Businesses across every industry and sector are growing increasingly reliant upon automation processes to improve organizational efficiency, boost customer satisfaction levels, and reduce operational costs. The most innovative and forward-thinking companies are consistently hearing that Robotic Process Automation (RPA) is systematically transforming the business world. However, they are also learning that RPA adoption can sometimes present complex challenges without a well-defined strategy and governance structure already in place.
Statistics indicate that approximately 53% of companies are already well on their way to RPA adoption, and experts expect this number to rise by 72% within the next two years.1 Unfortunately, the data also suggests that approximately 30-50% of initial RPA projects fail2 due to poor planning, lack of adequately trained technical staff, unrealistic expectations, or other unforeseen obstacles. Without a methodical, well- informed process for RPA adoption and implementation, this fear of failure can often cause enterprises to delay or obfuscate their entry into this seemingly futuristic world.
Simplifying Robotic Process Automation Adoption
CIO.com defines Robotic Process Automation as “an application of technology, governed by business logic and structured inputs, aimed at automating business processes. Using RPA tools, a company can configure software, or a ‘robot,’ to capture and interpret applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems.” 3 As with any new technology, organizational adoption of RPA requires an investment of time and resources, as well as a strong commitment to change. Depending on the specific business sector or industry, there may be limited real-world examples of successful RPA adoption. This perceived uncertainty and perhaps even fear can unfortunately cause many company decision-makers to delay their entry into this strange, new world. The good news is that RPA adoption can go quite smoothly when employing a clear, methodical approach to implementation, starting with smaller, less complicated processes and gradually expanding into the more complex.
OVERCOMING THE ROADBLOCKS TO RPA ADOPTION
Robotic Process Automation technologies present such an array of new and exciting possibilities that business leaders can often become overwhelmed. Where should they begin and with which processes? They may, in fact, have difficulty in even determining the precise strategic benefits of RPA adoption as related to their unique enterprise and their current operations systems. In a recent survey conducted by Harvard Business Review4, 44% of respondents claim that their primary concern surrounding RPA implementation is their general lack of understanding regarding how RPA best applies to their organization.
Common fears which can delay the adoption process might include:
- A general uncertainty of where to begin and with which individual automation processes
- Concerns over beginning with overly ambitious RPA objectives
- Issues regarding the governance structure’s current capabilities to plan an RPA adoption process that will be ultimately successful and with little to no disruptions in current operations systems
- Acquiring employee buy-in for RPA implementation in one area of the company while failing to expand that enthusiasm across all departments within the enterprise
- The potential lack of capabilities to scale RPA systems as the organization grows and expands into new and as-yet unimagined areas of opportunity (In fact, of the 78% of companies claiming successful adoption of RPA technologies, only 3%5 can further claim to have successfully scaled their digital workforce since the transition.)
While these are valid concerns, the RPA adoption process does not have to be overwhelmingly frightening. Forward-thinking business leaders who firmly believe that RPA is a crucial factor in their enterprise’s long-term success further assert that the initial approach to adoption must be methodical and strategic—yet simple to start. Especially during the early stages of adoption, organizations must avoid random installations of discrete or highly complex applications and instead focus on the more mundane, repetitive tasks.
A Spectrum of Process Adoption
From a strategic perspective, successful RPA adoption in the long-term requires a smart approach – one which focuses on the optimum selection of the right technologies that are easy to get up-and-running quickly. The selected products should also be powerful and secure enough to keep the in-house IT department and related staff happy.
Depending on the organization’s precise location on the progressively more multifaceted timeline of RPA adoption, issues for consideration will include a diverging assortment of processing tasks. Their complexity can range from the traditionally manual-intensive (rudimentary) to the more intricately interconnected (enhanced)—consider this a spectrum of process adoption. While RPA is still in its infancy stages and few real-world examples of full-lifecycle, large- scale deployments currently exist, a standard RPA spectrum for process candidates is already demonstrating considerable success.
RUDIMENTARY PROCESS AUTOMATION
In this initial phase, organizational leaders should first be identifying internal processes that are more rudimentary, repetitive, or mundane. These tasks often involve the most tried and true technologies, and they usually adhere to very precise operational procedures across multiple systems and departments. One example might be when a human employee copies a dollar value acquired from a legacy mainframe IT system and into an Excel spreadsheet operating within an in-house server. Other examples might include a variety of basic tasks with little value-added benefits, such as the completion of file transfers, project scheduling, screen scraping, and event data collection.
