Robotisation: it's time to industrialise | Insurance | Deloitte

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Robotisation: it's time to industrialise

Dutch Insurance Outlook 2017

Over the last years, Robotic Process Automation (RPA) has gradually moved through the stages of the hype cycle and today it is at the peak of expectations. Insurance companies have valid reasons to be highly interested in the concept of RPA, as they have many activities with a high potential for automation. We provide five main enablers that help to ensure a successful scaling up of RPA within an insurance context.

Various studies concluded that the majority of all activities performed by an insurer today can be automated by using currently available technologies like RPA. For example, the collection and processing of data in a rule-based manner. Our experience has shown that proper deployment of just one robot can result in savings in the range of four to eight FTEs.

Many insurers have already experimented with a ‘proof of concept’ to investigate the potential and technical feasibility of RPA within their organisation. However, scaling up the use of RPA remains a challenge. In many cases, the use of RPA remains rather limited and RPA is considered ‘just another IT tool’. While in fact it can be so much more. Full-scale deployment of RPA, driven by the business, can revolutionise the way we work today. It can even impact the outsourcing decisions that have been made in the past, as process robotisation is becoming an attractive alternative to traditional labour arbitrage. 

When scaled properly, RPA can result in breakthrough improvements in costs, quality, and operational risks. Five main enablers help to ensure a successful scaling up of RPA within an insurance context:

1. Make it strategically important
2. Create demand
3. Implement quick and principle-based decision-making
4. Remove barriers for RPA development
5. Sell the change

Dutch Insurance Outlook 2017

New winds of opportunity

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1. Make it strategically important

One of the largest inhibitors that prevents RPA from delivering its full potential is the lack of appropriate strategic positioning and a clear growth strategy. Traditionally, the strategic change agenda for insurers has been dominated by large transformations that aim to realise high business value, often accompanied by high complexity and a need for endurance. RPA implementations are, often mistakenly, associated with lower benefits and therefore approached in a more operational manner, with relatively low management attention, priority, and budget. However, due to the short delivery cycles and high applicability in the insurance landscape, RPA can actually contribute significantly to strategic industry targets, moving beyond short-term operational cost reductions. Some examples are:

• Increase Net Promotor Score by implementing RPA in critical customer journeys and enabling employees to spend their valuable time on interaction moments that really matter.

• Increase workforce flexibility by embracing the unlimited amount of virtual resources RPA offers. It can support one-off data cleansing and compliance projects, for example, or flatten peak loads and process backlogs in back-office processes.

Reduce operational risks by eliminating human shortcuts and workarounds, replacing unstable macros, and establishing 100 percent accurate audit trails in RPA logs.

Lower the cost ratio by eliminating manual, repetitive work on active or run-off portfolios on legacy systems.

The strategic intent should be set-out in a clear RPA vision that acts as a single point of direction for the roll-out of RPA. It should clarify how RPA contributes to selected strategic objectives within the organisation. The vision should be concise and accessible, owned by an executive business sponsor and created in close collaboration with Business, IT, and HR. The vision can be translated into a concrete growth strategy including SMART goals for the deployment of RPA. ‘Start small, organise big’ is advised as a guiding principle for large-scale implementation.

By making it a strategic priority, RPA has the ability to be more than ‘just another IT tool’ and grow into a business-driven, full-scale solution that contributes significantly to the company’s strategy.
 

2. Create Demand

Once the vision is clear, it is time to start creating demand for RPA in the organisation. Selecting the right processes to be robotised using RPA is one of the most important key success factors.

In order to scale fast and fully leverage the potential of RPA, there should be substantial demand, with sufficient feasibility and potential. We advise a combination of bottom-up and top-down demand generation.

Bottom-up demand generation is all about mobilising the insights on the work floor. It starts with creating awareness about what RPA is and where it can be applied. Town hall sessions and awareness workshops are some examples of how this can be put into practice. Next, a simple and clear mechanism for idea generation and collection should be put in place, which employees can use to articulate their ideas. This process should already assess the proposed use case on basic knock-out criteria, such as the absence of rule-based, structured data.

A prerequisite for successful bottom-up demand generation is that employees feel secure. If cost reduction or productivity increase is the main objective of implementing RPA, employees will probably not be inclined to put forward their best ideas. Investing in a sense of security and providing incentives can counter this risk to a certain extent. However, in order to ensure that all RPA potential comes to the surface, it is worthwhile to also engage in top-down demand generation.

