I have long been on a savage journey looking for the heart of service management, and I’m approaching a hairpin turn.
With Chat GPT’s help, let me explain.
[Note: You can find out more about the heart of service management at a FREE USM Workshop, by taking an APMG Certified USM Foundation class.]
The frenzy over artificial intelligence (AI) and robotic process automation (RPA) are waves of technology change that drive creative disruption. The impact to various streams of related activities (i.e., processes) in the enterprise is most apparent at two levels, and I can use the APQC Process Classification Framework (PCF) to illustrate.
In truth a process is quite simple. It has triggers (inputs), a series of activities, outputs (or outcomes), and is placed under control. But a process can be any stream of related activity, and for over half a century we’ve been beating this poor bastard to death.
We’ve applied swim lanes, diagrams, artifacts, and all kinds of graphics to illustrate how the process works in practice (getting back to ‘pure process’ is discussed at length in Demystifying the term PROCESS).
The Process Classification Framework (PCF) categorizes processes into various levels of granularity, ranging from high-level business categories to detailed work instructions.
As change accelerates at both the business category (upper) and procedure/work instruction (lower) levels due to factors like AI and RPA, it increases the importance of simplifying and standardizing processes, which sit in the middle of the PCF.
AI can have a transformative effect on entire business categories by automating decision-making processes, optimizing resource allocation, and providing data-driven insights. For example, AI-driven predictive analytics can significantly impact supply chain management, sales forecasting, and customer relationship management.
When AI is applied at the business category level, it often requires that processes within that category are simplified and standardized. This is because AI relies on structured data and well-defined workflows. To effectively harness AI's power, organizations must streamline their operations, data, and decision-making processes. Complex and non-standardized processes can hinder AI adoption and performance.
Robotic Process Automation (RPA) focuses on automating routine, rule-based tasks at the procedural and work instruction level. RPA bots mimic human actions, interacting with various systems and applications to complete tasks. This can lead to a more efficient and accurate execution of these tasks.
To implement RPA successfully, organizations must have clearly defined and standardized procedures and work instructions. RPA bots rely on consistent inputs and structured processes to function reliably. Any ambiguity or complexity in these processes can lead to errors or inefficiencies in automation. Therefore, simplifying and standardizing procedures and work instructions becomes a prerequisite for RPA deployment.
Middle-level processes act as a bridge between high-level business categories and low-level procedures. They help translate high-level business objectives into actionable steps. When change accelerates at both ends of the spectrum, these middle-level processes become crucial for ensuring smooth interactions and data flow between AI-driven strategies and RPA-executed tasks.
Middle-level processes need to be simplified and standardized to facilitate efficient communication and data exchange. They serve as a crucial link, ensuring that the insights generated by AI at the business category level can be effectively translated into instructions for RPA bots at the procedure/work instruction level.
As AI and RPA accelerate change at the upper and lower ends of the PCF, the middle-level processes become the linchpin for effective integration. Simplifying and standardizing these processes is essential to ensure seamless coordination and data flow between AI-driven strategies and RPA-executed tasks. This not only maximizes the benefits of AI and RPA but also enhances overall operational efficiency and agility.
Finding the Heart of Service Management – (or, what Chat GPT won’t tell you)
While the USM method has been successfully deployed in the Netherlands and Europe for over 8 years, it was only recently translated (2001) into English. So, it’s not something that Chat GPT will tell you about; (be careful of heading into a hairpin turn at 100 miles an hour)
“As of my last knowledge update in September 2021, I do not have specific information about the “SURVUZ Foundations’ Unified Service Management method” or its associated process model and standard workflows. However, I can provide a general understanding of how unified service management methods, process models, and standard workflows can help address the scenario described in a service management context. Please note that any specifics related to SURVUZ Foundations‘ approach would require access to more up-to-date and detailed information.”
ChatGPT
A unified service management method encourages organizations to take a holistic view of their services, considering both high-level business objectives (as accelerated by AI) and the granular tasks (impacted by RPA). This helps in aligning service management with overall business goals.
It promotes the integration of different service management functions, including service design, service transition, service operation, and continual improvement. This ensures that changes at the upper and lower levels of the PCF are smoothly integrated into existing service processes.
Unified service management often involves the establishment of standard processes and workflows. Standardization ensures that services are delivered consistently, whether they are affected by AI-driven strategies or RPA-executed tasks. Standardized processes are also easier to automate and optimize.
A process model provides a visual representation of how processes within an organization work together. In the context of unified service management, a well-defined process model helps in several ways:
Clarity: It provides a clear and shared understanding of how services are managed, which is essential for teams working with AI and RPA technologies.
Alignment: The process model can be used to align processes with the strategic goals of the organization. When change is accelerating at different levels, this alignment ensures that service management processes remain effective and relevant.
Change Management: A process model makes it easier to identify areas that need modification or improvement in response to changes brought about by AI and RPA. It allows for controlled changes to be made, reducing the risk of disruptions.
Standard workflows refer to predefined, documented sequences of steps for carrying out specific tasks or processes. In the context of unified service management, standard workflows offer several advantages:
Efficiency: Standardized workflows enable teams to perform tasks consistently and efficiently. They reduce the chances of errors and delays.
Scalability: When AI accelerates change at the business category level, standard workflows can be quickly adapted to accommodate new service offerings or modifications to existing ones.
Integration: Standard workflows ensure that the various components of service management are synchronized. This is crucial when dealing with the interplay between AI strategies and RPA tasks.
A unified service management method, process model, and standard workflows play a pivotal role in addressing the scenario described. They provide a structured and organized approach to managing services, ensuring that changes at the upper and lower levels of the PCF are effectively integrated, aligned with business goals, and executed with efficiency and consistency.
“However, the specific application of SURVUZ Foundations’ approach would require a detailed understanding of its principles and practices beyond the scope of my current knowledge.”
ChatGPT
Looking for the Heart of Service Management?
The non-profit SURVUZ Foundation’s Unified Service Management method provides a simple method for establishing an enterprise-wide service management system that is consistent with and complimentary to existing frameworks and practices.
USM enables the enterprise to get in control of its service delivery, with a management system of 5 processes and 8 workflows. It is a methodical approach that is based on a service management architecture that establishes a service management system.
USM provides a standardized, unified link for sustainable supply chains in service ecosystems. The process model and standardized workflows are used by any service provider, leveraging any combination of practice frameworks and any organizational topology.
USM is owned by the non-profit SURVUZ Foundation, who manages the specification of USM, focuses on quality control, and oversees adequate support in practice. As a community effort, the SURVUZ Foundation offers free USM resources on the condition that you’re willing to share your experience and lessons learned with other USM users.
This enables the enterprise to choose what resources to use; self-install, train-the-trainer, or fully supported implementations. USM allows you to combine any selection of practices from other frameworks.
For more information or a Free Consultation, contact MyServiceMonitor