Keys to a successful RPA implementation in manufacturing automation

Many manufacturers are exploring RPA implementation to automate their work processes in various departments. RPA (Robotic Process Automation), has many benefits for businesses. These include cost savings, accuracy and throughput. They also meet audit requirements. Despite the increase in the number of companies embarking on RPA journeys, only a few have been able fully to reap the benefits of RPA through successful implementations.

A successful robotic process implementation is labeled as such when teams have established a repeatable methodology and practice which results in the production/automation of hundreds of tasks or processes. A roadmap that is sustainable can help organizations deliver a successful RPA implementation. The RPA implementation process can be divided into three phases: incubate (build), and optimize (optimize).
Incubation Phase
The development of proof-of-concept automations is the most common way companies begin their automation journey. This is usually done at the function level by someone who does not have a mandate or sponsor at an organization or department. The POC’s scope is not well defined. It usually involves the automation of small parts of a larger process that was deemed good enough for automation based upon subjective criteria. After completing basic trainings on various RPA technology platforms, most of the scope is self-implemented.
These organizations have difficulty implementing the proof of concept because there is no clear path to scaled adoption. They often look for additional processes to implement. They are unable to realize the benefits of RPA after automating only 4-5 processes.
Even though it can lead to program failure, this initial phase of RPA adoption is crucial. It’s important not to just get a start, but to get the right one. The first question an organization should ask before implementing RPA is “What can RPA help the Business?” rather than “What can RPA help us do?” This question is crucial in establishing the right mindset.
Phase 2: Build
When executed correctly, automation can bring endless benefits to an enterprise. The greatest challenge for automation firms today is to identify the right workflows that can be automated. After automating the most obvious candidates for automation, the business hits a wall and is unable continue the automation momentum.
Enterprises should develop an iterative process to continually review their processes in order to solve this problem. These activities should not only produce a list of automation candidates but also provide a detailed recommendation for overall task reassignment or prioritization to improve operations.
To identify the departments, a map of the entire company is a structured way to do this. Next, create a map of the entire organization with each department lead. Include a list of team members as well as the tasks they perform. Next, you can evaluate each task and determine if it is suitable for automation. The task should then be divided into different categories. Some tasks can be automated (does not require human judgment) and are repeatable. Others are intelligent, which requires human judgement. There will be tasks that are not of organizational use or inefficient. It would be possible to automate manual tasks and leave the Intelligent tasks for humans (or use AI as a next evolution of organizational automation, further described under Optimize phase). Then, eliminate unwanted tasks and rearchitect inefficient workflows to increase efficiency.
Optimize Phase
A mature automation practice should have a process identification methodology in place during the Build Phase. This will allow them to identify processes and classify them into three buckets: Intelligent, Mechanical, and Wasteful.
The enterprise automation focus has been on tasks that were strictly based on rules and leveraged structured data sources, when human interpretation is not required. These tasks were simpler to automate. These tasks were easier to automate. For example, it is simple for the system extract financial data when organized in columns and rows within a table. However, extracting the same information when presented in multi-page financial statements becomes more difficult and requires intelligence for contextual understanding. This is an example of how it works: A home appraisal company must evaluate the condition of a property as part of its appraisal process. An appraiser must physically inspect the house and label the property as “Good”, “Fair”, “Bad”, or “Bad”. These tasks were left for humans during the build phase. However, in order to optimize, an enterprise should now be able to automate these tasks. To keep a skilled workforce that is able to drive the manufacturer forward, it is important to upskill.
Automating cognitive functionality is the next step in building scaled RPA programs. It helps in realizing RPA’s true value. Cognitive functionality automations can help improve customer experience and provide seamless, fully connected workflows.
Moving processes to an automated environment may also open up new opportunities, such as the generation of operational insights. The data trail is not captured when a human performs a task. A data collection system should be part of an automation environment.

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