Year-Over-Year Comparison: Modest Growth, Big Shifts in Spending
We queried companies about their planned spending in five major areas:

• Business intelligence (BI) tools
• Dashboards and scorecards
• Planning, budgeting, and forecasting (PBF) products
• Analytic applications
• Analytic infrastructure that supports all these activities

The following are some trends we uncovered:

• Not surprisingly, the dashboard and scorecard segment is on fire—a reflection of the number of inquiries we get from customers about these subjects.
• BI is also on an upswing, but camps are forming around three types of providers—best of breed, platform vendors, and enterprise application providers. Generally speaking, manufacturers are more strongly aligned with their enterprise application vendors and services firms are more in synch with best-of-breed competitors. Both segments have healthy platform supporters as well. We expect a more competitive market for these software firms in 2006.
• Although PBF products show a slight decline in spending, they are deemed the most strategically important EPM investment in 2006, slightly exceeding the importance of BI. Interestingly, manufacturers mentioned these products much more frequently than services firms. More than half of the firms surveyed indicated they have an operational system in place.
• The large decrease in analytic applications and slight decrease in analytic infrastructure are not easily explainable. In fact, it makes us scratch our heads and wonder why since inquiries from customers are veering more into these areas. The biggest impediments companies have in deploying performance management are access to enterprise-wide data and data from customers and suppliers outside the four walls of the firm.

• Traditional purchase models of seat-based pricing, site licenses, term licenses, and value-based pricing still make up nearly 80% of buyer preferences.
• Anywhere from 17% to 23% of companies, depending on the EPM investment area, would prefer an SaaS or on-demand purchase option, with service companies preferring this model significantly more than manufacturers. But we’ve also noticed an uptick in interest the past two quarters from client companies that are exploring these options as deployment models.

Better management is still impetus for investment
This year, decision makers noted what they hoped to achieve with their performance management initiatives. In order, the top three responses were as follows:

• Measuring actual versus targeted performance
• Setting strategic objectives and performance targets
• Monitoring execution of key processes or initiatives

Additional Information:
Research provided by kind permission of AMR Research.

This executive overview of the Basel II initiative from a credit and operational risk perspective offers a primer on Basel II methodologies and associated technologies. It is a condensed version of a recent Aberdeen White Paper entitled Analytics and Reporting: A Basel II Requirement. For a more in-depth look at the specific technological requirements of the legislation, you can read the full paper free of charge at Analytics and Reporting: A Basel II Requirement.

Executive Summary
Although most bankers know that reducing risk can directly boost earnings, few banks other than the big money centers have developed and implemented comprehensive risk programs and platforms.

This disparity between the need for risk prudence and the apparent unwillingness among many financial institutions to pick up the pace has not gone unnoticed by the banking industry’s watchdog, the Basel Committee. This international rulemaking body for banking compliance has issued the 2001 Basel II Accord, demanding that banks either increase their capital reserves or demonstrate that they can systematically control both their credit and operational risk.

Under the accord, banks that exhibit the appropriate risk diligence get a big payoff. They can use a significant portion of the money formerly forced into reserve to fund other business. Although the accord officially begins in 2007, the Basel Committee expects banks to start proving that they already are getting a handle on risk compliance today. Failure to demonstrate an upward trend in compliance will force “risky” banks, starting in 2007, to reserve far more money than they have had to in previous years.

Proving and documenting risk acumen demand taking credit and operational risk analysis to the extreme. The risk manager’s technology arsenal — data warehousing, multidimensional analysis, data mining, and reporting –– will be more necessary than ever before and will need to be applied in novel ways. Institutions will not only have to gather, organize, and analyze new types of data linked to the risk characteristics of financial instruments and transactions but also measure and document the effectiveness of their risk mitigation strategies. Risk officers and other senior management will need metrics that enable them to assess their risk positions and observe the continuing effects of actions on that position.

Although Basel II is often confusing, the accord could not be clearer on one point: banks must build “an appropriate systems infrastructure” to identify and gather data for an enterprise-level risk database. To meet these demands, banks will need robust, risk-related analytic technology and processes (Figure 1).

Figure 1: Basel II Analytic Requirements for Risk Management
Source: Aberdeen Group, April 2003

What Capital Reserves Mean to Banks
Aberdeen conservatively estimates that banks will spend $3.2 billion in the next four years preparing for Basel II. When compared with the $400 million that banks spent in 2002 on risk management technologies, however, the $3.2 billion reflects an annual compounded growth rate of 20%. The $3.2 billion signals the significance of Basel II; it is important because it determines the amount of a bank’s capital reserves, thus directly influencing a bank’s financial and operational performance.

As a rule of thumb, the larger the reserve requirement, the less business a bank can transact. In essence, the Basel II initiative is a complex calculation, the capital ratio that is applied to a bank’s risk-related assets, including the bank’s trading portfolio, book of loans, and operational systems. This percentage is based on Basel dictates as well as on the bank’s own assessment of its performance. To derive its risk position and thereby calculate the amount of money it must place in reserve, the bank must tally the amount of risk associated with each asset.

Basel II must be examined relative to its predecessor. Much to the dissatisfaction of banks that already have the technological wherewithal to measure themselves, Basel I demanded (and still does) that banks reserve approximately 8% of each asset class. Thus, if a bank has about $1 billion in loans, it must reserve approximately $80 million, or 8% of this asset class. Basel II is much more liberal, but much more demanding. Basel II is a much more granular calculation than its predecessor, but the onus is on a bank to derive and prove its risk position.

