Offering a narrow set of products and prices to an equally narrow market segment proved a recipe for success for Canal Insurance—until the company was hit by the recession, rising fuel prices, and new competition. Sales dropped and Canal needed a new strategy. It decided to broaden its range of customers and identify new prices that made the company both more competitive and more profitable. Canal adopted a virtualized business intelligence (BI) solution based on Microsoft technologies. Virtualizing the solution kept costs low, while the new BI tools helped Canal to turn a revenue drop into a revenue gain of 17 percent. Total cost of ownership declined by 40 percent, and Canal is now better able to evaluate new products and prices quickly and effectively.Situation
“One size fits all” may be a way to sell T-shirts, but can an insurance company thrive with that philosophy? And if it can, what happens when times change and it needs a very different approach?
That was the situation confronting Canal Insurance, the Greenville, South Carolina, insurer specializing in the long-haul trucking market—the market for insuring drivers, their trucks, and the cargo they carry. Within the long-haul trucking market, Canal had a specialty in what the industry calls the “substandard” market—that is, customers with above-average risk. That higher risk can stem from drivers carrying highly perishable cargo, from the driving records of the drivers or the routes they had to take, or from the newness of a company.
||We’re seeing revenues and market share go up because we’re playing smarter. And we’re playing smarter because of Microsoft BI.
Chief Information Officer, Canal Insurance
Largely following a “one-size-fits-all” approach, Canal offered a narrow range of products and prices for trucking firms that might get unfavorable underwriting offers, or none at all, from other insurance companies, depending on the state of the insurance market. The relative lack of product and price differentiation kept administrative and management costs at Canal low—and Canal was happy to pass that savings on to its customers. Because Canal offered a consistent product, business was good, and Canal built it into a U.S.$500 million a year revenue machine.
Until the recession hit. Then, some of Canal’s customers went out of business; others became more price sensitive because of rising fuel prices and other costs. At the same time, insurance companies that had not previously competed for Canal’s customers needed more business to keep themselves afloat and suddenly came sniffing at Canal’s market. As a result, more insurance providers entered that market, cutting into prices.
In the changed business environment, the old, successful business model no longer worked as well. Canal customers that were less sensitive to minor price differences when times were good now sought out the lowest possible prices. Meanwhile, new insurance competitors had pricing infrastructures that allowed them to set prices that were close to the cost of providing their service. By offering slightly lower prices to Canal customers with slightly lower risks, these competitors were able to woo away some Canal business. Within two years, Canal annual revenue fell from $500 million to $186 million, a drop of 63 percent.
“That got everyone’s attention,” says Adrian Brown, Chief Information Officer at Canal Insurance, with some understatement.
But what was Canal to do to win back its market share and revenues? The company needed to compete more effectively in a more finely tuned market with narrower margins, so it set out to acquire the resources to do so. Until this point, it had a single product manager. Canal hired three more product managers to create and price narrowly differentiated products that fit the risk characteristics of the insured. But to obtain the data that they needed—data, for example, on so-called loss/premium ratios, which measure the costs that Canal experienced in payouts from a piece of business, compared to the revenue earned from that business—the product managers needed frequent, detailed data reports.
Product managers requested the reports from the IT staff, which ran them on the company’s IBM 3270 mainframe and newer databases running Microsoft SQL Server 2005 data management software, which were not yet configured for self-service use. In addition to requiring the efforts of four IT staffers, this approach was time-consuming at a time when Canal needed maximum agility to beat its competition.Solution
“Our new product managers wanted self-service tools to determine price quotes and identify product opportunities themselves, without having to wait for reports to be run off the mainframe or out of SQL Server by the IT staff,” says Brown. “We’d hired the experts; now we had to supply them with the right tools to do the job we expected of them.”
||Our new product managers wanted self-service tools to determine price quotes and identify product opportunities themselves, without having to wait for reports to be run.
Chief Information Officer, Canal Insurance
That was easier said than done. Having deemed the existing tools unable to provide real-time responsiveness, Brown and his colleagues looked at business intelligence (BI) packages from Cognos and BusinessObjects. “Those are older, less cost-effective technologies,” says Brown. “We didn’t want them.”
Planning an End-to-End System
Instead, Canal decided that the most effective solution was an end-to-end system composed of Microsoft technologies and built on top of the company’s existing IT infrastructure. Canal retained Incisive Analytics to develop the company’s road map for BI and to design the platform for the new solution.
