Framework to institutionalize Automation Adoption
Large scale industrial automation has swept the world ever since Henry Ford introduced conveyor-belt assembly lines in 1913. The quest for automating routine mechanical tasks drove manufacturing evolution in the automobile industry.
As computers became affordable in the 1960s, Information Technology (IT) was introduced in enterprises primarily to improve ease of documentation, recording, and retrieval of data. This gradually led to augmenting human intellect and increase in the speed of information processing. The banking industry, well-known for its process- driven setup, has witnessed a significant evolution in automation. IT was used for record-keeping, then was expanded to transaction processing systems and eventually to customer information management systems. The financial industry further adopted IT into offering self-service, using software solutions such as online money transfer, payment gateways, trading platforms, and performance analytics.
Despite being evolutionary for most part, some automation technologies have proven to be revolutionary within specific industries. What Henry Ford’s conveyer belt did to a manufacturing plant, Interactive Voice Response (IVR) has done the same for the customer support industry; and similarly, introduction of online money transfer systems has led to worldwide e-commence growth.
Over the years, with IT becoming ubiquitous across enterprises, high-performance computation systems, federated data/knowledge centers, and sophisticated software solutions have become widely accessible. As a result, routine tasks performed by individuals in large organizations, such as fetching business intelligence from multiple systems and responding to a commonly occurring customer situation, can now be automated. The implications of such capabilities are expected to drive large scale transformations in every industry.
Robotic Process Automation (RPA) is the implementation of a computer software that mimics human actions to complete rule-based tasks. A study by Transparency Market Research indicates that global RPA industry would grow at a CAGR of 60.5% and reach a market potential of over $5B by 2020. Needless to mention, the cost benefits delivered by the RPA industry would be multi-fold.
Additionally, the concept of Artificial Intelligence (AI) has long existed since 1950s, but for various reasons, it has not been capitalized by enterprises for mass adoption in the past. However, combining such cognitive computing capabilities with Robotic Process Automation, the benefits are anticipated to rise exponentially. Acknowledging this tectonic shift expected to emerge out of the RPA-AI combination, many leading global organizations are already setting up focused working committees led by senior executives to develop enterprise-wide automation strategies and to evaluate required organizational changes.
Implementing RPA strategy
As RPA tools mushroom the marketplace, most large corporations are setting up initiatives to develop their enterprise-wide automation strategies. As in the past with other such technologies, enterprises are cautiously treading a full-scale adoption as they investigate typical implementation timelines and the size of anticipated ROI. As industry standards for RPA implementation are still being developed, it is recommended that companies develop their own proof points prior to executing a full scale implementation roadmap.
There are several enterprises around the globe that have found varying levels of success in their RPA initiative. In order to execute sustainable and successful automation of business processes, it is highly recommended to develop a RPA adoption framework and establish a center of excellence for process automation.
The first step in the RPA adoption framework is to develop an automation strategy. Like any other significant corporate-wide initiative, executive sponsorship is critical to success. A recent study shows that 40% of enterprises believe that RPA initiatives must be owned and managed by business units (not by IT). Hence, identifying the business leaders responsible for implementing RPA strategies will be a key requirement. Establishing automation goals, timelines, anticipated ROIs, and identifying skill gaps must be discussed and agreed upon.
The next step is to develop a roadmap – an important aspect in establishing a long-term automation strategy. The roadmap must define the evolutionary adoption of automation through prioritization of business processes, resolution of organizational dependencies, and identifying a strong governance structure.
Thirdly, it is important to evaluate RPA vendors/tools, build proofs-of-concept, and identify a strong implementation partner for setting up a successful CoE. Involving HR to establish an appropriate organizational change management to effectively embrace automation is another key step in the process. The skills required for designing, testing and deploying automation must be identified and plans to hire/train resources should be developed in parallel.
The above process to establish the Automation CoE typically takes between 2-3 months.
Once the CoE is established and staffed adequately, the robots can then be designed, tested and deployed. Involving the RPA tool vendor in the early deployment stages is a must. With strong governance and automated DevOps structure already in place, deployment issues could be handled expeditiously. It is also important to note that setting up of required performance metrics, measurement tools/methodologies must be given sufficient focus for continuous improvement purposes.
With a framework in place to strategically implement RPA across the enterprise, let’s review how RPA can be implemented in IT and back office operations, in the subsequent blogs.