Owing to a large influx of Enterprise-wide business cases promising dramatic cost savings and ROI, many organizations across the world are busy deploying bots to automate the routine rule-based manual processes. Though there are some quick wins that garner the attention of the C-Suites, many get stranded and unable to scale the benefits while implementing the RPA. In many cases, several business cases are not presenting the real ROI that misses to cover several aspects in discovery and post-implementation. Moreover, benefits are getting limited due to the absence of a holistic approach and many RPA projects being started with mere pressure from the top management to achieve cost savings. On the other hand, many RPA Center of Excellence (CoE) established are not adequately skilled to see through the entire digital transformation path and getting limited to only quick wins from RPA.
To garner, continued involvement and seamless coordination amongst various stakeholders, it's very critical to staff the CoE with both technical, and functional resources. Hence while charting the CoE to build, maintain, scale and accommodate RPA across the enterprise, the following are some of the aspects to be considered and they are not in any order. Overlooking the below aspects can easily whip the RPA implementation out of shape and eat up many of the cost benefits that were initially envisaged.
- Best Practices Repository – One of the most critical aspects to multiply the success stories of RPA across the enterprise is to leverage the lessons learnt and document them to share several stakeholders in CoE. Missing this will only double the efforts of RPA consultants, developers, subject matter experts, and operational owners. It is also important to briefly state why RPA is not chosen for certain processes in the Process Information Template. This helps the experts to re-engineer the process and suit it to the needs of RPA. This will be highly handy for choosing complex processes post-reaping the benefits from the quick-win pilots.
- Onboarding all stakeholders early in the game – Several RPA business cases are measured in terms of FTE savings and minimally focus on other benefits like enhancing customer experience and empowering employees. This in turn creates an aversion amongst employees to share ideas on process automation and making things more complex. Hence onboarding all stakeholders across the enterprise right from the beginning of the automation journey is important to be on the same page. This will ensure co-operation and collaboration of the CoE team.
- Inclusion of 3rd party consultants –This is important to access the skills that are not already available in-house. Many a times organizations choose an RPA tool based solely on the marketing accolades won by the RPA tool vendor or what other organizations have benefited and not by what’s best for the long term. A consultant will have a sharp eye to skim through the noise and look for what’s important to you. It is common knowledge to include your implementation partner to be on board early in the game along with your internal stakeholders. It is also especially crucial to scale up the CoE quickly and get on track with the benefits envisaged. Consultants bringing in the best practices and lessons learnt from the implementation experience will fasten the journey to success. They also bring outside-in views to take decisions on transforming certain processes that look not RPA'ble at the first instance. They will help you envision your journey after RPA.
- Alignment of RPA with overall Digital Transformation Strategy - Many RPA CoEs established are busy in grabbing projects for quick wins and leaving behind ones that have long-running business processes with more hand-overs and queues. Ideally, this may be left out or poorly designed for RPA instead of solving it with DevOps & BPM route. Moreover, with the chatbots transforming the front office, it is wise to integrate RPA to enable self-service and enhance customer experience. Furthermore, with the increased data capture on several processes in isolation, they need to be put to use for Business Intelligence(BI) and analytic tools to generate insights. Unfortunately, several steps involved in consolidation and transformation inhibit the automation and are manually handled with spreadsheets. Obviously, this is a manually intensive and also monotonous task repeated over time. Thus a larger vision of your Digital Transformation journey needs to be incorporated into your RPA discovery and implementation and CoEs are better positioned to keep a check on it.
- Change Management & Governance – As processes are meant to change for better execution, it is essential to have clear visibility on change management and governance frameworks. This in turn minimizes the exceptions and avoids inefficiency from creeping into the process. Establishing clearly documented policies and stage gates will ease the Change Approval Board(CAB). A very good automation governance framework will mitigate strategic and operational risks, address regulatory compliance, ensure knowledge management and escalation management.
- Process Re-engineering – Cut-throat competition in many industrial verticals inhibits longer life-cycle BPM projects. Though BPM is used for complex processes where there is no scope for RPA, there is a recent trend where RPA and BPM are used together. RPA will improve the process performance, eliminate errors and reduce the cost of operations whereas BPM enables the modelling of core process reengineering. RPA is like applying a sticking plaster over a poor process instead of dealing with the root cause. This can sometimes embed prevailing inefficiencies deeper. Hence the synergy between RPA and BPM will offer innumerous benefits.
- Tactical Automation – In some cases, simple scripting can automate the manual process which will further save the organization from RPA licensing cost and ease change management with the use of local tools. Hence tactical automation is also to be considered during the discovery phase for RPA.
- Analytic Insights – Bots create so many transaction logs which can further be analysed to report process improvements and minimize the exceptions when things go wrong. There are cases where visualization tools like Elastic Search and Kibana analyse RPA logs and glean insights to improve bot performance.
- Path to Cognitive Automation – As there is an increasing trend to evaluate AI capabilities in process automation, cognitive automation is getting evolved to automate tasks that are non-standard and do not follow a finite number of rules. This enlarges the addressable opportunities for intelligent automation of complex processes. Clearly earmarking likely candidates early on will save on repeated investments on the same process over and over again. Also, RPA can be put to use to ensure on-time data exchange is setup for cognitive automation to work.
- Bot Command Center - Over a period of time there might be 100's of bots running concurrently in an enterprise setup and should any one of them break down, the business operations need to have the visibility to know what has gone wrong. As many CoE setups are busy identifying new business cases, in all likelihood, you will have inadequate support staff when things go wrong. This results in poor performance of bots with many exceptions as processes are bound to change. Hence a comprehensive Bot Command Center (BCC) needs to be established to track, report, improve, amend or change and analyze the performance continuously.
- Reviewing the computing power needs - As several IT infrastructures are not designed to manage the speed of bot operations, it is very essential to review the logs generated by bots and assess the need for enhancing the computing power periodically.
Overall, a COE functions beyond the skills necessary to develop bots and ensures replication of success and Best Practices are maintained. Give your RPA CoE the right mission to fulfill the organization’s Digital Transformation strategy.