As every banker knows, the actual amount of capital reserve pales in comparison with the detrimental, multiplier effect it has on the bank’s ability to invest and lend. In short, the capital reserve takes money out of the hands of bankers who want to do business with it. Here is why. Banks are built on a leveraged model. Basel II dictates that a bank must reserve between $0.37 and $42.00 for every $100.00 in business loans. Banks obviously want to keep to the low end of the spectrum.

Aggressive banks play with riskier activities, and the accord says that these banks have one of two options. The banks either must keep a larger capital reserve than their more conservative brethren or demonstrate a superior ability to monitor and control the elements of risk exposure.

Basel II: Incenting Risk Experience and Computational Skill
Many leading banks are ready to prove that they can demonstrate the “right stuff.” In fact, these institutions lobbied to remove the “one size fits all” dictates of Basel I. The more sophisticated financial institutions contend that their risk-based internal models protect them from running into financial trouble. According to the argument, this extra margin of safety should lower the requirements for capital reserves, in both absolute and relative terms. And the Basel II Accord has embraced the argument. To get the preferential treatment, banks must compile an auditable trail that compares what they think they will lose with their actual performance.

To remove a potential bias toward rich and powerful institutions and incent banks of all sizes to get on the risk bandwagon, the accord has fashioned a two-phased approach to risk reduction, with increased benefits at successive stages. In the first phase of risk measurement, called the Foundation Methodology, banks compute the probability of loss for each customer, translate those losses into hard dollars, and apply a multistep risk formula to that profile. With the Advanced Methodologies Approach (AMA), banks measure themselves against the same risk factors and weightings as in Phase I, but they are allowed to apply their own internal calculations. In both phases, these computations are somewhat different for credit and operations, based on their different natures, but they are essentially the same. In the credit discipline, these phases are called the Internal Ratings-Based (IRB) method; in the operational context, Phase 1 is called the Standardized Approach, and Phase II is called the Internal Measurement Approach.

In Phase II for both credit and operations, the weightings and the resulting reserve obligation can change dramatically across the entire book of business, thus rewarding the experience and computational acumen of the financial institution.

A Multidimensional Primer on Credit Risk
Credit risk applies to all banks because they make loans, guarantee the performance of another loan, or extend lines of credit to customers. Basel II requires banks to measure credit risk for the following types of credit: corporate, interbank, sovereign (i.e., government), retail, project finance, and equity.

Although the Basel II methodology can still evolve, its current IRB requirements are quite rigorous and in principle will remain the same. Once a bank elects to use the IRB approach in one portion of its loan book, it must do so for all of its loans. This universal application will challenge most banks because they typically run their lending businesses by department or branch.

As a result, banks can expect to undergo a huge cultural shift as they attempt to consolidate the lending risk. Besides changing practices that have until now been based on qualitative factors, the need for hard numbers will overwhelm many currently used technologies. Measuring the effect of many loan characteristics will overwhelm, for example, the dimensional, volume, and computational capacity of most online analytic processing (OLAP) structures. OLAP can be quite useful, but it should not be viewed as the sole tool in credit risk.

Operational Risk and Everyday Business
Basel II defines operational risk as the threat of loss because of failed internal processes, systems, people, or external events. For the most part, banks consider operational risk to be a blanket expense, a charge that is built into the cost of other business functions. Like Basel I, Basel II permits banks to set aside 20% of its gross income to protect against operational risk. By accepting this so-called Basic Indicator Approach, banks forgo the ability to further reduce their reserve requirements. However, Basel II did introduce a stepped approach (similar to credit risk) for obtaining capital relief. These phases, the Foundation and AMA, respectively, require a core competence in operational risk analysis, and additional process and technology outlays.

Basel II’s Technology Demands
The law specifically charges banks to continuously monitor their operational risk exposures using advanced techniques such as risk-related KPIs (key performance indicators), scorecards, event alerts, and predictive measures. And, leaving no room for ambiguity, the accord specifically requires banks to build “an appropriate systems infrastructure” to identify and gather data for a substantial risk database.

IT departments within banks and their technology suppliers and integrators will need to consider the following analytic risk requirements:

• Budgeting, planning, and forecasting
• Data warehousing and data mining techniques
• Enterprise risk consolidation
• Key risk (predictive) indicators
• Scorecards and KPIs
• Event alerting and related process management
• Anti-money-laundering and fraud detection platform

This shortlist of technology does not exclude other software that banks can deploy to keep to the letter and the spirit of the accord. Given the Basel evolution, banks should expect the committee to raise the technological bar as it discovers the capacity of technology in terms of power and timeliness. In short, banks should expect tighter reporting windows, shut by more demands on the infrastructure.

Aberdeen Conclusions
Basel II is a difficult and changing body of regulations. Although it is easy to get lost in the tricky rules and calculations of Basel II, the rules themselves bring other “big picture” implications for banks and their technology suppliers to contemplate. Universally, the accord’s new approach for calculating capital reserves –– and the competitive advantage a lower capital reserve brings –– will transform the way the banking industry approaches strategic, financial, and operational planning.

These considerations require immediate action. Financial institutions will need to develop Basel II understanding and incorporate it into BI and various other analytic and reporting technologies. The more tightly suppliers weave these technologies into a Basel-ready platform, the better off they will be. Bankers and suppliers should note that the Basel Committee will measure the caliber of a solution, and it clearly has shown an appetite for repeatability and extensibility in solutions.

