Has your organization clearly defined and configured roles, agreements and responsibilities? Have all processes been mapped out? Are the techniques and skills in place for effective data management? And are you still running into poor data quality despite it all? Are you still using data quality reports as a worklist to improve data quality?
You are not the only one; we regularly encounter this in actual practice. Even in organizations that have all their processes structured properly and have data management and data governance in place, employees still perform repetitive manual actions on a daily basis. This includes logging into different systems (ERP and others), processing data (often combined with copy/pasting), and switching between various systems and/or applications. Organizations with mature data governance programs are no exception.
This is because companies do focus on data governance and data management, but then fail to take the next step and optimize their processes. In other words, they don’t always consider how to optimize data management and automate steps by inserting a ‘robot’ at the appropriate points. One method to get there is Lean Six Sigma, which looks at which steps in your process add value for customers. Organizations that dive into this can clearly see which of their employees’ repetitive manual actions do not add direct value for customers. Even so, these steps in the process are indispensable. When that is the case, automation is the solution.
Automating repetitive actions
Organizations that automate repetitive operations are more able to focus on their customers. The concept of automating these repetitive manual operations is also referred to as robotic process automation (RPA). A good example is configuring a setting in the master records for your customers. For example, when a sales order is created, this setting ensures that the system automatically looks up the correct, agreed prices for that customer.
Although the name might suggest otherwise, RPA is unrelated to physical robots. RPA causes scripts or applications on the computer to perform repetitive manual operations. This provides a number of benefits – not only accelerating the operations, but also 24/7 availability.
If you use the business rules (as defined in data governance) in RPA, the ‘robot’ will follow these rules scrupulously, without error – as long as the process remains unchanged after applying RPA. Better yet, nothing else changes in the IT landscape; systems do not need to be modified or replaced, and won’t become redundant. And if the ‘robot’ encounters something it can’t resolve, human employees can always step in.
RPA in practice
What does RPA look like in practice? As an example, let’s look at creating a new product entry. The employee manually creates the item in the system, often by referencing an e-mail and/or an Excel file sent by a requester. This requires the employee to input data into many different fields, sometimes as many as several hundred in total! No matter how experienced the employee is, it is still challenging to complete all the steps for creating the product entry and wrapping up any specific processes or sub-processes without any errors at all. A subprocess might be creating an info record for a newly created item.
Working smarter with web forms
Using RPA, these manual actions can be replaced by a web form that only contains the fields that cannot be automated, such as a product description. As a result, the employee no longer needs to skim through the hundreds of fields normally required to create a new product. Other fields, that do need to be manually updated when creating a product entry, can be automated using business rules. Examples include MRP settings for products that are always the same.
In the new situation, the requester no longer sends the employee an e-mail or Excel file; instead, the request is submitted via a web form. Once the employee reviews and confirms the form, the robot creates the product in the system or makes adjustments based on the business rules. Any additional data objects that are required, such as an info record, are also included right away. These tools are usually accompanied by a workflow solution. This makes it possible to automatically send emails to employees to retrieve data so that the robot can move on. RPA can also automate communication. Once the data object has been created, the robot sends an e-mail with the newly generated data to the employees responsible.
Operating on this basis:
• It is easier to draw up SLAs
• The speed of creating data objects is dramatically accelerated
• Data quality improves
• There are fewer risks that processes will crash
• There are fewer errors and risks, and no unnecessary costs
• Employees can focus on the customer or on other important work
• RPA is scalable, even with exponential growth
• RPA can be implemented quickly in situations involving strong data governance/management and no/low code RPA application
The process described above is an initial guideline. Actual implementation requires a solid understanding of the different factors involved, so organizations often struggle to complete it on their own. Our consultants have years of experience with workflows and RPA and have successfully completed these types of projects in various contexts.
Is your organization planning to start working with RPA process automation, and could you use some support? Make an appointment now to discuss the options, no strings attached!