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The Order-to-Cash Process
Document No.: Y212
Published by The Open Group, November 2021.
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This Case Study is based on a real-world example to illustrate the use of domain-driven design and event storming in the context of Digital Transformation. It focuses on the tire production company, Michelin, and in particular the order-to-cash process.
Although the concepts presented in this document address the typical concerns that correspond to the order-to-cash process and a tire production company, they could be applied to different situations.
This work supports The Open Group Open Agile Architecture™ Standard application.
Several years ago, we revisited the information system that supports our order-to-cash processes. We used to have a legacy monolith (hosted on a mainframe) supporting most of these processes. We decided to adopt a best-of-breed approach, where several solutions were implemented to support the different parts of these end-to-end processes: from order capture to transportation optimization up to logistics delivery. This move helped us to:
• Source the best software to support a subset of our processes
• Start decomposing our monolith, enabling us to change parts of our processes at a difference pace
As soon as there are several systems contributing, a central component is needed to ensure the overall execution. In our case, a central orchestrator, a Business Process Management (BPM) tool, was used to steer the execution of these processes and deal with differing object granularity. This may seem like a minor problem, but we do not manipulate the same object all along the execution of our processes: a customer order may have three lines (one line per item) that will be split for transport optimization into four lines (for instance, one customer order line being sent in two truckloads).
The introduction of the orchestrator was also believed to be necessary because the team building the contributing applications had lost the knowledge of the business rules they had to implement, which manifested into the creation of a team in charge of the orchestrator to enforce these rules.
After several years, different issues were occurring with this approach, especially around the orchestrator:
So, we decided to rethink our architecture around the concept of events and their choreography, as we wanted to get rid of the orchestrator. The approach we took can be regarded as a recipe that we tried, but bear in mind that we do not pretend to be a three star restaurant.
We used the domain-driven design approach for this architecture refactor. We know there are different ways to practice domain-driven design depending on the state from which you start, and the assets you already have. In the following sections, we will describe the different steps we went through.
In this section, we discuss the order-to-cash domain and the definition of its boundaries (even from a very high-level perspective). The context begins with the capture of sales orders by customers and goes up to the payment of the invoice. The work group decided to take the processes as a hypothesis, to ensure we have the goods/products at the right time and at the right moment, and how to allocate our inventory to customers that were considered out of scope. These belong to other domains with which we have relationships.
The event storming practice is useful to explore and discover your domain. But in our case, even when we started by describing the process, our efforts quickly became focused on the information that was passed all along the process. Sharing the execution of the process made it possible to highlight the information granularity we had to deal with at each step, as well as the temporality of events:
Figure 1 illustrates the different objects we are dealing with, their granularity, and how they are interconnected.
The granularity changes, along with their associated vocabularies (i.e., the ubiquitous language), helped the work group to decompose our domain into three sub-domains: Customer Orders, Customer Deliveries, and Customer Invoices.
Sub-domains often have dependencies, and so we defined for each relation which sub-domain is upstream relative to the other. The nature of the relation is also important, and to qualify it we used a strategic integration pattern. There are nine patterns in total but, in our case, we ended up using only four: Conformist, Anticorruption Layer, Open Host Service, and Event Published. The domain, along with its sub-domains for which relations are defined through integration patterns, forms a system context map. Figure 2 illustrates our case.
As you can see in Figure 2, not only do we have the domain described in the system context map, but we also find the teams realizing the domain – that is the team context map. Mapping teams is useful to identify any inconsistencies; for example, several teams working on a domain.
Indeed, during the previous stage, we found ourselves describing the objects we had to manipulate as part of the process, rather than identifying the business events themselves. So, to complete the approach, we had to complete the event storming. Figure 3 shows the result of this session.
The red sticky notes represent the main business events of the domain, and visually you can see the sequence of events. You will also recognize two of the sub-domains that were mentioned before: Customer Order and Customer Deliveries. We have also grouped events by the applications receiving them.
As event storming is used to discover and describe a business domain, it has very few Information Systems/Information Technology (IS/IT) details. So it is quite common to describe the events chain in a more “technical” manner. An IT event storming helps to highlight the information expected by each solution, the need to store this information or to request it, the data and Application Programming Interfaces (APIs) made available, and the events carried out.
Here, it is important to remember that our objective was to implement an event-driven architecture. It is quite common to rely on technologies such as Apache Kafka® to support it. One of the central concepts of Apache Kafka (or a similar technology) is the topic. It is the “container” in which you publish and consume your events. Figure 4 lists the topics we will be using.
We have a business domain decomposed into sub-domains and described through the main business events. The next and last step for us was to describe each bounded context so we know which events it receives and emits, which APIs it consumes and exposes, and which commands it executes. The Bounded Context Canvas (see Figure 5) is especially interesting as it also lists the domain entities or value objects it uses (using the domain “Ubiquitous Language”) and the “Business Decisions” (rules, policies, and decisions) it supports.
(Please note that the links below are good at the time of writing but cannot be guaranteed for the future.)
• The Open Agile Architecture™ Standard, also known as the O-AA™ Standard, a standard of The Open Group (C208), September 2020, published by The Open Group; refer to: www.opengroup.org/library/c208
Thierry Fraudet, Michelin
Thierry has been involved in the IT Industry since 1992 in a wide variety of contexts and companies (from start-ups to large international companies), which has enabled him to develop significant experience and expertise in Information Systems Architecture as well as Software Engineering, from large-scale distributed information systems to embedded software.
Currently working as an Enterprise Architect for the IT department at Michelin, his main focus is to develop the long-term IT technologies vision, articulate transformation roadmaps, and deploy IT capabilities to support business strategy and innovative thinking. Prior to that, Thierry was leading the Lean & Agile Transformation. He has been named as a Michelin Fellow for his significant contributions to the transformation of his company. Since 2020, he has been a member of the Board of Directors of the Club Urba-EA, a non-profit professional association that aims to develop Enterprise Architecture practices in French companies.
Olivier Jauze, Michelin
Olivier is an IT Distinguished Engineer at Michelin with almost 20 years of experience in Software Engineering and Architecture. Passionate in finding solutions to users’ problems with technology, Olivier coaches teams in their journey to deliver incredible products and, for a couple of years now, platforms too. Involved in many initiatives around Michelin core business, Olivier is also working in the service & solution and consumer experience areas. Recognized as a disrupter, he is continuously pushing organizations to adopt new business models and new ways of working. Recently he worked on an open source project to help software architects dealing with today’s continuous nature of software delivery.
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