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On the Journey to the Hybrid Customer with Process Mining

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by Lars Rautenburger & Alexander Liebl
September 02, 2020
10 min read

Digitization! Not in the future, but now!โ€ Statements such as these circulate across all industries around the world. Especially in the insurance industry, professionals hope to achieve efficiency but often lack the time theyโ€™d need to solve the snags in their internal systems.

Insurers who have consistently implemented Process Mining have been able to achieve a decisive competitive advantage, not only during the Covid-19 pandemic, but in a sustainable way that will likely stick around well into 2021 and beyond. Even purely offline customers are now confronted with new sales channels such as online and social media channels, orders made by telephone, chat and video chat. Itโ€™s becoming increasingly difficult to stay analog, although many insurance professionals fear change.

Customers who have appreciated on-site contact have so far mostly valued the experience of personalized consultation, but new technologies allow brands to recreate this process online. Think of social media feed algorithms, personalized email marketing, and content experiences like quizzes, assessments, and calculators.

Of course, a company can build any number of digital tools, but itโ€™s another process entirely to lead customers in. Customers will test the offered channels, gain experience and gradually find their new favorite channel that meets their needs. Theyโ€™ll make purchase decisions based on a myriad of factors, as all decisions are made in our digital world. Sometimes the price is decisive, sometimes the quality of service. If a customer is on the phone with a company one day, they may visit the companyโ€™s website the next day, and eventually set up a video sales call. They may also sit in a nurture sequence for weeks before making a choice either way. But classic tools for tracking the progress of a coverage application in the sales process (customer journey tracking) are not designed for this channel mix. They do not deliver meaningful insights for the entire process but focus on web analytics for the online part or the tracking of a telephone call. A change in channels is too much for them to handle, which is not surprising, since this requirement has never been made for these tools and techniques in the past.

However, each of these customer interactions leaves traces in the respective systems. Even if the tools currently in use are being superseded by a change of channel, more and more insurance companies are succeeding in consistently embedding the various channels in the central offering system enabling the customer to start a customer journey on the phone and complete it. For example, in the online rate calculator, a customer can get what they need without having to start the application process from scratch.

We are talking about a โ€œseamlessโ€ omnichannel change to the offering process, and the basic magic formula for this shift is to make the unique ID (usually the offer number) visible on other channels and to import the already collected data into other channels as a starting point or to make it available for retrieval. Of course, thatโ€™s impossible to implement without a system as sophisticated as Process Mining.

Here, the customer journey is successfully tracked, and the transparent customer suddenly becomes tangible as soon as the first information transfer from the respective application process to the central offer system takes place and a clear assignment of the offer number is guaranteed. The previous snag with the supposed tangibility and presentation of the Customer Journey was requiring manual effort by IT specialists, which is why the existing data, found in the depths of the offering system, was usually only involved in the event of error handling with complex SQL queries.

Process Mining - The new cross-channel transparency of real processes

However, with the development and establishment of the Process Mining technology, a procedure was created which represents exactly this data capturing in an automated and visualized way. Existing, but frequently unused, data is automatically processed without great effort in clickable and evaluable, up-to-date process images. You can zoom in on a specific process run from the surface down to the individual process step execution via โ€œdrill-downโ€ simply by clicking on it.

Process Mining thus enables companies to record their business processes based on their data, to reconstruct them automatically, and to analyze them in detail. In other words, itโ€™s a reverse engineering procedure that carries out process reconstruction and visualization with the aim of using transparency to identify weak points and therefore optimize across the board. Classically, Process Mining is used to figure out why a process execution does not perform as expected. But Process Mining is also suitable for cross-channel customer journey tracking, and thus it reveals another useful application scenario to make the most flexible of all target groups into something easy to understand.

For this purpose, only a bit of minimum data is required. You need the offer number and the associated activities. All of this data is lying dormant in the offering systems that strive for seamless capability to meet the needs of the hybrid customer. Reading this data using process mining enables dashboard-based transparency, with clarity on which channel the customer engaged with and what the customer journey looks like.

Combine this newly gained and previously unattainable transparency with the appropriate questions when considering the respective customer-specific customer journeys and youโ€™re able to see the interplay and the resulting fields of action, thereby increasing the conversion rate.