Whether they know it or not, banks that do not take Basel II seriously are putting themselves at risk in a different way. The danger is twofold: other banks embracing Basel II will gain a better handle on their risks, a better competitive position; banks that remain unaware of Basel run the danger of a drastic increase in their capital reserves, making them less competitive. But the bottom line is this: Basel II should be a call to action for banks to develop a technology-enabled risk process. In an era of increased uncertainty and business volatility, banks that heed the Basel wake-up call and learn to control their risk stand a good chance of making a lot more money.

Additional Information:
All material copyright © 1996-2003 by Aberdeen Group, Inc. All rights reserved.

What Exactly Is Operations Research?
Basically, operations research (O.R.) is the discipline of applying advanced analytical methods to help make better decisions. It is applied mathematics that follows the “scientific method” to deliver uniquely powerful enhancements to decision making in real life human situations.

O.R. traces its roots back to World War II, long before high-speed digital computers. It originated as a way to bring scientific calculations to Allied Warfare against Nazi Germany. Executive departments were given a quantitative basis for making decisions that resulted in winning the Battle of Britain. What began with the studying of radar signals in 1936 has yet to reach its full potential. Since the 1990s, however, when numerical processing became faster and more widely available, O.R. has joined forces with digital high speed computer technology, mathematics and industrial engineers to pursue new ways to apply mathematics with far reaching impacts.

With O.R., decision makers need no longer rely solely on intuition. Today, O.R. gives executives the power to make effective decisions and build productive systems based on:

• Rigorous mathematical models
• Consideration of all available options
• Careful predictions of outcomes and estimates of risk
• State-of-the-art decision tools combined with time-tested algorithms.

Articles and ads about software solutions that claim to enhance decision-making capabilities are commonplace. O.R. is not a buzz word for a “fad” with a claim to fame, so you won’t find O.R. listed under the “what’s hot in technology” section. Operations Research is best of breed, employing highly developed methods practiced by specially trained professionals. It’s powerful, using advanced tools and technologies to provide analytical power that no ordinary software or spreadsheet can deliver out of the box. And it can be tailored to you, because an O.R. professional can define your specific challenge in ways that make the most of your data and uncover your most beneficial options.

To achieve these results, O.R. professionals draw upon the latest analytical technologies, including simulation, optimization, visualization, queuing theory, scheduling, game theory, probability and statistics.

What Operations Research Can Do For Your Enterprise
O.R. delivers significant value to the organizations and executives who take advantage of it. As organizations continue to become more sophisticated and collect more electronic records, the task of analyzing data becomes much more daunting. Fortunately, business intelligence software, data warehouses and O.R. have all matured to the point of giving companies that employ them more precise information – and insight - than they’ve ever had before. With these software resources at their fingertips, O.R. professionals confront and overcome challenges that involve large numbers of variables, complex systems and significant risks.

In fact, the essence of O.R. is to deliver accurate knowledge in a timely fashion to make confident, calculated decisions with less risk than ever before.

Today’s software technologies for optimization and management science methods are used to profitably tackle a wide range of business issues, including:

• Resource allocation
• Retail and inventory planning
• Product mix and blending
• Staffing allocations
• Distribution, routing, scheduling and traffic flow
• Supply chain management and logistics
• Capital budgeting, asset allocation and portfolio selection.

Organizations that use O.R. have found it to be a strategic weapon in the fight for competitive advantage. According to the www.scienceofbetter.org website, here are a few examples:

• Continental Airlines applied O.R. to revise crew schedules during the Sept 11 terrorist crisis. Savings were estimated at $40 million in 2001 alone.
• AT&T applied O.R. to plan emergency rerouting of voice, data, wireless and satellite communication systems. Efficient allocation of resources won customer loyalty, upped revenue and saved hundreds of millions of dollars.
• Samsung applied O.R. to reduce manufacturing times to capture an additional $1 billion in sales of semiconductor devices.
• UPS applied O.R. to redesign its overnight delivery network, saving $87 million and projecting an additional $189 million savings over the following decade.
• NBC applied O.R. to improve advertising sales plans, increasing revenues by more than $200 million.
• Ford applied O.R. to optimize the way it designs and tests vehicle prototypes, saving $250 million. 

Five Sure Signs That You Could Benefit From Operations Research
According to the Institute for Operations Research and the Management Sciences (INFORMS®), if one or more of the following applies to your organization, O.R. can deliver what you need to confidently make better decisions:

1. You face complex decisions. Perhaps you’re faced with more decision factors than you can manually handle. Do you have competing goals or difficulty weighing the pros and cons involved with multi-criteria? O.R. professionals can analyze complex situations and build intelligence into software systems, to uncover insight and highlight the best options. Before you act, consult with an O.R. professional to see how taking an O.R. approach will pay dividends.
2. You're having problems with processes. One or more of your processes is limping along and you aren’t sure what exactly to change. Many small, day-to-day decisions are simply repeats of what’s typically worked well in the past and you’d like to incorporate imaginative creative forward-looking improvements. O.R. can simulate and test proposed changes to your processes before costly revisions in your day-to-day operating environment are implemented. With O.R. you’ll ensure that any changes you implement will be positive.
3. Your organization is not making the most of its data. Do you track information about your organization and have data that is begging to be used for decision making? O.R. specializes in working with this unused or under-used data – extracting the most valuable information from what's currently collected, and showing what additional data you could collect to increase the value even further. O.R. professionals can show you how to make fact-based decisions by incorporating historical trends with current driving indicators to allow you to seize the initiative and become the leader in the marketplace.
4. You need to beat the competition. Others in your field may already be using O.R. to gain competitive advantage. An O.R. professional can help you get ahead and stay ahead – because O.R provides a big picture view of the world and can pinpoint critical interconnections to suggest innovative new sources you ought to explore to retain (or develop) a position of sustainable superiority.
5. You're troubled by risk. Do you want to limit or reduce risk? Assessing the risk of a new project or contract is often tricky. O.R. helps you quantify risk, which is critical to controlling it. O.R. assists in planning how best to balance risk against the gains you expect. With so much on the line, wise executives are seeing the value of leveraging the best technologies possible – with O.R. as a central ingredient in their recipe for success.

