How to measure the ROI of an RPA programme
Intelligent automation has the potential to greatly improve efficiency, reduce costs, and increase productivity in various industries. However, implementing an intelligent automation system can also be a significant investment of time, resources, and money. As with any business decision, it is important to consider the potential return on investment (ROI) before embarking on an intelligent automation project.
Calculating ROI for RPA programmes is inherently difficult. The tendency is always to focus on the easiest measure, and frequently the key driver sought by the sponsor - FTE savings, however this carries some key problems with it - firstly, while there can undoubtedly be effort saved by automation, it is unusual that any individual works entirely on automatable tasks, therefore normally only a percentage of any individual is saved. Unless the process is carried out across a large team, savings may not amount to actual headcount reductions. Secondly, a focus on FTE is the best way to cause programme failure. Reference to that KPI will immediately generate resistance and fear- the biggest barriers to overcome.
Lets look at the full range of potential benefits:
When implementing a programme , the first thing to define is the objective, and this may well come from the Board. The KPIs should reflect and measure the objective, but the CoE lead should also make the Board aware of other benefits they may have overlooked.
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At the most basic level of assessment, measures will be translated into financial benefits to be compared against implementation costs, but some of the measures above may be intangible, and here some diligent creativity may be required to represent these in a way that makes business sense.
The key thing is that an assessment of benefit and cost takes place, and opportunities are prioritized. The precise methodology is irrelevant so long as the process is diligent and considered.
Once bots are deployed, there should be a process for monitoring and validating the benefit realisation. (This might be as simple as 'benefit per cycle vs number of cycle runs') although there needs to be 'real world' validation also to check that the quoted benefits enabled are actually being realised in reality.
It is worth noting that as with any project delivery, the CoE lead should take accountability for defining the benefits realisable, but the business should sign up to these at the outset and then it is their responsibility for delivering them once the bots are in place.
Technology Exec | Strategy, Innovation, Project Delivery, | I help the c-suite maximize value through data & digital Innovation. $65M in proven efficiencies with transformation, AI, data management & value creation
2 年One item for you to contemplate is the inclusion of increased data quality. As a data professional we spend 80% of our time cleaning up data quality issues. RPA offers tthe ability to improve data quality which then has major downstream benefits for analytics and machine learning projects
Chief Operating Officer Inflection AI, Inc.
2 年Thanks for this contribution to the discussion- one additional thought for companies, should they think of RPA as a thing in itself (e.g. “RPA programme”) or should RPA be one lever in a broader business process improvement programme… the ROI calculation is still a core part then of the optimization effort but one can view RPA as one contribution toward the business goal as opposed to starting with a need to juatify a technology…
Tnx for this Tim, in line with our experience, We are always tyring to improve staff members work experience and if possible the patient journey, I personally look for opportunities to improve data quality, but that is because of my previously BI role.
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2 年An interesting post Tim, well done! From my experience scoping a client's systems for potential RPA projects is both time consuming and costly. Task mining can help with this if it has a robotic process mining function included as does UltimateSuite's. This can save significant amounts of both time and money enabling a clear competitive advantage to RPA vendors and their clients. Once bots are deployed their efficiency can also be tested and compared with before deployment data. The ROI can also be calculated through the platform as well.