- The introduction of any new technology requires a careful selection of the business area where it is sought to be deployed.
- This selection is crucial to demonstrate the capability of the technology to deliver business results so that it is championed by the stakeholders.
- At Cevitr, we recognise the importance of using a structured approach in making RPA deployments successful and more mainstream in the Industry 4.0 era.
Robotic Process Automation (RPA) is an application of technology by which business processes, that use computer systems and applications and follow a fixed logic or set of rules, can be executed by a trained software robot. The deployment of RPA spans across industry verticals and its application can be tailored to a host of use cases, varying in complexity and sophistication. Hence, selecting the most suitable candidate process may often be perplexing for many businesses. This guide highlights a methodology that Cevitr has used for its clients, to address the first question that all businesses ask:
We begin to answer this question by examining the universally accepted outcomes that businesses are looking for from RPA deployment such as:
- Cost Reduction in business process transaction processing
- Speed at which transactions are processed
- Higher level of accuracy in the outputs produced
- Reducing the level of manual data & information processing activity
In addition to these outcomes each business will aim to achieve additional consequential benefits
- Increased sales growth
- Increased profitability
- Increased levels of customer satisfaction
- Increased levels of employee satisfaction
is therefore, the first and vital parameter that is looked at whilst deciding a candidate process for RPA implementation.
Next, we look at the technology itself and focus on the data and information
that can be processed with an RPA solution.
- RPA technology relies upon structured data, even though the data itself can come from multiple sources. Examples of structured data are Excel based reports generated from enterprise/business applications, transaction records in enterprise/business applications and electronic invoices in portable document formats (pdf). (Conversely, a paper-based record or hand-written annotations in business documents are a classic example of unstructured data and requires a level of Artificial Intelligence (AI) solutions to be deployed before an RPA solution can process such information.)
- Does the data & information use certain rules to be processed? If so, identify the rules and quantify the number of rules that need to be applied to process a single transaction.
- Consider data coming from multiple sources like applications, websites, reports etc, that require a swivel chair appoach to processing. These have a direct co-relation to the volume of processes and the number of rules that need to be applied.
A combination of these elements determines the second parameter of PROCESS COMPLEXITY
that is essential for businesses to consider for RPA applications.
Identification and achievement of outcomes are the reasons why businesses are looking at adopting RPA in the first instance. An early quantification of the business benefit helps in assigning the correct set of criteria that will define success or failure. TRANSACTIONAL VOLUME –
the third parameter is a key determinant in contextualizing the business benefit be it cost saving, process output accuracy or process speed.
Next, we look at the technology itself and focus on the data and information that can be processed with an RPA solution.
Having identified the three key parameters of Business Impact, Process Complexity and Transactional Volume, candidate processes for RPA implementation can be analysed by positioning tasks on the Process Mapping Grid by Cevitr, on a scale from high (H) and medium (M) to low (L).
Processes that can be mapped to the top right-hand quadrant are characterised by low process complexity, have a medium to high business impact and high transaction volumes are the ideal for RPA implementation. However, for each process to be mapped correctly, all the Sub Parameters (SP) as well as a set of Objective Quantification Criteria (OQC), need to be measured.
We have identified 10 SPs and 32 OQCs to which we have ascribed a rank-based weightage that is used to evaluate our clients’ processes. Some of the common SPs and OQCs have been outlined below:
Each target automation process is measured using this scoring mechanism and the results are used to position the business processes on the Process Mapping Grid.
The ideal attributes of a candidate process for initial RPA deployment would score the lowest in Process Complexity and highest in Business Impact and Transaction Volumes, placing them in the top right area of the grid. These processes would be the (1) Proving Grounds for RPA implementation and an ideal First Proof of Concept Candidate.
Candidate processes that could additionally be considered in the initial stages of RPA implementation could be the BPO work that has already been outsourced to low cost locations. However, for an organisation wide stakeholder buy-in, which is essential in making the use of RPA more main-stream in business, this may not be the best place to start because of the low business impact. Therefore, once there is stakeholder buy-in with the initial POC that has a high Business Impact, there is a real possibility of taking further cost out by reclaiming (2) BPO work Using a Digital Workforce.
At Cevitr, we believe in the power of a Digital Workmate to support employees by performing tasks that are repetitive, routine and mundane but essential to the organisation. This effectively enables employees to contribute to the business in ways that only human beings can – by being creative, making connections and taking decisions. Therefore, as RPA becomes integrated within a business, the next step would be (3) Digital Empowerment of the workforce. Automating tasks that have low transaction volumes can yield high business impact as a consequence of employee satisfaction.
(4) Hybrid RPA Delivery is when a combination of standard RPA solutions and human-based decision making are applied in executing a process. In some cases, this may be when some best of breed Artificial Intelligence solutions are combined with standard RPA solutions for executing an end to end process. Inherently these processes are more complex in nature and do have a high business impact. They should only be automated when a level of maturity in technology capability is achieved along with an established co-working model that makes the interaction between the human worker and digital worker seamless.
The benefit of using a structured methodology to identify candidate processes is that when this approach is applied to a broad range of business processes it will inevitably lead to developing the building blocks of an organisation wide Automation Roadmap. The automation roadmap itself evolves from an initial view and as adoption within a business increases, newer priorities will need to be incorporated in the automation journey. As RPA & AI adoption in Industry 4.0 has been identified by leading analysts and advisors as being at the peak of the hype curve, an unstructured approach will inevitably lead to disillusionment, which would then deter further investments in the technology. Moreover, the current focus of most RPA deployments is in demonstrating that the technology works, and little attention is being given to identifying the surrounding processes and methods that need to be applied for a longer-term value creation that the technology has to offer.
About the Author
This article was originally concieved and developed through collaboration with the #NextGeneration brigade at Cevitr. We are committed to developing the next generation of business leaders by combining youthful exuberance with the foresight of experience Manasi is a creative Content Writer at Cevitr who has Eight years experience designing and facilitating narrative
environments for clients from the commercial and heritage sector. Rebecca is a university student and yet finds the time to work at Cevitr as a Marketing Assistant, bringing new ideas and enabling Cevitr to use the #NextGeneration approach. Jaideep is the Co-Founder and Managing Director of Cevitr and has
over 30 years of IT industry experience
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