This article presents an Intelligent automation framework that defines four automation categories based on Organizational Innovativeness derived as a function of the core automation focus of an organization i.e. task, process, knowledge, or customer. The automation categories are discussed for their characteristics, value proposition and implementation examples with some insightful recommendations suggested towards the end.
Special thanks to Ralph Aboujaoude Diaz for providing valuable inputs in giving final shape to this article, Pascal Bornet for reviewing it, and Paul Barnett to allow citing his seminal work on “Valueism”
Reflecting on RPA and Intelligent Automation at the start of 2019, the adoption of these automation techniques has sharply increased in the last couple of years with significant growth in the number of customers and successful case studies. The provider landscape continue to evolve and expand with a variety of products and categories, and with many customers looking to go beyond a pilot stage into full scaled implementations this year. Task vs Process automation debate seems more unsettled then ever with the product strategies of some vendors now looking to shift gears more towards attended task automation from unattended process automation. And, providers with more Intelligent offerings cannot stress more about the importance of holistic end-to-end process automation achieved through data-centric cognitive automation technologies. Whilst task automation is most easily achievable with almost zero involvement from IT, more complex Intelligent automation technology adoption requires a good IT participation. In terms of key challenges faced if on one hand very low code task automation can often lead into maintenance overhead, end-to-end process automation on the other hand suffers from scalability issues with businesses soon realizing the inadequacies in their existing legacy processes needing a good overhaul before automation could be applied.
Whether the focal point of automation is task, process or data, from a strategic point of view, RPA and Intelligent Automation are providing organizations with significant cost savings and operational efficiency improvements. But, companies who are leading the fourth industrial revolution are the most innovative ones in the adoption of a range of newer disruptive technologies. They instead have customers as the focal point and are reinventing business operations to generate more value for their customers.
Innovation- the key to value creation
Innovation is about generating value by adopting a new idea or behavior that may pertain to a product or a service that an organization provides, or to the production processes or business operations that it undertakes. The new idea or behavior enhances or fundamentally changes the existing technological or domain knowledge making the nature of innovation as either incremental or radical.
When it comes to the question of what value to create, it is about generating value in broader terms than merely monetary value, as Paul Barnett explains in his concept of “Valueism”. In Paul’s words –
Valueism asks every business and organisation in every sector to recognize that the only reason it exists is to create value in some form or another – probably several forms, and certainly not just monetary value.
The primary focus must be customer value since, “the only purpose of a business is to earn and keep a customer” as management guru Peter Drucker famously said. But it must also extend to all other stakeholders upon whom the business depends to create that value. To serve the interests of all stakeholders is the only way to ensure the business model is sustainable over the longer-term.
Paul suggests considering value beyond monetary profits and looking at a corporation’s wider social impact. This includes the impact on humans (customers and employees), on the environment, and on the third parties involved.
Achieving a sustainable competitive advantage through value creation is very much linked to the ability to innovate. Time and time again, numerous businesses and institutions claim innovation to be their key to success and profitability. There is no question that the need to innovate is so very essential for businesses that must change how they operate in the current technologically disruptive business environment in which a range of new technologies are shaping up the future of work in the form of a fourth industrial revolution. Holding back on innovation and focusing on short term efficiency gains only is not sustainable strategy especially for businesses facing disruption.
Intelligent Automation – Are you being Innovative?
In the pursuit of Digital transformation, organizations need to continuously improve existing business processes by exploiting proven automation technologies to reduce operational cost and increase efficiency to stay competitive in the short term. But more importantly, organizations need to re-invent existing business processes by exploring the adoption of newly emerging disruptive technologies to continue to stay profitable in the long term.
When it comes to exploiting existing automation technologies in an effective way, it often requires re-configuring existing business processes, so they can be made faster, cheaper and better through automation. Such incremental process innovation is generally a problem-solving process in which existing processes are adapted to address the recognized needs for automation within an organization. As such, the adoption process needs more planning, and can be characterized by process selection, reﬁnement, automation development and execution. A timely assimilation of the automation technology into the organization is a critical factor in this case in order to produce the desired organizational change.
But when it comes to exploring new disruptive automation technologies, it is about re-imagining existing processes through experimentation and innovation, so they are modernized and brought up-to-date to the changes in the market conditions caused by disruptive technologies. Such radical process transformation through new technology is a creative process in which new and existing ideas are combined in a way that it produces operational conﬁgurations that were previously unknown. This can be characterized by research, discovery and experimentation, and a longer-term approach to be able to withstands failures along the way.
Being an “innovative organization”, in the context of Intelligent Automation, requires both Innovation-generating abilities to transform existing business processes, as well as Innovation-adopting abilities to embrace new disruptive technologies.
The following section presents the Intelligent automation framework based on Organizational Innovativeness derived as a function of organization’s core automation focus i.e. task, process, knowledge, or customer. The different automation categories being derived are discussed below in a tabular form for their various characteristics.
An Intelligent Automation Framework based on Organizational Innovativeness
Reference Links for Implementation Examples
 Three use cases for attended automation
 Five successful use cases on RPA implementation
 Cognitive Virtual Assistant case study
 Unstructured data processing case study
 Alder Hey Children’s Hospital- UK’s first Cognitive Hospital case study
 Amazon Robotics vision
- When adopting automation, organizations must consider value creation beyond monetary benefits to include the impact on the needs and well-being of customers, employees, environment and society at large
- Organizations who are at an Innovation- aspiring stage must make efforts to move to the next stage and start innovating when it comes to implementing automation
- Organizations who are already on the automation journey, and are at an Incremental Process Innovation stage to increase short term profitability through efficiencies, must also make efforts to move towards customer focused radical Process Innovation stage to transform existing business operations by embracing newer disruptive technological disruptions so they are profitable not only in the short-term but continue to stay competitive and profitable in the long run
- Organizations should look to leverage strategic partners when embarking on the Intelligent Automation journey to help provide the breadth and depth of skills needed to drive innovation and to overcome the key challenges faced at different stages of automation
- Maintainability, interoperability and scalability of automation are critical success factors to move to different innovation stages
- Deployment of an overall “Automation” governance framework is essential to ensure that risks (regulatory, reputational, etc.) are appropriately addressed
- Customers must focus on building “Resilient” software robots. Deploying “clumsy” and monolithic automation, that is hard to maintain and scale, negatively impacts the ability to innovate and lowers the trust in automation with more time, effort and money spent on recovering from failures than moving into the next automation stage
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Deepak is a highly accomplished IT professional with 15+ years of experience in Software based Automation- Test & RPA. Majority of Deepak’s automation career has been focused on Enterprise Applications such as SAP, Siebel, PLM, Custom Wealth & Asset Management platforms, Healthcare Claim Processing systems, and other similar IT systems. Over the years, Deepak has worked in a variety industry sectors and well known global businesses across US and UK namely Barclays, IFDS, Department of Works and Pensions, RWE Npower, Motorola, UnitedHealth Group.
Deepak holds a Bachelors in Computer Science & Engineering from BVP Delhi, and a Masters in Strategy & Innovation from SAID Business School, University of Oxford with distinction in Innovation Strategy.