“When Incisive Analytics said we’d need nine new server computers for the BI solution, I was concerned,” says Craig Colaluca, Infrastructure Manager at Canal Insurance. “Our data center had grown because whenever we had a new project, we bought another server, or three servers, for development, test, and production. Now, we had no rack space, no time, and no personnel for another nine servers.”
Canal had no rack space, time, or personnel for another nine physical servers, that is. But it had experience with virtual servers—mixed experience. It had virtualized some of its systems a few years earlier, using VMware technology, which it found expensive to license and difficult to use. The company then tried an early version of Microsoft virtualization technology, successfully.
That success led Incisive Analytics and Canal to now consider current Microsoft virtualization technology: the Windows Server 2008 R2 operating system with Hyper-V technology. The Microsoft virtualization software offered support for the potential BI solution without additional operating systems or software layers. And it fit seamlessly into the company’s existing environment.
One point that Canal and Incisive Analytics confirmed before moving forward was the ability of Microsoft SQL Server 2008—the intended host for the data warehouse at the heart of the new solution—to run effectively in a virtualized environment.
“People assume that SQL Server needs a lot of physical resources,” says Colaluca. “But our research indicated that the software would run just fine in a virtualized environment. The transfer rates between servers would be even faster than in a physical environment because those transfers would be happening in memory, not across physical network links.”
Making It Happen
To install the virtual environment, Canal engaged Intellinet, a Microsoft Gold Certified Partner. Intellinet deployed a pair of Dell R710 computers with two quad-core processors on each. One host server runs six virtual servers: a trio of database, analysis, and reporting servers for the development environment, and a parallel set of database, analysis, and reporting servers for the test environment. The second host server runs the database, analysis, and reporting servers for the production environment.
Putting the production servers on their own host servers provides the most RAM and compute resources for the servers that would need those resources the most. The data warehouse includes seven years and 2.5 terabytes of data in the production environment; earned premium data constitutes 3 billion rows in one table.
To help ensure the high availability that Canal wanted, Intellinet set up the two physical servers as a cluster; if one computer should go down, the other can keep data flowing seamlessly to users.
||We’d hired the experts; now we had to supply them with the right tools to do the job we expected of them.
Chief Information Officer, Canal Insurance
The data for the solution originates from three key sources: the mainframe, which hosts aggregated policy premium data; an existing SQL Server–based database, which holds data about claims; and another SQL Server–based database for detailed policy, coverage, and vehicle data. The solution uses SQL Server 2008 Integration Services to bring that information into the data warehouse. From there, the solution generates four SQL Server Analysis Services cubes, which contain data on policies, claims, premiums, and loss/premium ratios.
Product managers and others access the BI information through an intranet site running on Microsoft Office SharePoint Server 2007. SQL Server Reporting Services generates easily accessible reports on the data that is used most often and gives Canal the ability to customize more reports as needed. Users with advanced skills can access the cubes directly and conduct “what-if” and other analyses using Microsoft Office Excel 2007 spreadsheet software and PowerPivot for Excel 2010. Users can define their reporting requests, and ask for both summary and detailed information, using drop-down menu selections.
Now that the initial BI solution is in deployment, Canal executives plan to expand it in several ways. For example, as users become more comfortable with it, Canal plans to add BI functionality such as “heat maps” and “dashboards,” which will display data graphically for at-a-glance viewing. Canal also plans to quickly upgrade to Microsoft SharePoint Server 2010 to take advantage of features, such as PowerPivot for SharePoint Server 2010, that make it easier for users to analyze massive amounts of data while collaborating with other users on those analyses.
Brown also envisions expanding the BI solution with a fifth SQL Server Analysis Services cube that hosts data about the performance of Canal agents. This cube would be accessible through a Canal extranet to agents located outside of the company’s network. It would enable those agents to review their performance at any time and motivate them to improve their performance. The cube would also be a way for managers to gain real-time understanding of the performance of their field agents, in order to address issues or adapt to changing needs at the earliest possible opportunity.Benefits
By succeeding in its goal to offer more competitive products and prices, Canal has started driving up revenue and market share, and made it possible to expand its market. At the same time, it’s seeing operational efficiencies and a lower total cost of ownership.
Boosts Revenues by 17 Percent
Since the deployment of the BI solution, revenue has climbed 17 percent and Canal is being asked to quote on a wider range of business. Policy and transaction counts are up, too.
No single factor achieved this turnaround, but Brown says that the commitment of the company’s product management to both personnel and the new BI solution was a key ingredient of his company’s renewed success.
