HOW EXL BUILT A LARGE SCALE DIGITAL WORKFORCE FOR A LEADING ENERGY AND HOME SERVICES PROVIDER AND HELPED MAINTAIN ITS LEAD IN THE HYPERCOMPETITIVE UK ENERGY MARKET

DOMAIN EXPERTISE ROBOTICS PROCESS AUTOMATION

DIGITAL INTELLIGENCE

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CASE STUDY

HOW EXL BUILT A LARGE SCALE DIGITAL WORKFORCE FOR A LEADING ENERGY AND HOME SERVICES PROVIDER AND HELPED MAINTAIN ITS LEAD IN THE HYPERCOMPETITIVE UK ENERGY MARKET

Our client, UK’s leading energy and home services provider had begun feeling the heat.

The increasing entry of smaller, more nimble players since the late

‘90s, had turned the energy market in Britain hyper-competitive. The

dynamics of the energy market made it imperative for the company to

reduce costs and keep energy tariffs low, so that customers would not

switch to competitors. Solving this issue would take automating many

processes, fast.

With this in mind, the provider set up a robotics process automation

(RPA) centre of excellence (CoE) to cut costs through automation of

back-office processes. However, many of the company’s back office

processes were outsourced to vendors. A lack of detailed process

understanding could pose a severe risk to service delivery during the

course of the automation journey.

That’s why the company turned for help to EXL, their strategic partner

for business process management, transformation and analytics for

over 12 years.

EXL had been delivering improved revenue and compliance as well

as reduced cost of operations for the client for several years in a row.

Its domain experience and in-depth knowledge of the company’s

processes gave it an advantage in taking on the challenges of building a

large digital workforce within a short time frame. To do this, it brought

into play its global RPA development experience and robust proprietary

change management framework.

ContextUtilizing its deep knowledge of client’s back-office processes, EXL first

undertook a detailed RPA feasibility assessment to identify all the

processes that could be automated. The study encompassed over

500 unique processes across four lines of business and covered over

20 proprietary and third party IT applications that were being used.

EXL also identified several processes where internal transformation

initiatives were already underway that could conflict with

automation efforts.

Using the data generated by the feasibility study, the EXL team

categorized back-office processes based on their complexity. Then,

prioritizing these processes based on potential benefits, EXL developed

a phased approach towards automating them.

“ The dynamics of the energy market made it imperative for the company to reduce costs and keep energy tariffs low, so that customers would not switch to competitors. Solving this issue would take automating many processes, fast.”

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HOW EXL BUILT A LARGE SCALE DIGITAL WORKFORCE FOR A LEADING ENERGY AND HOME SERVICES PROVIDER AND HELPED MAINTAIN ITS LEAD IN THE HYPERCOMPETITIVE UK ENERGY MARKET

This approach had two components that would run in parallel. First,

redundant activities within the processes that were not adding value

would be eliminated. Second, the streamlined processes would be

digitized in three waves, beginning with processes of low complexity

and progressing to extremely complex processes.

An early pilot project had revealed that client’s systems and change

management policies were not prepared for large-scale automation.

For instance, the company’s HR systems and policies were not designed

to deal with a digital workforce that would not need payroll, or for that

matter, supervisors. The IT architecture would also need reworking to

allow robots to function efficiently.

With this in-depth understanding of the process landscape and

understanding of automation-related challenges, the EXL team

developed an outcome-linked commercial model with an innovative

per-BOT service charge.

OrchestrationEXL began fixing upstream and downstream system issues across

multiple processes, and started improving data quality. This reduced

unnecessary exceptions and, thereby, automation costs. In parallel, a

separate automation team took end-to-end accountability for process

diagnostics, documentation, solution design, development testing, go-

live, and ongoing bot administration.

