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Enterprise motivation to pursue hyperautomation

In Atos's thought leadership paper, Journey 2024: Redefining Enterprise Purpose, we predicted that enterprises will need to adjust their market ‎strategies and reassess their value chains, which may push their strategic intent beyond their current capabilities. Accordingly, their IT systems must become agile enough to accommodate these changes and scalable enough to support the ‎streamlined business processes that deliver increased customer satisfaction.

Hyperautomation may be part of the ‎solution.‎ Consider this:

An example of a specific strategic intent could be to employ no-human-touch, hyperautomated operations to increase efficiency, ‎reduce costs and improve overall performance.

Hyperautomation involves using advanced technologies such as digital ‎decisioning and machine learning to automate processes, decisions and tasks. By automating repetitive, time-consuming ‎and error-prone activities, enterprises can free up employees to focus on more strategic and value-adding work. ‎Additionally, hyperautomation can help an enterprise make better and faster decisions, improve customer satisfaction ‎and increase agility and scalability.‎

Hyperautomation uses technologies like digital decisioning and machine learning to automate ‎processes, decisions and tasks — freeing up ‎employees for more strategic activities and helping enterprises ‎make better, faster decisions.

How hyperautomation ties into the Business Motivation Model

The Business Motivation Model (BMM) is a framework that describes the relationship between an enterprise's ‎strategic intent and the underlying motivations, goals and objectives that drive that intent. In the context of ‎hyperautomation, the BMM would suggest that the strategic intent of an enterprise to pursue hyperautomation is driven ‎by specific motivations, goals and objectives related to increasing efficiency, reducing costs and improving overall ‎business performance.‎

The BMM has a hierarchical structure with strategic intent at the highest level — and the motivations, goals and objectives that drive it are arranged in descending order of specificity. One of the key components of the BMM is the goal ‎model, supporting Peter Drucker’s management by objectives (MBO) system, explained in his 1954 book,

Now, let’s look at hyperautomation through the BMM lens.

At the highest level, the strategic intent of an enterprise pursuing hyperautomation is driven by a desire to improve ‎overall performance, possibly motivated to compete more effectively in the ‎marketplace or to increase profitability and growth.‎

At the next level, we can identify specific goals and objectives related to increasing efficiency, reducing costs and improving ‎performance. These could include goals such as reducing or eliminating manual errors in a ‎process, improving decision making accuracy and speed, and increasing customer satisfaction.‎

Finally, specific motivations for achieving these goals and objectives would be identified at the lowest level, such as a need to reduce labor costs, a desire to improve operational efficiency, or a goal to ‎increase market share.‎

As you can see, BMM provides a way to understand the relationship between an enterprise's strategic intent and the underlying ‎motivations, goals and objectives that drive a hyperautomation initiative. It also helps understand the ‎motivation behind the implementation and what the enterprise aims to achieve with hyperautomation — thereby providing a solid basis for the endeavor.

Hyperautomation requires vision

Hyperautomation is not a quick fix or a “magic bullet.” It requires thorough planning and can be quite resource-intensive before it is implemented well enough to deliver sustainably, so the vision and business motivation must be clear up-front.

Hyperautomation and digital methodologies are essential to promoting sustainability, by enabling organizations to operate more efficiently and reduce waste. However, it is also vital to ensure that these technologies are used responsibly to support sustainability goals. In addition, the ethical, legal, and social implications of hyperautomation must be considered and included in the business motivations, goals and objectives.

In upcoming blogs, we will explore various ‎aspects of sustainably implementing hyperautomation, including themes such as advanced hyperautomation ‎technologies, balanced with agile implementation and maintenance methodologies to increase sustainability. We will also look at, the governance and constraints inherent to hyperautomation as well.‎

Watch this space for more.

By Peter Kalmijn, Senior Digital Business Analyst

Posted on: February 13, 2023

 

 

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About Peter Kalmijn
Business Engineer of the Digital Transformation and member of the Scientific Community
Peter is a qualified and experienced professional specialising in digital transformation. He is a visual-spatial thinker with an international multi-cultural background. Combining his keen interest in IoT, Automated Operations, Digital Decisioning and Business Rules with over 30 years of IT experience gained in business- and software engineering, Peter has authored various papers and articles and has spoken at events. Additionally, he is the lead trainer of Atos’s Digital-Decisioning-related courses. As a long-time member of the Atos Scientific Community, Peter led the track on augmented humans and co-bots for Journey 2026. Within the Atos Expert Community, he serves as the global head of the Architecture and Business Analysis sub-domain of Application Modernization Systems. As a thought leader and guild lead of Digital Decisioning at Atos, Peter is dedicated to helping innovative clients achieve their business vision and goals of highly automated operations with BPMN, DMN, and CMMN and implementing hyperautomation.


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