Top-down demand generation starts by translating the strategic objectives into value drivers and cost drivers. For cost reduction purposes this will translate into drivers like FTE reduction and outsourcing spend. If quality improvement is the objective, the focus will be on drivers like the first-time-right-percentage, number of complaints or failure cost. Once the key drivers are identified, a business analyst will typically start a company- or department-wide analysis to determine where the most impact can be made with the least amount of effort. The Pareto principle is often applicable: 20 percent of the processes harness 80 percent of the potential. The top-down analysis focuses on determining the feasibility of RPA automation and the potential of end-to-end value chains. In contrast, bottom-up analysis often mainly focuses on tasks and sub-processes.

The combination of both types of demand generation will result in a richly filled pipeline – or roadmap – of processes in the organisation that have the potential to be automated.
 

3. Implement quick and principle-based decision-making

Next, a clear procedure and governance for prioritising and planning should be put in place. Experience shows that a complete and fail-proof set of decision criteria is hard to set up, and can lead to unnecessary bureaucracy.

Formulating a basic set of principles for prioritising, and setting up an effective decision-making body have proven to be more effective. The principles should clarify what the primary objective is and how parameters like business case, quality, risk, and client satisfaction are weighed.

The scope for application of RPA also needs to be set:
• Are we going to apply RPA to business critical processes?
• Are we going to make changes in our core system to resolve the issue or will we apply RPA?
• Are we first going to optimise before robotising?

To ensure employees keep a sense of security, as mentioned earlier, inclusion of a people-oriented principle is recommended. This will lead to questions such as: “Is the key focus to reduce costs or is the focus to perform an increasing amount of work with the same amount of people?”

The decision-making body should at least include executive representatives from the business, for example from Claims, IT, and Risk. The frequency of the meetings depends on the degree of scaling and should align with the intensity with which new processes are being automated.
 

4. Remove barriers for RPA development

Once the right processes and priorities are determined, and the decision-making body is in place, it is of crucial importance that all barriers for RPA development have been removed. This means that the required architecture and infrastructure have been set up and made available, and that contracts with selected solution vendors are in place. Standard roles and responsibilities need to be defined and a comprehensive training curriculum should be in place. In order to counter a potential shortage of development skills or capacity, it is advisable to have contracts with external partners in place to provide support. This provides extra flexibility for scaling up quickly if necessary. When combined with a result-based fee model, this is an effective approach for realising the desired benefits.
 

5. Sell the change

When scaling up, things get real. And when things get real you’d better be prepared. Firstly, a ‘burning’ platform has to be created to raise the sense of urgency and to get people moving. Secondly, a compelling change story needs to be told that articulates the why, how, and what of the upcoming transformation and its impact on customers, employees, society, and shareholders. Thirdly, employees have to be given clarity about the impact RPA has on their own jobs.

Cost reduction is usually the primary objective of introducing RPA and people may lose their jobs. What will the procedure look like and what are the available options? In our experience, employees are often pleased to be able to perform activities with more added value and we see that savings are often achieved, not by letting people go but through recruitment stops. It could however be useful to involve the works council at an early stage in order to get a full understanding of the upcoming changes.

If productivity is the main objective, i.e. ‘doing more with the same number of people’: what are the growth areas and corresponding roles, and how will the transition take place? If quality improvement or increased value creation.
 

Making it real

The previously mentioned five key enablers allow insurers to successfully scale RPA. Setting up a Centre of Excellence (CoE) is a proven way to successfully operationalise these enablers. Depending on the organisational structure and robotics strategy, a CoE can be set up centrally, decentrally, or in a hybrid form. After ‘starting small’, it is now time to ‘organise big’. The pace of scaling will go hand-in-hand with the effort put into the enablers and the impact made by the deployment of RPA. Strong benefits management and communication of results will furthermore act as a catalyst for implementation. In the near future, the virtual workforce will gradually take on more intelligent work by means of cognitive solutions, which can be integrated within the RPA workforce. For now, the technological readiness of RPA can already provide significant benefits for repetitive, rule-based tasks. Many Dutch insurers have experimented with a proof of concept, or even successfully implemented an RPA in a pilot. So, the technology is there and has proven to be ready for Robot Process Automation!
 

Resources

1 Deloitte (2015)

More information?

For more information about robotisation in the insurance industry, please contact Arjen Beers via abeers@deloitte.nl / +31882881236.

Dutch Insurance Outlook 2017

New winds of opportunity

Request report
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