A use case: Process Mining as Game Changer

Is the exit rate at certain defined measuring points (e.g. after filling in a certain field or exceeding a sub-step such as tariffing) the same for all channels? If there is a significant difference between the channels, the question of the cause arises. A company must figure this out in order to counteract this issue and reduce the number of dropouts.

A typical problem case: the customer often drops out of the online rate calculator at a point where the customers on the supported channels (e.g. telephone/ video chat) normally do not. It is necessary to analyze the customer's guidance through the online rate calculator at this point. Presumably the field description or desired input type is not target-oriented and overstrains the customer.

As there were previously no automated reference values to other channels coming the online rate calculator, it is quite possible that the team identified this as needing to be optimized, but never prioritized it. Thanks to cross-channel Customer Journey Tracking, a best practice that is already in place, business can now be transferred from this individual case analysis to other channels in order to achieve a higher overall closure rate.

Another application for process mining in the insurance industry that has been successfully tested is the claims management process. From the customer's point of view, it is clearly necessary to increase the process speed in order to become more customer-friendly and at the same time to reduce the process costs for one of the most cost-intensive business processes in the insurance industry.

But as with everything new, insurance companies tend to be skeptical of new and promising technology, and have to do testing and evaluation before it can be recognized as a game changer. The fears that large up-front investments will have to be made in process mining and that the next long runner is in the pipeline are understandable. IT projects and supposedly โ€œout-of-the-boxโ€ approaches have often left scorched earth, making it nearly impossible to recoup investment if the initiative is abandoned.

Only clarity and facts can remedy this situation:

1. After a short look into the systems it becomes clear that the necessary data is available and that no fundamental interventions in running systems are necessary.

2. It is not an implementation project, but rather an optimization measure that is built on a real database, where the short time-to-value is the most important factor.

Greatest chances of success and minimized risks due to the โ€œProof of Valueโ€

The application of a validated best practice approach - the so-called proof of value - ensures this. Within approx. 10 weeks, a business case is created that is self-sustaining and pays off on the strategic company goals. At the same time, the proof of value only requires a small amount of input (e.g. granting access rights to necessary tables) from the company, which wants to analyze its processes and gain an impression of its real process flows.

The necessary and appropriate alignment of the business case including on-going projects and the all-encompassing embedding in the digitization strategy is carried out by the specialist and technology consultant, while the process mining tool providers fulfill their obligations to cooperate mainly in their role as technology providers.

In order to ensure that the business case and the identified potentials develop their full effect, it is important to plan each individual measure based on the needs of the organization before implementation and thus decide on the best possible implementation according to the specific needs and application. This is the core idea underlying ifb group's Value First Principles.

In principle, the following must be observed when prioritizing and implementing measures:

a) Is it a quick win or a medium-term optimization measure?

b) How can it best be integrated into the current digitization strategy and ongoing projects, where are there dependencies?

c) How can the affected target groups be successfully involved in the implementation at the different working levels in order to enable their participation and early influence? RPA, for example, can be a good solution for quickly adding value by automating manual work steps with a software robot and thus exploiting automation potential. However, RPA is not always and inevitably sustainable in the long term and, despite meaningful motivation, can lead to major upsets and unrest in the absence of or incorrect communication. It is essential to focus on the added value and the overall picture of the organization rather than targeting a specific technology that only partially meets the requirements.

Take all parties involved โ€œon the journeyโ€ with you

Especially for optimization and, if necessary, automation, it is essential to live transparently and to include all parties involved at an early stage. During implementation, it is important to work in partnership to achieve the goals, because every optimization also means change, and these must be introduced with professional expertise, a sound knowledge of human nature and the necessary sensitivity. This is the only way to ensure that the Process Mining initiative and its added value flourish everywhere and that employees, sales partners and end customers are open to the opportunities offered by digitization and actively accompany the change.

In order to make this all-encompassing transformation possible and to accommodate all interest groups, a multidimensional and interdisciplinary approach is required. All digitization initiatives must combine functional versatility and process-related expertise with a strong understanding of technology and many years of specialist insurance expertise.

This article first appeared in German inย Zeitschrift fรผr Versicherungswesen in der Ausgabe-Nr. 13/2020.

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Lars Rautenburger & Alexander Liebl
Director Operational Excellence & Process Mining Expert - IFB Group

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