Top 5 Lessons Learned in Process Automation

So, you decided to learn more about Process Automation?

Congratulations, that means you appreciate the value that new technologies bring to the table and you are preparing yourself for the future!

At IDC Summit 2021 Adriatic, I talked about my experience in Robotic Process Automation (RPA) journey. The feedback was so impressive that I decided to explain the points presented at the Summit in this blog post.

Why Robotic Process Automation

Why Process Automation, and why Robotic Process Automation in particular?

Because it is a fresh and powerful technology that can help a lot of different organizations by humanizing the workplace and making it more efficient at the same time.

Let’s see an example of robot at work.

This was a project finished in 2 weeks as a response to a situation caused by the pandemic. After the lockdown was initiated, companies were required to issue daily commuting certificates to employees performing field work. This created a surge of paperwork at one of our clients in Field Services.

And this was a perfect opportunity for RPA – the process was repetitive, high volume and well defined. Business Analysis was performed in a couple of days. The robot had to fetch the required data from several sources, including employee information, project data and means of transport. Robot than created the certificate using that data and automatically uploaded it to the field service application so that the employees could access it by using their mobile phones to show it to the officer on the street.

In the end the robot managed to create a certificate in 1.5 minutes compared to 15 minutes that was needed manually.

Top 5 Lessons Learned in RPA

Today I am going to talk about some of the most important things I learned from RPA projects in the last couple of years and show some demos as examples.

So, let’s start.

1. Know the Boundaries (To Break Out)

Sometimes, after presentations and demos clients get so excited about the technology that they start to think that anything is possible. And a lot of things are but it is important to understand what RPA is best used for and what it cannot be used for.

RPA can relieve people from manual, repetitive, rules driven tasks and let them focus energy on the fulfilling part of work. We talk about ’taking the robot out of the human’.

RPA robots can emulate actions employees perform on their workstations. Robots can log into applications, move files and folders, copy, and paste data, fill in forms, extract data from documents, send emails. They can also communicate with other systems using APIs but that is not a sweet spot. Robots are fast and predictable, performing tasks as specified and without mistakes.

The technology is primarily based on using existing application UIs which is a big advantage for automating legacy applications and applications without APIs.

Process suitability for RPA is influenced several factors, by its input data (if it is structured or unstructured), number of variations, number of exceptions.

It is also important to understand that RPA is not AI, but recent developments revolve around extensions with AI. Some AI use-cases include intelligent document understanding, natural language processing, fraud detection, recommendation engines…

Some cases are not easy to differentiate if it is an AI use-case. That is why I suggest increasing your competence in that area or including your implementation partner early on so that they can provide help with assessment.

That said, when you know the boundaries, you can decide to break them.

One of the examples is Fraud Prevention process at one of our Communication Service Provider clients, where there was so much data to be pulled from the systems that we decided to deploy 3 robots in parallel working in 3 shifts to process all requests in 24h. The challenge here was that although RPA can be faster than the human it cannot be faster than the applications used, so we worked around that using multiple threads.

Same company, another example – remember this when I talk about scaling in a couple of chapters.

Here we faced semi-structured input, a huge number of variations and a high number of exceptions. But we went for it – Customer Experience and business value won over complexity.

The result was amazing, the robot decreased processing times from 3 working days to only 3 working hours.

So, know the boundaries before you break them.

2. Communicate for Adoption

There was a saying that I liked, goes something like ‘When the wind blows, are you going to build walls or windmills?’.

RPA brings fear of the unknown. I hear some people saying, ‘how is this going to affect my job’.

Remember: transparent communication is crucial for adoption. You should be clear RPA is there to help. The goal is not to replace employees but to create Digital Assistants helping them with boring mundane work and enabling them to do more attractive, higher value work.

After following this kind of approach, we have seen the adoption rise again and again, in the end employees treat robots as their digital colleagues and start calling them names like R2d2, Srećko, Radiša and so on.

3. Process Selection is Key

Process selection is sometimes underestimated. I see some people saying ‘if we could only find that next great value process’ but I suggest there is more than that.

Start from the beginning. The first automated process will have the biggest impact on your program – the first win reinforces all other projects. So, it is very important to try to choose high impact and low effort processes as the first ones.

Secondly, I suggest you follow both top-down and bottom-up approaches in parallel. Top-down to define strategy and bottom-up to create and sustain the idea pipeline, your employees know best what kind of work they are doing.

Create an ecosystem of joint planning, selection, execution, and responsibility – strong internal links in your organization need to be connected to a partner that can lead you through the process.

Here we have an example of a great win for a first process. This was done for a Holding consisting of 70 companies in different industries. Together with them, we have chosen a process that impacts all 70 companies.

Every company needs to register every change in their staff employment status into a central registry. This is a tedious and time-consuming task. Imagine doing it for 70 entities!

We managed to automate all variants of this process in a matter of one month, enabling our clients HR department to focus on higher value work with employees instead of putting them under a pile of manual labor.

We saved time, simplified processes and – made internal customers happy!

4. Plan to Scale

Scaling will determine the success of your RPA program.

After finishing the PoC, companies can go in different directions, from abandoning the technology, stalling, moving slowly to scaling.

To scale and feel the full benefits of RPA you WILL need to plan.

As the first step you will need to define your strategy which allows RPA projects to align to strategical goals.

This will enable you to establish your Automation Operating Model. This is critical for the ability to scale.

Operation model should define HOW an automation strategy is executed and WHO is doing it.

Defining the HOW should include policies and procedures to scale operations in a controlled manner.

Defining the WHO includes

  • Defining a Steering Committee for vision, funding, coordination
  • Business + CoE + IT as key executing functions
  • and support functions like Improvement, Change Management, Communication, Workforce Planning.

CoE is the central point that should be responsible for creating ideas, prioritizing, distributing and governing RPA program.

5. Innovate. Measure. Learn. Repeat.

And last but very important, the importance of measurements…

To measure, you first need to define what value means for you. That definition should incorporate your and your company’s vision, goals, needs, and wants.

Consider both hard and soft values. Hard values are easier to calculate like hours or time saved. Soft values are not so easy to calculate but important nonetheless, for example improved quality, customer satisfaction, employee retention etc.

As a next step you should define measurements for your values. Key metrics might include things like Customer and Employee Experience, Time to Market, Operating Cost, Risk & Compliance, Employee Productivity…

Then you are ready to measure. Measure as frequently as possible to gauge the progress, and at least once before and once after process automation to be able to determine the added value.

Key Success Factors for RPA

In the end I will summarize what I see as main benefits for RPA.

It is fast and nimble, low-integration technology, and low maintenance in case underlying applications are fixed – all leading to a lower cost of implementation than traditional integration or software development projects.

Digital workforce can work 24/7 exactly as specified.

RPA continues to evolve by expanding its area into Intelligent Process Automation (IPA) using AI skills, Machine Learning, Process Mining, native integrations, advanced analytics… But do not wait, establish your seat at the front row right now!

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