Skillsets in the robotics domain are both rare and in perpetual short

supply. EXL began recruiting the right talent in earnest, onboarding

over 43 skilled RPA developers, four technical leads, and two technical

architects within seven weeks to setup an offshore RPA CoE for the

client. To support this technical talent, EXL also deployed over 50

quality analysts and process experts to provide the necessary domain

knowledge and reduce implementation risks. With this large team

on the job, and developers working in dual shifts, over 130 bots were

deployed in less than eight months, with 50 more added later. In all, the

initiative spanned over 80 process activities handled by 200 FTEs.

To tackle the company’s systemic challenges, EXL deployed its robust

change management framework, and actively co-ordinated between

client’s operations process owners, IS teams, the inhouse RPA CoE, and

finance and procurement teams to fast-track the change deployment.

OutcomesWhile many organizations have attempted large-scale RPA programs,

few have stabilized within such a short time frame, and fewer still have

achieved sustainable benefits. But, EXL’s digital workforce initiative has

achieved what was previously unimaginable.

Over 500,000 non-value adding transactions were eliminated without

any negative impact on customer experience. Over 180 bots were

successfully deployed across more than 35 processes leading to savings

of over 200 FTEs. The cost of offshore operations reduced by £0.77M

from 2017-2018 through automation alone, and the recurring yearly

savings because of the overall initiative are projected to be £1.7M.

With the new digital process teams ticking along smoothly, EXL has

also set up a digital command centre for real-time performance tracking

and alerts.

Given the success of its digital workforce, client has laid out a future

roadmap for more complex processes to be automated. EXL will

continue driving these future initiatives through leveraging more

advanced technologies such as machine learning, natural language

processing, fuzzy logic, and prescriptive models.

End customers are also benefitting from better customer service. For

instance, when maintenance requests spike during the winter, the easily

scalable bot workforce is able to process service requests faster and with

fewer errors.

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HOW EXL BUILT A LARGE SCALE DIGITAL WORKFORCE FOR A LEADING ENERGY AND HOME SERVICES PROVIDER AND HELPED MAINTAIN ITS LEAD IN THE HYPERCOMPETITIVE UK ENERGY MARKET

EXL (NASDAQ: EXLS) is a leading operations management and analytics company that designs and enables agile, customer-centric operating models to help clients improve their revenue growth and profitability. Our delivery model provides market-leading business outcomes using EXL’s proprietary Business EXLerator Framework®, cutting-edge analytics, digital transformation and domain expertise. At EXL, we look deeper to help companies improve global operations, enhance data-driven insights, increase customer satisfaction, and manage risk and compliance. EXL serves the insurance, healthcare, banking and financial services, utilities, travel, transportation and logistics industries. Headquartered in New York, New York, EXL has more than 27,000 professionals in locations throughout the United States, Europe, Asia (primarily India and Philippines), South America, Australia and South Africa.

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Client Challenge

• Hyper-competition in the UK energy market leading to pricing pressures

• Slow pace of internal automation efforts due to lack of process expertise

• Risk of a faulty implementation impacting customer experience

Context

• A detailed feasibility assessment identified processes that could be automated

• Predictive analytics helped develop a dual-pronged, three-phase approach for large-scale automation

• Systemic challenges to the success of the initiative were studied

• The outcome linked commercial model included an innovative per BOT service charge

Orchestration

• Over 40 skilled RPA developers onboarded within two months, and over 130 bots deployed within eight months

• Over 50 process experts brought in to support automation efforts

• Robust change management framework deployed

• Operations, IS, RPA CoE, Finance, and Procurement teams worked together to fast-track issue resolution

Outcomes

• Over 500,000 non-value adding processes eliminated without any negative impact on customer experience

• 180 bots deployed across over 35 processes with savings of over 200 FTEs

• Digital command centre provides real-time performance tracking and alerts

• Cost of offshore operations reduced by £0.77M in 2017-18

• Yearly recurring savings projected at £1.7M

• Future roadmap laid out for automation of more complex processes

SUMMARY

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