Business and Technology Insights

Going Beyond ROI: Measuring Effort in Robotic Process Automation

 
November 25, 2019

After adopting a wait-and-watch approach, the utilities sector is now following in the footsteps of banking, healthcare, and other industries. It is finally ready to embrace robotic process automation (RPA).

For utilities companies, the benefits of deploying RPA, or software robots, are many. They can execute repetitive business processes, such as customer records management, complaints resolution, and  metering and billing not only faster but at lower costs too. Besides, rolling out such a disruptive technology can address the challenge posed by a highly demanding, dynamic market. That’s not all. RPA can also be harnessed to enhance accounting workflows, boost throughput for processes across the value chain, and minimize variability in operational output.

There is a catch, however. For electricity, water, and gas companies, the central question when implementing RPA is to determine the best method to measure the return on investment (ROI). Enterprises across industries have typically looked at ROI as a financial metric, calculating it as investment gains realized as a proportion of costs incurred.

With customer experience emerging as a fundamental driver of business outcomes in this era of Business 4.0TM, it is time to hit the reset button on ROI.

Alternate metrics

Enterprises need to factor in the ‘return on effort’ (ROE) or ‘effect on experience’ (EoE) while measuring the outcomes of RPA initiatives in the energy and utilities industry.

One way to measure ROE is to gauge the total incremental returns generated by the effort put into an RPA project. Besides quantitative attributes such as reduced implementation costs and financial savings accrued from a few paid holidays, the overall incremental benefits should incorporate qualitative aspects like better employee morale and improved end customer experience.

Effort can be computed in terms of the total project execution cost. This includes not only the usual implementation overheads but also the opportunity costs of assigning internal resources and adverse stakeholder impact arising from suboptimal productivity and project delays.

Apart from effort and returns, two other dimensions that play a critical role in the ROI equation are time and customer experience. Assessing time is rather straightforward – cycle time can be measured as a proportion of ‘mean time to resolve’/ ‘mean time to service’.

However, unlike effort and time that can be easily correlated with returns, quantifying experience follows a different process. It should be linked to how RPA can positively influence the end customer experience. To measure this, utilities firms need to understand, in depth, the various issues faced by their internal stakeholders – the customers who will use the robotic software.

For instance, can RPA ensure that help desk employees are more productive and agile? Can programmed, self-learning tools empower call center staff to respond to customers’ queries swiftly and satisfactorily?

Finding answers to such questions will help organizations determine whether automation yielded the desired benefits they had envisioned at the outset of the project.

Building future-ready enterprises

RPA can transform a workforce by providing employees with the requisite tools and applications for being future-ready. This will ensure that a firm’s ROE, and by extension ROI, will be superior. Put simply, automation projects can be successful when each relevant stakeholder can gauge the real value that such a technology unlocks. It’s not merely about executing a series of automated workflows at scale, but about helping an organization’s workers and managers understand the ‘big picture’.

Also, implementing RPA can augment human capability with technology, a key point of TCS’ Machine First Delivery ModelTM, which can offer a firm’s customers exponential value.

What can’t be measured, can’t be managed, they say. For utilities firms operating in an environment where consumer behaviour and regulations are rapidly evolving, measuring RPA-based outcomes – both qualitative and quantitative – will be crucial to orchestrating digital reimagination.

Rekha Natarajan is the practice lead in the utilities business unit at TCS, where she has over 18 years of experience. Her expertise lies in the areas of quality assurance and artificial intelligence. For over two years, she has been associated with the automation and quality engineering practice in TCS’ utilities unit.

Rekha has engaged with global utilities customers on various automation initiatives like robotic process automation, IT operations automation, application services automation, and quality engineering transformation.