These quick-hits of RPA transitioning can build confidence in the deployment team, the employees, and the key decision- makers responsible for approving the initial proposal for RPA adoption. These initial processes to automate often return immediate and measurable results while simultaneously delivering incremental benefits involving several of the subsequent processes and subprocesses that the organization will choose to automate in the future.
ENHANCED PROCESS AUTOMATION
Moving beyond the rudimentary phase comes more enhanced process automation which involves the integration and coordination of multiple RPA processes, many of which may have been only recently upgraded during the rudimentary phase. These individual RPA processes may also be interconnecting with various legacy business applications, such as ERP/CRM systems. Through a well-defined integration strategy, these different tools and platforms gain additional capabilities far beyond their very basic, individualized functions.
For example, enhanced phase integrations can provide the ability to manage the processing of larger quantities of highly complex transactions or those that are reliant on a deeper level of data analytics. Another example might be the processing of standard financial data required for the compliance protocols of the U.S. Department of Treasury.
Where to Begin: 6 Steps for RPA Adoption
There’s no question that RPA technologies offer tremendous opportunities involving improved productivity, scalability, predictability, quality, reliability, auditability, and both customer and employee satisfaction levels. However, to harness RPA’s maximum potential, companies need a carefully crafted, methodical approach for execution. Optimized deployment of Robotic Process Automation relies on the proficient execution of six well-established principles.
1. Learn what RPA is and what it is not
Before even considering an entry into the intpriguing, new world of Robotic Press Automation, it’s important to understand what, precisely, RPA can and cannot do. Contrary to popular belief, RPA is not the same as Artificial Intelligence. RPA technology and applications enable organizations to implement enhanced efficiencies by automating various repetitive, manually intensive tasks. In turn, employees can then focus more of their time, attention, intelligence, reasoning skills, and judgment capabilities on more complex, value-added work functions.
While many people often use the term AI to describe various activities ranging from simple automations to the performance of complex algorithmic interpretations, RPA adoption does not perform any of these more advanced capabilities. In other words, RPA does not self-learn, think, act, or interpret for itself. Humans are still the “brains”behind the entire operation.
2. Identify potential RPA opportunities
Begin by creating a “wish list” of appropriate automation processes that are prime candidates for RPA. Review rules- based and deterministic applications of the individual processes, perhaps identifying those that require high numbers of employees to complete. Consider using an automation candidate scoring matrix to determine the comparative time savings, criticality, frequency, effort to automate, and lifetime of automation of each process. Other top candidates might include processes with lower estimated times to automate, those utilizing standard or structured data, or processes with an inconsistent or fluctuating demand but which still require a full-time staff. Three process types which are often excellent candidates for initial RPA integration include:
- Data entry procedures, such as claims management or invoice-processing systems
- Data extraction systems, such as the extraction of customer data for the filing of tax claims
- Repetitive, routine, and otherwise mundane tasks, such as the processing of bank transactions or insurance claims
3. Select initial use cases and define success criteria
Pre-determining the expected ROI is perhaps the biggest challenge of effective RPA adoption. Organizational automation processes are continually increasing in complexity, even without RPA implementation, as regulatory and compliance requirements, exceptions criteria, and geographic variations continue to morph and evolve seemingly without end. When identifying realistic ROI expectations, determining the break-even point is often an excellent place to start.
However, determining the success rate of an initial use case relies on a variety of measurable variables across a broad range of areas. Cost-efficiency is great, but only if the new technology adds value to the overall organization in the end. When documenting and analyzing the associated impacts of an initial use case, factors of consideration might include:
- Costs of licensing the various RPA tools (the price for robot licenses usually decreases as the number of required licenses escalates)
- Costs associated with RPA implementation, configuration, deployment, and testing—including any costs associated with acquiring expert consultation services in RPA
- Costs related to system maintenance, including future RPA software upgrades, application modifications, and processes changes
- Costs associated with new IT infrastructure demands
- Speed and productivity of the individual applications versus conventional human employees (even an RPA application that performs just as fast as a human can be extremely advantageous because the apps can perform work 24/7)
- Accuracy and compliance issues
- Scalability, flexibility, and issues of fluctuating demands
- Removal of non-value-added automation processes from human employees while perhaps upskilling the work force simultaneously
- Additional internal processes and structural elements that may be unexpectedly yet positively affected
- Decision-points within the RPA process that require human intervention, if applicable
- And so much more.