Conclusion
Strategic decision making is crucial to the success of business initiatives and entire organizations. It’s important to ask the right questions, think out of the box, sort through the myriad of factors and consider all potential options, before you move forward to select your course of action in order to achieve maximum results.

Operations Research is a proven management solution in the analytics field today and it will continue to grow exponentially from its World War II roots. No matter what stage of growth an organization falls into, O.R. techniques can help make dramatic improvements, decision by decision. The sooner O.R. is implemented into a company’s decision-making process, the more far-reaching the benefits will be.

Additional Information:
 

Today's giant corporation is much like the CIA in its ability to gather and generate terabytes of information and intelligence. It can produce unlimited reports, metrics, benchmarks, and segmentation of every customer, operation, process, and transaction. But what does it all mean? That's where good analytics—based on both technology and human interaction—come into play; analytics make the difference between information overload and real business value. What follows are best practices of four businesses in very different industries that each found the right mix of tools, processes, and management to maximize the value of their data.

Nowhere is the value of business intelligence (BI) and enterprise data management more evident than in the gaming, entertainment, and hospitality industries. When a loyal casino customer hits the jackpot at a slot machine in Reno, Nev., or Atlantic City, N.J., what's important is not how many terabytes of data are stored in our data warehouse or the kinds of reports some analyst can run after the fact. Rather, it's how the information is leveraged in real time to serve the customer immediately on the casino floor. If the customer is celebrating a birthday, for example, that data will let employees know instantly so they can surprise the guest with a special greeting or gift in the casino or hotel room.

To take another example, consider a Total Rewards Diamond card customer who's a regular at one of our Midwest riverboat casinos. BI lets us know what gaming experience that customer most enjoys, as well as personal preferences as to room accommodations, restaurants, and entertainment amenities, so we can determine what incentives will best persuade the customer to visit our Rio or Flamingo hotel casinos in Las Vegas.

These are just some of the personalized services that Harrah's Entertainment can increasingly provide guests as a result of our focus on customer-facing, analytical, and operational BI efforts. No matter how broadly our casino entertainment locations continue to grow, or how complex our business and IT operations get behind the scenes, we recognize that we're in a discretionary consumer-service industry where customer loyalty and satisfaction, at the individual interaction level, make or break our business every day. That's why we've been investing in innovative CRM approaches and BI processes and technologies, as well as refining our core Total Rewards loyalty program. We're also integrating myriad other customer-facing and back-office systems and capabilities to give us a 360-degree view of our business.

Our goal is to create individual relationships and differentiated service among the nearly 40 million customers in our database who choose us for casino entertainment.

Setting us apart from competitors is the fact that all these customers—including our recently acquired base of Horseshoe Gaming and Caesars Entertainment guests—will enjoy the benefits of Total Rewards and our data-driven CRM and BI approaches. Our expanded customer base lets us offer an even broader set of locations, brands, and amenities in the United States—and, increasingly, abroad. In fact, international development is an exciting new growth area for us. We now operate in Canada and South America, and recently announced planned projects in Europe, the Caribbean, and Asia. These will leverage and enhance our existing capabilities and also let us create new value and insights. (For more on the integration of Caesars, see below.)

As with any successful enterprise BI approach, many sources of business data can be leveraged at the local or enterprise level for analytical insights. At Harrah's, these include financial, operational, transactional, marketing, product, labor, and customer-satisfaction data. Business and technical processes are used to acquire, archive, and organize that data into a data warehouse so that standardized and ad hoc reporting and analysis tools can ensure the efficient communication of the insights gleaned from the data in the right format, at the right time, and to the right people.

We've partnered with Cognos, IBM, SAS, Teradata, Tibco, and others to create a highly integrated and customized solution to meet our needs. And while BI technology and techniques are critical to the execution of our strategy, another key is our strategic customer focus and a culture of analytical inquisitiveness and data-driven decision-making throughout the company.

Loyal to the Core
Usually, one core element at a BI-focused company really drives the technology's use and adoption. At Harrahs, it's perhaps no surprise that the core of our CRM and BI efforts remains our Total Rewards loyalty program, together with the data and operational insights it provides. By refining our closed-loop insights and efforts around this core, we've established a scalable, extensible, and differentiated loyalty and service framework within our company to continuously improve customer interactions and business outcomes. Through these core efforts—and the leverage of our enterprisewide BI tools, processes, and metrics—comes growth in terms of customers, locations, and revenue, as well as valued relationships and greater loyalty with new and existing customers.

As a result, we've seen our share of customers' discretionary gaming entertainment spent with Harrah's versus competitors jump from just over 30% a few years ago to nearly 50% today. This is a solid indication of brand loyalty, relationship marketing, and closed-loop BI in action.

BI at Harrah's permeates the organization and is firmly embedded in our culture. For example, there's a dedicated BI analytics group that reports to the CFO and is supported by the IT team to provide daily automated and ad hoc reporting, both online and in printed "white books." The content of these reports can be parsed many ways depending on who has access, be it the CEO, the CFO, or one of our three regional operating-division presidents or corporate functional areas. Some may want general top-line trends, while others may wish to drill down to find out which games did well at which locations, how bad weather affected business, and so on. The white books usually include key performance metrics, revenue analysis, and the amount of game play and hold at every location, as well as food-and-beverage sales, Total Rewards metrics, retail statistics, and other data. We can then identify hot spots, or attention areas, and quickly engage resources to dig deeper and implement marketing, staffing, or operational changes as needed.

