Adrian Iaiza, Head of Process Automation and Improvement, Tal Australia
The rise of RPA has captivated the attention of executives with the promise of cost-savings beyond labour arbitrage, cost avoidance by extending the life of legacy IT, quicker implementation than traditional IT projects, reduced process risk, auditability and compliance.
Many of us have successfully deployed RPA into our ecology. However most implementations are piecemeal. Just a year or so ago, RPA was at the peak of its hype cycle, so has all the effort lived up to the hype?If you’re looking for some quick tips, here are a few things to bear in mind next time you’re asked to take stock.
One of the selling points of RPA was the ability to rapidly deliver capability in a cost effective manner. To achieve this in practice require careful planning and foresight in the following areas.
RPA requires the capture of business rules, as well as the detailed process of entering the transaction. The later can be tedious, and time consuming if you aren’t careful. If this is becoming a critical path in your organisation try recording the transactions happy path with narration, and only document exceptions.
A process automation are made from chains of common sub-processes. Designing this into your development and requirements methodology offers significant benefits. Remapping your process library all your processes are made up of common sub-process through what I term process normalisation, delivers two immediate benefits: your design and build phase is dramatically reduced as you reuse rate increases. It is also a gift that keeps giving. The more your code base is designed this way, the faster and easier it is to develop.
Another benefit is the significant reduction in maintaining code. Version upgrades, changes in screens due to user or regulatory drivers is not uncommon and can pose issues to any RPA fleet. If your processes have not taken advantage of the modular nature of process normalisation, you are likely to be faced with rapidly increasing maintenance demands redirecting for focus and investment.
Invest the time to go out and communicate how RPA can complement and not compete with your organisation’s digital and STP journey
The attraction of designing your processes and code with process normalisation in mind is that changes are made with surgical precision that considerably reduces your development. This is no panacea; reuse needs to be embedded at the heart of your development and QA review.
Stability is something else to ponder on. If you’re your code base is not living up to performance expectations it might be time to reach out to other providers who have a deeper and broader expertise with your toolset. Exponential RPA sales growth has seduced some providers into overselling and promising their capability.
Another aspect to consider is how well the scope of your RPA code base is understood by application development teams across your enterprise. If the level of awareness is low, you run the risk of these teams propagating changes without understanding the dependency on RPA resulting in bouts of instability and frustration. Look at enhancing awareness and governance, invest the time to go out and communicate how RPA can complement and not compete with your organisation’s digital and STP journey.
Each technology has its strengths and weaknesses. RPA is well suited to rules-based automation of structured back-office business processes; API-led automation excels integrating discrete micro-services and applications; desktop automation can neatly knit together common desktop activities. Ensure when designing RPA applications that you are leveraging its strengths and not trying to be all things to all people.
RPA does promise and can deliver better Customer service, reduced operating costs with less risk. To really capitalise on these opportunities you need to consider your automation framework.
Automation requires clean, structured digital data. Shrewd RPA enthusiasts collaborate and support any digitisation and data governance initiative within the organisation. Removing the barriers to accurate data and analytical insight is essential. These initiatives turbocharge the payback of current, and scope of future, implementations.
RPA is not an island. Substantial benefits are to be had through pairing RPA with machine learning and chatbots. While RPA tools are being developed to intelligently learn processes and schedule, pairing RPA with chatbots and machine learning applications creates end to end solutions that have tangible, significant impacts to the organisation.
You shouldn’t be afraid of taking stock. Only throughcontinual, objective assessment will progressive practioners evolve to their ideal of what good Intelligent Automation can be. Pushing the boundaries and collaborating with internal stakeholders is an effective way to transform and integrate this capability into a newer and agile digital organisation.