4. Pilot solution for initial use case/POC
Several leading RPA technologies can sufficiently manage the most common automation scenarios, but many organizations may already be utilizing various components with pre-existing, RPA- or AI-enhanced capabilities. As organizations gradually move towards large-scale automation involving multiple processes with capabilities using unstructured data, the company can steadily integrate additional RPA solutions to achieve the desired final objectives.
It is critically important to coordinate with RPA vendors and select only those who can offer end-to-end process support, which will boost the enterprise’s chances of achieving maximum results. The collective goal for any organization considering RPA adoption is to select the right technologies that best suit the unique automation demands of the individual company while also having the capabilities to become fully operational quickly. With the help of a reputable RPA specialist, choose only those products which will limit disruptions to existing internal procedures while simultaneously optimizing security, power, and scalability opportunities.
5. Measure results and document lessons learned
Business leaders who firmly believe that Robotic Process Automation is a critical component of future business success are also rarely afraid to re-engineer a few legacy programs when appropriate. After all, a primary goal of RPA adoption is to produce as few exceptions as possible. If inefficient legacy programs are generating higher numbers of exceptions due to subpar interdependencies with RPA applications and systems, then re-engineering the legacies may be the only way in which to achieve the desired outcomes for automation. Perhaps most importantly, thoroughly document all lessons learned and the modification processes of existing applications, if applicable. Because variability in business is constant, organizations frequently reprogram apps, systems, chatbots, and other RPA components to perform within the reality of constant variability and fluctuations in automation demands. As the business grows and expands, the documentation of prior lessons learned will expedite the next reprogramming processes significantly.
6. Expand to next use case and repeat pilot, measure & expand steps
Any significant procedural change or installation of a new protocol always relies – at least, in part – on extensive employee buy-in. If the staff feels as if the new protocols are being forced upon them without their advice or consent, the implementation process is probably doomed from the start. Statistics indicate that a lack of effective coordination and cooperation between the RPA governance structure and the IT and other internal departments is directly responsible for a significant percentage of RPA adoption failures.
The coordination must also occur inter-departmentally. Successful RPA adoption should be a team effort comprised of a unique combination of talented individuals with varying needs and desired outcomes. Enterprises entering the world of RPA adoption should consider these six basic principles in- depth before implementing the very first RPA modification.
Once the governance structure documents, analyzes, resolves, and retests any issues of concern related to the initial use case, an overwhelming sense of confidence can easily start to envelop the in-house IT team. While this is a positive sign for continued success, this increased sense of self-assuredness can sometimes easily lead to mistakes being made in the next use case scenario. For example, instead of acquiring employee feedback along the way from a broad range of departments like they did during the initial use case, the staff may mistakenly decide that these interactions are no longer necessary. But by adhering as strictly as possible to the procedural steps used in the first case, the team leader can essentially streamline the RPA implementation of the second.
PLAN FOR FUTURE SCALABILITY DEMANDS
When choosing among the many technologies available for enhanced Robotic Process Automation, businesses must always consider the potential scalability issues of their preferred selections. No matter how well the product performs out-of-the-box, it may not be the best choice if it isn’t capable of scaling to meet the ever-expanding and constantly morphing demands of the business. Organizational leaders should focus on three primary aspects.
- Managing increases in workload
- Expanding the scope of usage
- Increasing the range of access
FOCUS FIRST ON PEOPLE, NOT PROCESSES
RPA is not a one-size-fits-all automation solution. Some businesses may use RPA technologies as a payroll automation tool while others may rely on it for Human Resource on- boarding processes. In many scenarios, the organization tends to focus on identifying the various, internal processes that they would like to automate based on the success rates of the RPA product.
However, for optimum results, the business should really be focusing more on its human employees and where they are being forced to perform redundant, non-value adding tasks. The governance structure should first identify which systems need to change so that their human employees can pursue judgment-based roles for which they are best suited, such as critical thinking, strategizing, and creative problem-solving.