Likewise, our marketing, gaming, hotel, retail, and customer-service and satisfaction departments—among others—have access to a rich amount of predefined reports and ad hoc data on slot and table play, player behavior, hotel occupancy, marketing and promotional campaigns, restaurants, events, and retail sales. With this, they can design, test, and roll out campaigns, promotions, game changes, and service and staffing changes targeted to specific customers during specific times at specific locations. This personalized marketing, using a variety of delivery channels such as VIP Hosts, E-mail and direct mail, lets us create the right incentives for each customer and improve everyone's overall experience at Harrah's. In turn, we can use these insights to create future campaigns that give us the highest ROI and ensure our marketing dollars actively contribute to the bottom line.

We aim to transform our decision-making approach from "I think" to "I know." Virtually every customer-facing initiative—whether it's a direct-mail campaign or a new promotion or slot theme—is tested in a controlled environment using a test campaign and a control segment. With our BI systems and processes, we can then monitor the behavior of the test group and measure the relative effectiveness of the initiative, rolling out only those we think will be most successful. With this philosophy, we've evolved from simply analyzing historical data to predicting the future performance of many marketing campaigns—a critical lever in maintaining competitive advantage and effective margins in our markets.

Our corporate structure, from a people and system perspective, also bolsters our BI efforts and sets us apart. Unlike most of our competitors, Harrah's is organized with a federated mind-set of how corporate and properties work together and share accountability—similar to the way a world-class retailer or financial-services company operates.

In general, key business strategies and automated systems are developed collaboratively but deployed centrally. Daily usage of tools and capabilities is executed locally by the properties by means of best practices and templates across the company. While we appreciate the market insights and agility of each of our local properties, we've created centralized functions and processes so that customers see a coordinated experience no matter where they stay or play.

This federated approach also can be seen in our infrastructure and how data is collected. We've shifted almost all our systems to two redundant, centralized data centers. Only a few front-of-house systems, such as slot systems and point-of-sale devices, are located at the properties themselves. And all properties feed data into our central data warehouse.

In all we do, privacy and security are a big priority. The vast majority of the data we collect is provided voluntarily by our customers and based on their activities using our customer card. This voluntary approach to capturing player activity has proved to be a win-win model for our customers and Harrah's: We've grown Total Rewards card usage from approximately 50% of tracked revenue in our casinos to nearly 80%. And with our integrated systems and enterprise view of customers' preferences and transactions, we can accurately recognize and reward them through a variety of channels and touchpoints across any Harrah's, Caesars, or Horseshoe property.

This approach allows Harrah's and our customers to mutually build upon and benefit from the relationship, and ensures that we can best provide differentiated service to our Total Rewards customers, as well as gauge their satisfaction with our performance.

Over time, we've evolved our BI systems and processes to take advantage of new technologies and best practices from other industries like retail. An example is a unique spatial and data-visualization tool we co-developed with a New Zealand company named Compudigm. With it, we not only have a dynamic "heat map" view that displays the layout of the casino floor down to the individual slot machine, but also can visualize and drill down on the transactional data flowing through the games over any period of time. It addresses another key challenge data warehousing can pose: allowing us to sort through extensive amounts of transactional data in a non-numeric way.

Going into the new year, we'll continue our spirit and approach as we create new capabilities to enhance and differentiate the customer's overall experience. We'd like to be even more service-oriented and to provide more offers, amenities, and individualized experiences for our best customers. Our vision is to react in near-real time to serve customers while they're at our casinos, whether through employee interaction, an automated business process, or a self-service transaction.

Betting on Better Services
We're migrating from a purely analytical CRM approach—looking only backward at past performance—to a more operational CRM approach that uses both historical and current information. We'll also use a business-rules engine and defined business processes to trigger actions we can do now to help create a differentiated and personalized experience for customers "in the moment."

The technologies and initiatives we're pursuing to reach our goals are well under way. One pilot project, called Moonshot, uses sophisticated SOA-based application integration and business-rules engines as well as real-time messaging between customer-facing touchpoints to integrate front-of-house transactional systems with customer data available in real time from our Active Data Warehousing platform.

With these new capabilities, we can pilot and evaluate a number of new ideas and initiatives that range from proactive and personalized service on the gaming floor, to innovative promotions and product introductions. We've only begun to scratch the surface, but these innovations wouldn't be possible without our solid foundation of core analytical CRM systems and BI tools.

From a BI vantage point, the odds seem to indicate that the House has indeed created some compelling competitive advantages. Looking ahead, one sure bet is that we'll continue to leverage our new and existing capabilities to achieve our business-growth strategies in the United States and abroad.

Sidebar: Caesars Joins The Game
The acquisition of Caesars was our sixth in as many years, but at $6.8 billion and with more than a dozen properties and locations, it's by far the biggest deal we've done. It will also be the fastest and most complex IT integration effort we've ever taken on. The deal was finalized the afternoon of June 13, 2005, but when folks came in the next morning, we already had the network infrastructure and electronic communications systems up and integrated, and employees from both companies were working together. Even I was a bit amazed that when I first fired up my laptop that morning and connected through the Caesars LAN, I could get to everything I needed.

