Content updated in April 2022
RPA (Robotic Process Automaton) enables businesses to leverage automation and enhance the performance and overall efficiency of the workforce by automating labor-intensive jobs and minimizing human errors.
McKinsey Digital has found that RPA can result in an ROI between 30 and 200 percent in the first year.
However, the road to RPA implementation is not an easy one. Infect, according to Ernst and Young, almost 50% of RPA project fail.
In this blog, we will discuss the 7 core challenges faced by the organizations in RPA implementation and methods via which they can resolve them:
1. Employee resistance and its management
A technological revolution of this magnitude does not go uncontested. This is a universal principle, and the case with the implementation of RPA is not an exception. The robots will steal our jobs, goes the common narrative. In this regard, the management’s understanding of the organization’s culture is tested.
With Robotic Process Automation, we are talking about a digital workforce that can perform all the human resource functions, specifically rules-based and repetitive.
For this, the management must take the existing workforce into confidence because embracing new technology is easier said than done.
How to resolve
The CIOs would greatly favor the workforce by not being in a denial mode. They should come forward and explain that the implementation of RPA is likely to bring about a significant change in the landscape.
A practical method to minimize change resistance is to involve all the employees in the early stage of RPA planning. Employees who are directly involved with a process know the nitty-gritty of the complete workflow.
Seeking responses and validation from people at all levels helps businesses build a realistic timeframe and processes for RPA implementation.
Employees who feel valued show less resistance to the change. Moreover, the work hours vested in menial, repetitive tasks can now be invested in more creative activities such as customer service, strategizing sales, marketing, etc.
2. Lack of clarity: what, how, where to implement RPA
The RPA is not an end in itself; it is an enabler that enables organizations to do more with less, which can lead to greater productivity.
There are many challenges to implementing RPA, but one stands out: the lack of understanding of what RPA means. Most people think RPA is just automation or robots doing repetitive tasks. But this is only a part of the entire story. In reality, RPA is much broader than that, it’s about automating the entire business process.
There are three main types of RPA: robotic process automation, cognitive computing, and conversational computing. Each type uses different technologies to automate processes.
- Robotic process automation uses machine learning algorithms to perform simple data entry or email routing tasks.
- Cognitive computing uses natural language processing to interpret user requests and provide automated responses.
- Conversational computing uses speech recognition and text-to-speech synthesis to allow humans to interact with machines.
How to resolve
Automation is an important part of any business process. It helps businesses to reduce costs and increase productivity. However, automation cannot replace human intelligence.
Certain best practices need to be followed during the RPA implementation process to ensure that a business process is completely automated. These include:
- There must be a proper understanding of how the business process works.
- A good design for the entire business workflow needs to be created.
- Right automated tool should be adopted to effectuate RPA implementation
- Business users must be involved at every step of the way.
- The business process must be tested thoroughly before it can be deployed into production.
- Complete visibility into how RPA will impact all aspects of business, including finances, inventory, sales, marketing, customer services, and human resources should be penned down.
3. The security risks assessment
Implementing RPA solutions means granting access to all your legacy systems like CRM, ERP, accounting software, etc. The bot will handle a large chunk of data to execute any rules-based task.
In a scenario like this, there are high chances of data misuse, either in employee mistakes or cyber-attacks by hackers.
The main security risks related to RPA are cyber-attacks against the software itself, which could compromise its integrity and functionality. In addition, it is important to consider the possibility of malicious users gaining access to the system through social engineering attacks, phishing emails, and many more.
How to resolve:
- A sub-team within the RPA team can be employed to monitor and report any bot misbehavior.
- Active directory integration and encryption are other complementary measures that can be taken to prevent any security breach.
- To mitigate this risk associated with sensitive data, organizations should implement robust authentication methods and encrypt all sensitive data.
- The leading challenge for organizations implementing RPA is the lack of visibility into the execution of tasks and the ability to detect anomalies. This makes it challenging to identify and resolve issues before they become serious problems.
- Organizations must ensure that the automation solution has built-in mechanisms to monitor the execution of tasks and alert users if any errors occur.
4. Tackling the total cost of ownership
According to a survey, out of 500 respondents employing a wide range of RPA solutions across various industries globally, 41% of the respondents said it is difficult to maintain RPA.
As more companies embrace digital transformation by employing RPA, one of the biggest challenges is the TCO (Total Cost of Ownership). And it why because software and hardware costs are important components of TCO.
The software costs mainly include operating system costs, bot licenses, Virtual machines, etc. Whereas hardware costs include machines, servers, databases, and alike.
How to resolve
- Multithreading for data processing is one option that can be applied by highly data-intensive organizations which are stored at several places. By multithreading, the RPA tool can reduce the turnaround time up to 1000 times faster.
- Running multiple RPA bots (6-8) on a single virtual machine also reduces the overall costs of operating system and hardware licenses.
5. Choice of correct processes for automation
To get started with RPA, “you have to pick the right process. It has to be stable, mature, optimized, rules-based, repetitive, and usually high-volume,” said Leslie Willcocks, professor of technology, work, and globalization at the London School of Economics, in a discussion with McKinsey.
“The bots are ready, are you?” – Goes the saying across the industry when the question of adopting RPA arises. Irrespective of the size of your organization, the decision to adopt and deploy RPA is one major challenge.
How to resolve
It is easier to automate template-driven processes where decision-making is based on standardized and predictive rules.
- RPA can be deployed for processes with readable input such as text-based data, user interface (UI) activities like keyboard strokes, mouse clicks, etc., optical character recognition, and green screen.
- Big-sized batches that don’t require intrinsic knowledge should be automated to bring an immediate boost to the employees’ efficiency
- Processes that need to comply with the safety and quality norms should be ideally automated.
- Repeated customer queries that need quicker resolution and fast settlement should be considered for automation by employing chatbots
6. Challenges of scaling up
Though the early adoption rate for RPA may seem encouraging, only 3% of organizations have scaled their digital workforce according to Deloitte Global RPA Survey.
This gap is substantial for a solution that boasts of saving time and costs.
How to resolve
- In the given scenario, developers have proposed models such as robot-as-a-service or RaaS. This will allow new customers embarking on digital projects to scale up quickly by obtaining licenses, implementing platforms, and placing the RPA application on the platform.
- Optimizing processes before automating. One of the best approaches to ensure scalability is fixing existing processes by identifying patterns and optimizing them by involving every stakeholder.
- Businesses that leverage the collective expertise of the involved stakeholders are likely to optimize process selection, enhancing scalability.
7. Preparing for the C-Suite
Implementing an enterprise-wide digital workforce requires the support and sponsorship of the c-suite because the cost-benefit analysis drives the c-suite. The C-suite will not approve of any automation initiatives unless sustained and tangible benefits are visible to them accruing in the foreseeable future.
How to resolve
On-boarding the C-suite and functional leadership with a plan of action backed by cost-benefit analysis in the near to medium term will be an ideal approach to implementing RPA.
There are many challenges to any transformation project and RPA implementations are no different. The key issues you must consider above all are: leadership and communication.
Without leadership (without C-suite sponsorship), the adoption rate of RPA and AI will be too slow to be of any real benefit to the company. And without communication, the benefits that accrue from RPA will not be heard or seen by all those who can benefit.
To tap the capabilities of RPA and accelerate your digital transformation journey, you can talk to our automation experts from AutomationwhiZ.