Insurance companies have seen the shift to online self-service go mainstream over the last year and a half, and are now at a point where they must pivot if they want to meet the evolving demands of today’s customers.
To do so, it is paramount that insurers harness technologies that will enable them to make data-driven decisions central to their operations. This will be key in avoiding investment missteps and failures.
Process intelligence uses an organization’s own data from both digital and physical sources to discover patterns and insights that provide full transparency into the steps involved in a given process. Then, the organization can use that information to identify duplications, waste, bottlenecks and performance gaps to manage business process executions more efficiently.
With evolving customer behaviors, new competitors within and outside the industry, changing demographics, shifting compliance standards and the continuing pandemic, it is mission-critical for companies to have end-to-end process transparency to understand what, how, who, when and why they are conducting these process steps (such as payment processing, order to cash and escalations) to operate more effectively.
Insurers need a strategy based on data-driven, actionable insights to optimize their processes, help improve collaboration across their organizations and demonstrate regulatory compliance. All too often, companies make investments in modern, digital technologies without fully understanding how to use those technologies to their full potential. Simply investing in technology will not get the return on investment a company seeks; rather, the business needs to use that technology to assess and—as needed—transform its processes.
Finding untapped value
As insurers seek to improve the customer experience, reduce operating expenses and increase value, examining transactional data to understand what people, machines and organizations are actually doing (or not doing) can help tell the real story.
Those who monetize operational data will find themselves understanding their opportunities, making better decisions, reducing their costs and serving their clients in a quicker and more meaningful way. With extra insight into their organization, insurance companies can model specific decisions more accurately before taking them across the enterprise.
Let’s look at the initial step in a standard claim process—the first notice of loss—as an example. Generally, this process involves confirming the customer’s identity, locating the policy number, updating contact information, updating the loss description, taking a statement, verifying damages and triaging the claim—and that’s not even an exhaustive list. In this case, process mining can help create a detailed understanding of every step the customer representative makes to intake the claim.
Implementing process intelligence can allow companies to put together this detailed understanding in hours or days, rather than weeks or months like a more traditional analysis would require. This can give insurance companies a strategic advantage and improve customer satisfaction, quality and performance. To increase returns on investment, insurers can use advanced analytics to identify process steps that the organization didn’t know were occurring such as late or multiple escalations, missing information, handoffs, the number of touch points with the customer and manual workarounds.
Typically, what we have found is that organizations can improve the customer experience by providing first-call solutions, which decrease the number of touch points, handoffs and escalations needed. This can also save time and money for the organization.
Best practices and benchmarks
The granularity and breadth of data derived from process mining allow insurers to identify best practices and benchmarks for processes across different lines of business as well as compare one office to another, one person to another or one unit to another.
This sheds more light on best practices, where they are being followed, where processes are breaking down and where performance improvements need to be made, but they aren’t always visible to managers. The specificity of this data also means companies can access a wealth of information that goes well beyond the anecdotal.
Once organizations understand process patterns, they can identify hidden opportunities to reduce costs and improve quality and performance.
Integrating process intelligence for the strategic and operational management of the insurance business, overcoming divisional silo structures and barriers can set a company apart from its competition.