We've since completed the rest of the multimillion-dollar infrastructure build-out of our redundant network and back-of-house operational middleware, as well as data-warehousing platforms in our two enterprise data centers. We closed out 2005 by completing the entire integration, conversion, and centralization of all Caesars back-office systems and functions. Everything has been running well, despite essentially doubling the number of employees to nearly 100,000 and handling significantly more daily, monthly, and year-end financial and procurement transactions than we could have imagined.

In the third and fourth quarters, we also deployed new capabilities for cross-property customer hotel booking and in December, we successfully completed our first full front-of-house conversion of the Flamingo in Las Vegas including integrating the slots, tables, casino, hotel, events, and point of sale. This let us offer all of our Total Rewards capabilities in record time and with encouraging results. Through March, we'll convert front-of-house systems for the rest of the Caesars properties in Nevada, Mississippi, Indiana, and New Jersey, and then we can relaunch and market Total Rewards across more than 40 U.S. properties. Then we'll start the process internationally, first in Canada, then likely in South America. Those will be good tests as we begin adapting our systems in the Bahamas, Spain, and Slovenia, and for planned expansion in Asia.

Financially, fully two-thirds of the value expected from this merger is revenue upside, with only about a third in cost savings. That's why there's a lot of focus on getting Total Rewards into the Caesars properties. For the third quarter of 2005, the first one reflecting the Caesars acquisition, the company reported record revenue of $2.3 billion, up 78.2% from the previous year.

Tim Stanley

Sidebar: 12,000 Opportunities At Dunkin'
Launching successful business-intelligence initiatives isn't about doing things you couldn't accomplish before. Rather, it means collecting data and making decisions in a more efficient and effective manner. And when you have 12,000 worldwide retail outlets—including Dunkin' Donuts, Baskin-Robbins, and Togo's restaurants—collecting that data and executing a comprehensive BI strategy is a big job.

We at Dunkin' Brands previously lacked the tools to efficiently gather the information necessary to better understand our products, franchisees, and customers. To gain insight into the business, our knowledge workers would have to spend as much as 80% of their time piecing together data from disparate systems.

Three years ago, we launched a BI strategy primarily to analyze what was going on in the market for our brands. We were particularly interested in analyzing marketing and promotional efforts and developing applications that would support our strategic vision. To achieve our goals, it was critical to develop an integrated, single source of the truth and then leverage that information to measure the success of our business investments.

But as a 100%-franchised organization, we faced unique challenges. We needed to implement technologies and applications that could gather information in the most efficient way possible, then quickly turn that information into products and services to drive the success of our franchisees. By making accurate, timelier decisions about the products and services we delivered to our franchisees and customers, we could boost revenue and profitability across the system.

To start, we had to create a data warehouse to integrate this information. Doing this required us to ask: What type of data would we need to gather? How available would that data be? And what would be the most efficient way to store and analyze it?

At first, we took an iterative approach, with input from both technology and business partners. The process included gathering the available data and identifying gaps in that data, such as missing elements or incorrectly coded item numbers. This is another unique feature of a franchise-business model: The franchisee owns the source of the data and can inadvertently introduce anomalies. But we resolved many of these gaps and completed the analysis that would give us the business insights we sought.

We have an Oracle back-end database and Oracle Discover on the front end to create reports and analysis. Each night, we collect a feed of point-of-sale (POS) data from a representative sample of our restaurants. This data is aggregated in the data warehouse, along with other pertinent data points such as retail information, profitability metrics, and external information from third parties.

A good example of such an analysis involves the introduction of our line of espresso beverages. Using tools from product inception through national rollout, we could immediately gather and evaluate POS information from participating restaurants. In short order, we could compare test markets with control markets to see the effect of our promotional campaigns and measure outcomes, even unintended ones.

These tools have greatly enhanced the analytical capabilities of our knowledge workers and we require every user to be certified. Currently, we have 260 users who are fully trained across the business: including finance, marketing, operations, and new-product development. It's important for these power users to have full control and a deep understanding of the data and analysis tools. Our main goal is to support them.

The biggest challenge so far has been the volume of data. In 2004, the company had $4.8 billion in annual sales, and since each transaction is relatively small, the volume of data is enormous. But this is also one of the benefits; previously, it was a labor-intensive effort to provide a clear view of enterprisewide sales. In the past year, we've seen the data-collection process accelerate and adoption within the organization grow more widely.

To determine the ROI of this ongoing initiative, we've used time and efficiencies as a measure of success. Reducing the time it takes to gather information from weeks to hours is a real money-saver. And taking action on that information has clearly let the organization make better business decisions.

Assessing business opportunities—such as identifying new markets in which to launch stores—is critical to our company's continued success. Our BI platform will scale as we gather data that accurately reflects the expanding universe of Dunkin' Brands. Armed with this information, our BI users will effectively measure business results and thereby help the company achieve its strategic goals.

Rick Broughton is acting CIO of Dunkin' Brands.

Sidebar: BI Wins At McKesson
About three years ago, McKesson Pharmaceutical, a $71 billion business unit of San Francisco-based McKesson Corp., began an extensive business-intelligence implementation. Executive management had identified opportunities where BI could provide gains in productivity, close off profit leaks, and improve business processes. They asked that the team focus on these areas by developing specific, process-based analytic solutions.

To start, the strategy needed to capture the new data from our ERP implementation. My team faced the challenge of getting the ERP team on the same page. It was critical for them to jointly deliver the enterprise-data-warehouse layer—a more robust architecture connecting financial information with new sales, logistics, and inventory information. We brought all of this information into an SAP Business Intelligence solution with the goal of deriving significant benefits to the company's bottom line.