IDENTIFYING A WELL-DEFINED GOVERNANCE STRUCTURE
Throughout the RPA adoption process, identifying the unique and varying roles and responsibilities involved will substantially improve the organization’s chances of success. Who will be responsible for new deployments? Who will be modifying existing applications or creating new ones? Furthermore, who will define the criteria for assessing whether these aspirational apps are truly successful in meeting the company’s core automation objectives? Some factors to keep in mind when developing this governance structure include:
- Create an RPA roadmap, complete with milestones and intermittent deadlines.
- Involve Human Resources while supporting and helping to define their employee development and upskilling procedures
- Create a cross-functional team that will spring into action and clear temporary backlogs in circumstances of possible bot failures
- Involve the legal and compliance departments where appropriate
- Coordinate and keep apprised the organization’s IT department throughout the entire adoption process. Their ongoing buy-in is crucial for long-term RPA sustainability
- Calibrate the development and production environments to ensure the smoothest possible deployment of RPA technologies.
- Consistently track productivity, performance metrics, and both positive and negative impacts while identifying potential areas for improvement
NON-MANDATORY COGNITIVE PROCESS AUTOMATION
A later phase in the spectrum of process adoption is cognitive process automation, which offers promise with RPA but is not mandatory to achieve most of the RPA benefits. This process might entail the convergence of rudimentary and enhanced automation processes with available factions of Artificial Intelligence (AI). The introduction of human-like bots and chatbots would usually enter the process at this stage, which could potentially further amplify the overall system’s AI or “self-learning” capabilities to enable intelligent automation.
However, many companies are perfectly content to stop their adoption process anywhere between the rudimentary phase and enhanced, while still reaping the majority of RPA benefits and success. They might also choose to simply focus more on the expansion of the initial rudimentary phase use cases rather than moving forward with the more complex integrations which may or may not add value to the organization’s core automation objectives. Not all RPA adoption strategies need to eventually end with the cognitive process phase.
The adoption of Robotic Process Automation does not have to be a massively fear-inducing endeavor. Just as with any change in internal procedures and protocols, organizations can optimize their chances for success by simply implementing a strategic and step-by-step approach. The basis of this implementation plan simply relies on the selection of the right technologies that conform best to the company’s existing automation and manually intensive processes.
By partnering with a leading expert in RPA systems and applications, enterprises entering the world of RPA adoption will have significant advantages over the competition. Choosing the right technologies that are also maximally secure and powerful is a crucial first step, but the selection of only those products that can become fully operational quickly is even more important.
Still in its infancy stages, RPA technologies are already becoming increasingly widespread across every business industry and sector. As these technologies continue to advance in their capabilities, new and exciting innovations in automation processes will also begin to appear—both from the manufacturers of these RPA products and the forward-thinking organizations which utilize them.
About IRPA AI
Founded in 2013, the Institute for Robotic Process Automation and Artificial Intelligence (IRPA AI) is an independent professional association and knowledge forum for the buyers, sellers, influencers, and analysts of robotic process automation, cognitive computing, and artificial intelligence. Our global network and advisory services offer leading-edge market intelligence, industry research, sourcing assistance, and events, as well as offering opportunities to learn and network with stakeholders across service industry functions.
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1 Deloitte, Deloitte Global RPA Survey (2018), retrieved from www2.deloitte.com/bg/en/pages/technology/articles/deloitte-global-rpa-survey-2018.html
2 EY, Get ready for Robotic Process Automation (June 2017), retrieved from EY.com/gl/en/industries/financial-services/fso-insights-get-ready-for-robotic- process-automation
3 CIO, What is RPA? A revolution in business process automation (September 2018), retrieved from CIO.com/article/3236451/what-is-rpa-robotic-process- automation-explained.html
4 Harvard Business Review, The Rise of Intelligent Automation (2019), retrieved from www.oracle.com/a/ocom/docs/artificial-intelligence/hbr-pulse-survey.pdf
5 Deloitte, Deloitte Global RPA Survey (2018), retrieved from www2.deloitte.com/bg/en/pages/technology/articles/deloitte-global-rpa-survey-2018.html