
How can we best support shared services organizations in this context?
- The best inquiry is the one that can be resolved before it reaches your shared services organization.
Example: assist the customer via ‘self-service’. - If you can’t proactively avoid an inquiry, solve it with the highest degree of efficiency and customer satisfaction.
Example: automate aspects of the agent’s tasks.
Service delivery with embedded intelligence in SAP S/4HANA Shared Services Framework
A global manufacturer of luxury cars based in Germany was looking for a way to transform their shared service process for vendor inquiries in order to increase service quality by reducing manual steps in this process2. In addition to offering a modern user experience for both suppliers as well as agents, the company was looking for ways to better support suppliers before they submit an inquiry. Since implementing SAP S/4HANA Shared Services Framework with embedded intelligence, the shared service organization has seen a 25% reduction in the effort required for handling vendor inquiries.
How did they achieve such efficiency? Let’s look at this through the lens of two personas; the supplier and the agent. How could the shared service organization make it easier for a supplier to find answers to the most-common questions, so the supplier would not even need to submit a ticket or pick up the phone? While static, digital information such as Frequently Asked Questions are already a good start (data acquisition on level 2), the automation of this step can be further increased to level 4 using a chatbot as part of SAP S/4HANA Shared Services Framework. If the supplier is looking for additional information that the chatbot is unable to provide, they have the option to still create a ticket.
In this case, the agent should be equipped such that they are able to answer the question in an efficient way - after all, time is money. In the case of this car manufacturer, this has meant strategically increasing the level of automation for information analysis through the use of intelligence from a semi-manual (3) to a semi-automated level (4). Under the hood, this capability is provided by SAP AI Business Services business entity recognition and service ticket intelligence. Let’s take this further and think about opportunities in the decision-making stage in which the shared service agent decides how to respond based on their previous analysis of the request. Here the system can recommend possible responses (solutions) to the agent based on historic responses to similar inquiries (increase automation from level 2 to level 4). This further reduces the time to respond and increases customer satisfaction.
Making conscious decisions on what, whether, and how to automate and to what degree is a key step on the journey to increasing intelligence in your end-to-end business process – whatever your individual strategy and objectives may be: increasing top-line growth, pure cost optimization, or freeing up time to increase the personal relationship with your customers and suppliers in this current climate.
What would reducing the shared services effort by 25% mean for your business? Having additional budget to develop that new product ahead of schedule? Or expanding more quickly in a growth market?
One of the questions we frequently hear is: “How do you describe the value of intelligent processes?”
Now that we have a common understanding of human decision-making and the degree of automation, the next blog post will focus on the business value of intelligent processes. This will equip you with methods and tools you can incorporate in your own journey towards leveraging intelligent processes in SAP S/4HANA.
Sources
1 Parasuraman, R., Sheridan, T.B. and Wickens, C.D., 2000. A model for types and levels of human interaction with automation. IEEE Transactions on systems, man, and cybernetics-Part A: Systems and Humans, 30(3), pp.286-297.
2 SAP SE, 2020. Rise to the challenges of uncertainty with financial readiness. SAPPHIRE NOW Converge; video (start at 49:47).
This is the second post in a blog series focused on intelligent processes in SAP S/4HANA, aimed at sharing more details on our vision, how you can enable intelligent process thinking in your organization, and how you can get started in your environment. In the previous post, I introduced the concept of intelligent processes in SAP S/4HANA as a way to increase the level automation in your business processes end-to-end by using natively embedded capabilities.
Andreas Welsch is Head of Intelligent Processes, SAP S/4HANA Product Management.
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