Within nine months, we developed the data warehouse layer that captures the bulk of existing SAP and legacy information, as well as new sales, logistics, and inventory data. This wasn't an insignificant achievement. From a volume perspective, we extract upward of 15 million records nightly and load 35 million records per night into the SAP platform. Currently, we're methodically building out process-based analytics that utilize this data.

For this effort, we've built more than 30 process-based analytic solutions to focus on several critical areas: finance/profitability; sales and marketing; procurement; customer and supplier contract management; and distribution-center operations.

For example, we're in process of more closely analyzing the accuracy of customer and supplier contracts and how they compare with the actual information we now retain in the BI system. These analytics are increasing the effectiveness and efficiency of contract compliance with both customers and suppliers. In operational analytics, we need a very clear inventory analysis of our more than 30 distribution centers. The BI platform developed process-based analytics for inventory dating, inventory adjustment, and quality metrics, which allows us to determine how accurately we deliver the right product to the right customer.

Keeping Score
In addition, we're starting to deliver the first iteration of scorecards and dashboards. This effort is in the initial stages, but we hope to eventually provide corporate performance-management alerts that isolate critical key metrics for all business processes.

In the three years since implementing the BI platform, the number of named users with access to the system has grown to 1,500, including about 300 who use it daily. Although user acceptance and adoption continues to climb, achieving growth hasn't been easy. In many instances, BI isn't mandatory, and we see varying levels of participation. Additionally, many users are accustomed to the old way of reporting and analyzing from the legacy-data warehouse. We're trying to extend SAP BI much farther into the organization, and we're slowly transitioning people away from other existing data sources.

To help drive user acceptance and adoption, we spend a good deal of time on training and support. Initially, we allowed many of the BI users to build their own queries, but we discovered that this freedom sometimes complicates the ways users gather and analyze data. To improve ease of use, we've optimized the performance of our BI solutions and simplified the query-development and execution processes. For example, as part of the sales-process-based analytic solutions, we reduced the number of queries from approximately 700 to 45, and we improved query performance in certain instances by more than 300%, on average.

Moving forward, our next major BI initiative will address the need for more operational, or just-in-time, analytics. As with most BI implementations, analytics or reports are provided next-day. Our goal is to move data more quickly across the environment, providing even greater benefits for the business.

Indeed, we've made significant strides with our BI effort. The executive committee—initially consisting of the McKesson Pharmaceutical CIO, CFO, the SVP of marketing, and the SVP of business-process reengineering—set the direction. The committee has evolved based on business requirements; the BI team continues to deliver accordingly. Of course, it's not possible to satisfy every business-user request. We remain focused on our goals: providing process-based analytic solutions for the business to increase productivity, close profit leaks, and improve processes.

It's this business-intelligence focus that has enabled McKesson Pharmaceutical to deliver significant benefits to the company's bottom line.

Brian Hickie is VP of business intelligence with McKesson Pharmaceutical.

Sidebar: Outward-Facing BI
Like many of our corporate counterparts, we at PHH Arval are using business-intelligence and dashboard technology to differentiate ourselves in the market. But unlike our competitors, we've launched our initial foray into the BI arena as a customer-service initiative, rather than as an internal analytics application.

As the second-largest provider of outsourced commercial fleet-management services, we manage company car programs for nearly a third of the Fortune 500 companies as well as for hundreds of government agencies. We estimate that our PHH InterActive Dashboard application—introduced in the summer of 2005—will save our clients as much as three work days each month in downloading and analyzing fleet data.

As a strategic partner, PHH handles all the processes involved in managing a fleet of business vehicles. We design and tailor ways for company-car drivers to order the vehicles they need, then deliver the vehicle to the driver. We provide a variety of lease options to the company, and issue drivers charge or credit cards to use at the fuel pump. We ensure that appropriate maintenance gets done, and when bad luck happens, we manage the accident-response process. We take care of properly registering and reregistering the vehicles; and because the cars are titled to PHH, once the lease expires, we can sell the cars on behalf of the client. Every one of these processes generates a tremendous amount of information that can help our clients manage their fleets more efficiently.

PHH InterActive Dashboard allows clients to access and analyze fleet trends by providing three years of summary information on key performance indicators and fleet expenses. It gives them access to fleet billing, inventory, and fuel-purchase information, as well as information about vehicle orders and used-vehicle sales options. Clients can monitor their fleet expenses, which are summarized and presented in a format that can be incorporated into their budget-analysis process. For example, trend-analysis reports show the average price per gallon consumed by the fleet over a period of as long as 24 months.

We introduced PHH InterActive in 1998 as a comprehensive enterprise information and asset-management tool. At the same time, we developed an extensive data warehouse, which integrates information from several systems to provide the level of reporting clients needed. While pleased to have the information, they were often overwhelmed by its sheer volume. This was the catalyst for the Dashboard—a collaborative effort with clients. As CIO, I attended many client meetings and worked with our Client Technology Advisory Board. Once we identified their requirements, I worked with the developers to build the prototype. We went through several stages of prototyping.

In terms of vendor selection, we were already using the Brio enterprise reporting toolset, but hadn't upgraded to Hyperion's Performance Suite after Hyperion's acquisition of Brio. Once we determined we wanted to upgrade, we brought in the leading BI vendors and narrowed the field to a short list of providers. In the end, we went with Hyperion. For us, in addition to providing a comprehensive enterprise toolset, it was the path of least resistance—we wouldn't have to redo all our existing reporting, and we would continue to have an integrated solution.

We took an incremental approach. We didn't try to solve all our problems with the first release. We released the beta at the end of August and the second version in December. With each iteration of the Dashboard, we've received valuable feedback from customers. Such input helps us deliver critical requirements incrementally and steadily.

