Waiting for (Business) Intelligence

Business Intelligence is a collection of technologies and processes managed by a competency center to ensure that business users have the data they need to make sound decisions. The Competency Center manages the BI infrastructure and applications, ensures data quality, allocates priorities for delivering new information to the community and oversees the evolution of BI assets.

BI relies on data sources (e.g. policy management and claims systems) which are resourced through a central location (the data warehouse). This data is integrated to support viewing the business in all its dimensions (e.g. premiums and experience by product line and territory) as well as trend analysis and, ultimately, predictive analysis. Data marts deliver this data through analytical reporting tools. Information can be viewed via a workstation, laptop or portal.

Given the high initial costs of business intelligence (BI) program deployments, insurance organizations of all sizes continue to ponder how to obtain value out of these programs in such a way that they become self-sustaining over the long term. This is a particularly poignant question given that the benefits of BI have been hard to quantify. Yet, for any innovative BI program to succeed, insurers must be confident in their investment.

Measuring if BI Works

Fortunately, there are proven ways and approaches to measure whether or not a chosen BI program will deliver maximum value. Regardless of how a specific program is developed and implemented, each BI program should deliver the following:

  • Competitive Advantage: This can be gained via a number of strategies such as aggressively pricing products, better segmentation of risks, deliberate anti-selection, cross-selling accommodation products, indeed, a whole gamut of approaches in line with the overall Enterprise plan. The common thread however is access to information and the use of analytics for selecting and modulating the best set of business strategies.

    For example, a carrier may elect to aggressively price residential risks in a certain market. Some of the fundamental analytics that must support this strategy could be to gain visibility into the number of dwellings insured, their loss experience, risk exposure and other attributes that would help in pricing such risks better. It is safe to say that for most companies, without BI these rather simple questions are not so easy to answer.

  • Operational Efficiency: This can be attained by deploying BI applications to optimize an existing process. For example, reporting to the IBC automobile statistical plan (ASP), that sets the data submission requirements, is at its core, a data integration problem that can be easily solved with a BI infrastructure. Frequently, the IBC makes changes to the reporting content and formats. Quickly adapting to data submission requirement changes and reducing the propensity for filing errors are operational efficiency gains of a well architected insurance BI platform.

For direct carriers or brokers, increasing the efficiency and therefore, reducing the costs of claims servicing is another immediate benefit of sound BI deployments. This is particularly true as many carriers attempt to tighten the timeline between a reported claim and its resolution.

Technology is not the Problem

Most insurance companies understand the advantages that Business Intelligence (BI) can bring to the table: increased efficiency, greater accuracy, improved turnaround and customer service, streamlined reporting – the list goes on. However, many BI initiatives have failed for a number of reasons, ranging from the lack of executive sponsorship to bad architecture design decisions. Others are hampered by complex and disparate legacy systems, multiple lines of business, mergers and acquisitions, and escalating infrastructure and integration costs. As a result, even for those that have invested in BI solutions, the results have often fallen short of expectations.

At the heart of the issue is the fact that many consider BI to be a technology problem. In actual fact, it’s a business dilemma—a problem that demands the attention and buy-in of CEOs/CFOs and Chief Risk Officers.

For anyone tasked with the responsibility of developing (or reconfiguring) a BI program to obtain maximum value, there are a few factors that help drive success:

Step 1: Develop a BI program with a strong business strategy alignment

A Business Intelligence program must have a strong affinity with a carrier’s strategic plan. The overriding principle of the program is how its deliverables, over time, promote the use of information to support the business strategy. For example: If a carrier’s business strategy includes the continued development of strong broker relationships, a BI Program will include objectives to support “information based interactions” with brokers.

A corporation may focus on attaining a minimal Combined Operating Ratio (COR) to strengthen its position for future investments. In this case, a BI program would put a strong emphasis on sophisticated analytical capabilities to find pockets of profitability in its portfolio.

Step 2: Develop and follow a clear change management strategy

According to Manon Champagne, President, A+ Transition, a Montreal-based change management firm, “the objectives of a BI program will never be met by technology alone. Indeed, no matter how much money is spent on the BI infrastructure, if people do not embrace new practices, behaviours and mindsets, a BI program will have no real impact on the bottom line.”

She goes on to say, “It’s a common mistake to believe that a technology investment alone will spur change in the enterprise. Investing time in managing the adoption of this technology is critical to getting the expected ROI.”

A successful BI program therefore requires the management of sometimes deep cultural changes. Striving towards the vision of an informational culture and adopting best practice process changes in managing decision support, demands a carefully planned and executed change management strategy that is tailored to the dynamics of P&C.

Step 3: Adopt the right decision support architecture

Adopting the right decision support architecture for P&C is akin to building a house: a weak foundation may be able to support a single floor but anything more will make the whole structure tumble to the ground.

For a P&C BI program to be effective, the ideal target architecture must be kept in focus at all times. This architectural blueprint is called the Corporate Information Factory (CIF)—not to be confused with client information file. The CIF clearly lays out the components of the BI system and ensures that applications deliver the expected analytic capabilities. A properly deployed CIF will also allow the company to start cutting ties with legacy reporting systems. This step, over time, ensures that reports are based on a single set of numbers and generates savings by eliminating multiple reporting systems.

Step 4: Deliver “something new” on a regular basis

Most BI initiatives are characterized by a large initial investment that includes technology, development and change management. During this initial phase, expectations must be tightly managed since the user community may not see a first application for months. A properly devised program ensures that past this initial phase, application “releases” within the BI system occur on a regular basis.

An application release includes the addition of new data sources, new paths to drill into existing data, new attributes (of a policy, risk or claims, synchronized with the capture of these data elements in the operational systems) or new standard reports and metrics.

When new functionality is delivered on a regular basis, the user community at all levels of the enterprise will engage with the program and become active participants of an informational culture.

A level playing field

A decade ago, only larger carriers on the cutting edge of technology were considering BI investments of any significant scale. Today, however, the majority of P&C insurers realize that better access to management information and the ability to “drill the numbers” are necessary in order to play in today’s competitive environment. Today’s BI solutions can level the playing field by enabling relatively smaller insurers to compete more intelligently.

A sound, long reaching program that includes technology, process and change management however, is key to leveraging BI to its full extent and achieving the anticipated rewards.

Philippe Torres is President and founding partner of SQLiaison, a Canadian leader in Business Intelligence solutions for the Insurance Industry.

Cost Reduction and Compliance:

According to Carl Lambert, Director Actuarial Research and Analytics at Co-operators, using BI for the purpose of regulatory reporting can dramatically reduce operational costs, especially when planning for the sometimes frequent statistical plan changes issued by the Bureau. Another advantage is that operationally, BI provides a uniform view of key indicators.  Reconciliations efforts between financial statements, rate filings, internal reports and regulatory reporting are greatly reduced.  Finally, regulatory reporting provides information on data quality, which in turns, can be used to improve data quality either at the operational source or in the data warehousing process.

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