“We’re seeing revenues and market share go up because we’re playing smarter,” says Brown. “And we’re playing smarter because of Microsoft BI and features including self-service, and reporting and analytics. They have helped us to improve our profitability and service models. Our BI solution is in its early days, but we are providing better information and, in some cases, information that really was not available before. This is a new system, and it will take time to fine-tune it to our needs, but now we have the right tools and platform. The sheer amount of data we have requires different processes and thinking, all of which need to be learned and incorporated into our work processes. The Kimball Data Star methodology is the foundation, and it consumes servers, storage, memory, and processing. It’s a truly great concept that necessitates rigorous architecture and platforms.”
Enables Broad Expansion in Addressing a Range of Risks
To replace its old “one-price-fits-all” pricing, Canal can now determine proper prices for the range of risks that it wishes to address. Product managers are using the BI solution to identify new pricing opportunities that give customers better prices yet help to ensure that Canal can offer the new products at a profit. That gives the company the ability to offer far broader choices to potential customers.
As part of its development of new, competitive prices for a broader range of risks, Canal is starting to use the Microsoft BI solution to analyze loss/premium ratios by every rating variable and loss category; gain visibility into business development activities in the agency channel; and obtain transaction-level detail for trending, benchmarking, and auditing activities.
“Without the Microsoft BI solution, we couldn’t offer the increased range of differentiated products that our customers want,” Brown says. “We couldn’t make the business decisions that we need to make to respond to changing market conditions so quickly. And we couldn’t respond with products at prices that are both attractive to our customers and profitable to us. This could never have happened if we’d stayed where we were with technology.”
Provides Data to Expand Markets and Make Operations More Efficient
Canal is putting the new real-time data and analysis to use in ways that go beyond the primary goal of increasing product differentiation for greater competitiveness.
For example, Canal is using data and analysis from the Microsoft BI solution to expand its geographic reach to the few states in which it is not already operating. “States differ in their regulatory requirements, but most want extremely detailed information about rates, the pricing model on which those rates are based, and the impact of rate increases over a range of variables in that model,” says Brown. “The Microsoft BI solution will give us a way to meet regulatory requirements more easily than we ever could before, making it more practical and possible for us to move into additional markets.”
Canal will also put Microsoft BI data and analysis to use in other ways that it didn’t originally anticipate. For example, the solution can help Canal to detect insurance fraud, by matching policies to claims in ways that human analysts might miss. The data and analysis also can be used to spot sales trends earlier than otherwise possible and to address those trends to improve the bottom line. The solution might identify offices that are underperforming, giving Canal the ability to add resources to those offices or take other steps to boost performance.
Reduces Total Cost of Ownership by 40 Percent
The use of the Microsoft BI solution instead of Cognos or BusinessObjects, combined with the choice of Microsoft virtualization technology instead of VMware, significantly reduces licensing costs for the new solution. VMware, for example, requires a separate licensing fee for each virtual machine deployed; in contrast, Microsoft licensing includes four virtual machine licenses with every license for Windows Server 2008 R2 Enterprise. As a result, Canal can deploy up to four virtual machines per computer without an additional charge. Considering the reduced licensing for both the Microsoft BI and virtualization technologies, Canal saw significant savings in software costs.
Hardware costs were also lower because Canal adopted a Microsoft virtualization solution. Instead of buying, servicing, and ultimately replacing nine computers, Canal bought only two computers. Even when the higher per-computer cost of the computers hosting the virtual machines is factored in, Canal estimates that it spent 62 percent less on new hardware because it chose Microsoft virtualization.
What’s more, Canal finds that the virtual environment is more reliable and available than a physical environment is, further reducing costs by reducing maintenance needs. “Since we clustered our two host servers, we simply don’t have to worry about the Hyper-V–based environment,” says Colaluca. “It’s highly reliable and SQL Server is highly reliable. I can walk up to one host server and unplug it, and the virtual machines will continue to live on the other host. And when there are problems, they’re more easily resolved; something that might have taken us down for a day or two on the physical environment takes us down for only five minutes in the virtual environment.”
Maintenance is not just faster; it’s more convenient, too. Colaluca was pleasantly surprised the first time he reconfigured the random access memory allocations on all nine of the virtual servers—through a remote connection from the comfort of his home.
The company also saves by eliminating the need for additional IT professionals to run reports for business managers. Because the reports can be run more quickly by business managers themselves, the IT staff is freed to pursue more value-added functions for Canal.
“We adopted this solution to grow revenues and be more competitive,” says Brown. “But we’re also seeing total cost of ownership drop by as much as 40 percent.”
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