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Mistakes to Avoid when
Implementing RPA

August 2020 | Article

By Bhavik Patel

By Bhavik Patel

8 Mistakes to Avoid when Implementing
Robotic Process Automation

8 Mistakes to Avoid when Implementing Robotic Process Automation

Let’s start with the good news about Robotic Process Automation. It promises an ROI of between 30% and 300% in the first year.


Given this impressive return, investing in RPA has become a no-brainer for numerous organizations. According to a recent EY survey, 41% of bosses in 45 countries are accelerating automation as they enter a post-COVID world.


Now for the bad news…
The failure rate for initial RPA projects is between 30% and 50%. Why is this? In our experience, organizations tend to fall into the same traps over and over again when implementing RPA.


To avoid your organization joining the failure rate stats, here are 8 of the most common mistakes:

1. Failing to engage senior executives

Senior decision makers must be enthusiastically on board from the start. That way, valuable resources will be freed up early on – resources such as subject matter experts (SMEs). They have the process knowledge, metrics and test data that you’ll need for a successful RPA project.


Given RPA’s heavy reliance on IT infrastructure and IT applications, it is essential that your IT team is involved from the beginning. They’ll quickly highlight and resolve any unexpected challenges – software or infrastructure upgrades, security policies, relevant access for the robots and so on.

2. Automating bad or broken processes

Automating a bad process is just speeding up a bad process. Before attempting to automate any processes, make sure to analyze and streamline them as much as possible.


When a process has a simple decision logic, it becomes more straightforward to automate. The solution needs fewer test scenarios during User Acceptance Testing, and it’s also easier to maintain once in production.

3. Not having a dedicated team

Trying to implement an RPA project while simultaneously managing
day-to-day workloads is at best challenging and at worst, nigh on
impossible. Without a dedicated team, there will be delays to the project
and therefore delays to the ROI.


Make sure to plan ahead and allocate dedicated, uninterrupted time by
SMEs and process owners to carry out requirements confirmation,
solution design, testing and deployment.

3. Not having a dedicated team

Trying to implement an RPA project while simultaneously managing day-to-day workloads is at best challenging and at worst, nigh on impossible. Without a dedicated team, there will be delays to the project and therefore delays to the ROI.


Make sure to plan ahead and allocate dedicated, uninterrupted time by SMEs and process owners to carry out requirements confirmation, solution design, testing and deployment.

4. Failing to overcome the fear of digital workers

Change is always difficult, especially when it comes to automation. Understandably, many employees assume the bots will replace them, and that means you will almost certainly face resistance.


It is important to educate employees upfront about how RPA will positively impact their daily working lives. The robots will take on the boring repetitive tasks, freeing them up for more rewarding, strategic work that needs cognitive flexibility, complex problem-solving, creative thinking and emotional intelligence.

5. Lack of coordination with the IT team

Implementing RPA without coordinating with the IT team is one of the worst mistakes you can make – yet we see organizations doing this virtually every day.


RPA is totally reliant on IT infrastructure and its various IT applications. On too many occasions, IT teams have no choice but to delay ROI on automation because:

 

• the information security risk assessment has not been completed
• the correct infrastructure is not in place
• there has been insufficient performance testing to make sure the infrastructure can handle the bot’s ultra-rapid navigation through applications.

 

We’ve seen too many examples where a lack of IT coordination has resulted in the robot taking down the IT application servers, causing business-wide disruption.

6. Insufficient process testing

Thorough testing throughout the project is vital. Cutting corners, and assuming that the automated solution will work in every scenario is one of the most common reasons why RPA projects fail.


The solution should be tested in development and production to ensure consistent performance in all environments. Always test the `happy path’ (the default scenario with no exceptions or error conditions) and then test the exceptions to check the robot can handle all scenarios.


Bear in mind that projects are slowed down by insufficient test data, so make sure to involve your SMEs from the start. They will help you define testing scenarios and reduce delays by collecting the test data upfront.

7. Forgetting about ongoing maintenance

We’re always surprised by how many organizations assume that robots
can take care of themselves. Once the automated solutions are in place,
they forget that bots need support and maintenance to keep them
running smoothly.


Just remember that processes invariably evolve over time and
applications involved with those processes will have a roadmap of
changes.

7. Forgetting about ongoing maintenance

We’re always surprised by how many organizations assume that robots can take care of themselves. Once the automated solutions are in place, they forget that bots need support and maintenance to keep them running smoothly.


Just remember that processes invariably evolve over time and applications involved with those processes will have a roadmap of changes.

8. Failing to scale up

Deploying the first robot is easy. However, many organizations fail to scale up their efforts beyond that.
The true benefits of RPA will be realized only if you identify the right set of processes to automate and then scale up accordingly.


In order to reap a maximum return, your organization should consider creating an RPA Center of Excellence (CoE) – a pool of expertise that drives everything necessary for successful RPA initiatives. For example, they can:

• Build an organization’s RPA expertise
• Acquire and train new resources
• Deliver seamless change management
• Establish clear standards, procedures and policies
• Ensure that compliance regulations, information security requirements
and regulatory standards are met
• Oversee the RPA technology infrastructure

A CoE helps you identify, evaluate and prioritize new automation opportunities – from small projects all the way through to supporting a large bot ecosystem. Intelligent automation products are constantly evolving, and an RPA CoE will allow you to gain the maximum return on investment.

For more information on how to reap the benefits of RPA,

get in touch with our technology experts at Quantanite.

For more information on how to reap the benefits of RPA, get in touch with our technology experts at Quantanite.

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