How should managers implement an Intelligent Automation strategy?
Daniel J. Power
Intelligent automation (IA) is changing business operations and it is necessary to implement such systems to stay competitive in many industries. External forces and internal constraints too often result in "cobbled together", poorly integrated, and siloed automation capabilities. Intelligent automation (IA) technology usage will increase. Intelligent Automation is broadly defined as the combination of automation and related technologies such as Computer Vision, Cognitive automation, and Machine Learning to make intelligent decisions, thereby improving accuracy and eliminating errors. IA means the system can autonomously alter its state or actions in response to varying inputs and learned models.
Managers want to implement automation projects that maintain a high standard of quality and long-term adaptability and agility. Incrementalism and piecemeal implementation may be especially dysfunctional for large-scale Intelligent Automation (IA) projects. Working with a single automation vendor and a single automation platform has pros and cons and such an approach may not deliver significant long-term value. An integrated vendor strategy may lead to more innovative and more sophisticated operations. Ideally, new IA solutions will be sophisticated enough to adapt to novel situations and solve new problems. Some implementation suggestions include:
1. Craft a plausible enterprise intelligent automation vision. The vision must seem reasonable, but it should be challenging and motivating.
2. Embrace and promote technological change, intelligent automation, and digital transformation. Implementation involves a deep commitment.
3. Identify and prioritize IA use cases. There are many possible use cases. The key is to start with "winners", an IA application that shows strong positive results. In insurance that may be claims processing, in some businesses it may be resolving
customer requests, in a manufacturing setting it may be implementing sensors to create an intelligent automated production line.
4. Clarify and share widely the IA strategy and long-term goals. An organization's direction for intelligent automation must be finalized by identifying strategic initiatives.
5. Identify leaders who are change champions. Change champions encourage and facilitate change.
6. Develop a skill development program for current employees. Managers should encourage and reward employees for seeking new and enhanced skills relevant to IA.
7. Create a governance and testing framework. It is vitally important to successful IA to effectively manage the entire governance, testing and execution process.
8. Develop short-tern plans and projects and allocate budgets. A short-term plan generally allocates resources for a year or less. Use the plan to guide project activities, manage a project budget, and establish a baseline for measuring success.
9. Promote continuous improvement and seek feedback and collaboration. Emphasize small manageable, high-value improvements, and endeavor to remove barriers to those improvements. Organize continuous improvement teams and celebrate incremental improvement.
Overall, managers should be agile in pursuing an IA strategy. Managers should create opportunities and pursue the best ones. Our goal should be to create an IA system that is deliberately implemented with great care so the system adds real value. In general, managers should strive to unleash the creativity of in-house "experts" and in some situations consultants.
In summary, begin by identifying the "worst" case scenario for the selected IA strategy, document that scenario, and prepare for it, then go out and implement a "best" case, more optimistic scenario for the IA strategy. If implemented successfully, intelligent automation will be transformative and will make an organization more resilient.
References
Zubair, R. K., "Intelligent Automation and Change Management — Key steps," assistedge, November 29, 2019, at URL https://www.edgeverve.com/assistedge/blogs/intelligent-automation-change-management/
Last update: 2020-07-31 08:57
Author: Daniel Power
Print this record
Show this as PDF file
You cannot comment on this entry