The second release focused on used-vehicle information. Customers are interested in understanding how well those vehicles perform when they come out of service to determine resale value. In our third release—slated for this month—we'll show summary stats about maintenance and accidents, and correlate them with resale value.

Eventually, we're looking to use the tool internally. But the big bang for the buck that has justified the implementation is how the Dashboard has separated us from the pack in our market.

Tim Talbot is senior VP and CIO at PHH Arval.

Sidebar: Travelocity's Mamie Jones on BI
Mamie Jones, senior VP of strategic sourcing at Travelocity, Sabre's online travel-reservations site, spoke recently with Optimize senior managing editor Paula Klein about Travelocity's BI efforts.

Q: Sabre has projected a dramatic 40% rise in revenue this year for Travelocity. Will BI play a role in achieving that growth?

A: IT plays a very big role in our business since we're a technology-centric company. We also know that as we increase the personalization of our marketing and target campaigns to be more relevant to customers, booking rates can exceed as much as eight or 12 times the standard methods [of outreach]. Our data warehouse plays a key role in assuring that our merchandising efforts pay off.

Q: What are your specific BI strategies?

A: We're moving from an enterprise data warehouse to an active data warehouse which should give us more real-time data, not just historical data. It will help us make better, more accurate, and automated business decisions and offer more timely updates to consumers. We want to use data to improve our products and learn more about which promotions, experiences, and services customers find valuable. Our merchandising objective is to increase customer value and offer a richer online experience. We also want to increase suppliers' value through all of our channels. This vision is evolutionary; it's not one project, but an ongoing effort.

Q: How far along is the data warehouse?

A: We've done some benchmarking and we're in the process of planning the architecture, the design, and the capacity. We're building this internally based on our current Teradata platform. We think we're out in front on this. Having current data will help us retain customers by building loyalty and satisfaction. It also leads to better predictive modeling.

Additional Information:
Tim Stanley is senior VP and CIO of Harrah's Entertainment.

The Challenges of Customer Data Integration
By Robert Lerner
Current Analysis
 

One of the major challenges facing companies today is developing a single, consistent, and complete view of their customers across all applications, databases, and customer touch points.  The challenge is significant, because developing such a complete view of customers is not an easy task, but it is crucial to a company's success and to its ability to comply with any number of state, federal, and international government regulations.

Certainly, most companies have an intuitive grasp of the significance of obtaining such a view of their customers. But many companies fail to understand its overall importance and far too many underestimate the difficulty of getting this view. 
 
Indeed, it is surprising that not every company appreciates the importance of a single, consistent, and complete view of the customer.  (In fact, among the companies that do understand the importance, not every one of them recognizes that they lack such a view today.)  Without a single, consistent, and complete view of its customers, a company cannot begin to understand its customers - and it cannot begin to serve its customers well.

Consider, for example, a company that has duplicate customer records.  In all likelihood, some customer interactions with the company will be associated with some records and not with others.  The duplicate records complicate the effort to track customer actions such as customer buying habits as well as customer interactions with various customer touch points (e.g., the Web, call center, etc.).  The company will also have difficulty determining the total value of the customer.  As a result, the company's ability to serve and support the customer may be limited. 

In fact, the company's ability to retain the customer could be jeopardized.  Customers are easily put off by customer support representatives who do not have a complete history of their interactions with the company.   Moreover, many customers have ceased to do business with a company after having been bombarded with marketing messages that the company intended to communicate to different individuals but were, in fact, directed to the same individual because of duplicate customer records. 

But companies also incur potentially significant costs because of duplicated customer records and other customer data problems.  While the costs of retaining a single customer can be significant, these costs can skyrocket if the company has to retain the same customer more than once because of duplicate customer records. 

However, problems like these are only the tip of the iceberg for companies without a single, consistent, and complete view of their customers.  Without such a view, expensive applications such as CRM, ERP, and the like will not only fail to live up to expectations but will require much more of an investment than the company anticipated.  CRM applications, for example, can be a boon to companies, but only if the customer data fed into them is consistent, accurate and reliable.  Inconsistent customer data (data containing multiple customer records for the same customer, etc.) can lead CRM applications to present the company with an erroneous idea of who the company's customers are and their overall value to the company. 

If the goal of a CRM application is to help companies maximize the customer experience at each stage of interaction - and to facilitate deep, long-term, and profitable relationships with their customers - then feeding the application incomplete, inconsistent and duplicate customer data can defeat this goal and increase the costs of maintaining both the customer and the application.  Now consider a company's problem if it relies on the same customer data used in its CRM application for a variety of applications (such as front and back office applications, data warehouses, etc.).  In this case, the problem is magnified and the costs associated with the problem grow exponentially. 

And in an era of increasingly strict compliance standards, a single, consistent, and complete view of the customer is critical to keeping a company in line with regulatory or industry standards.  Indeed, the degree to which a company has a comprehensive view of its customers can determine the degree to which it can comply with state and federal government and international regulations. 

In recent years, and especially since 9/11, governments have enacted regulations that essentially require a company to know who its customers are.  Regulations such as OFAC, the USA Patriot Act, HIPAA, Graham-Leach-Bliley, state and federal Do Not Call legislation, and so forth depend, at their core, on a company's ability to know its customers. This requires a single, consistent, and complete view of the customers. 

HIPAA (Healthcare Insurance Portability Accountability Act), for example, requires hospitals, physicians, and managed care companies to adopt patient information, privacy, and security standards.  It also allows patients to access medical records, make corrections to the information contained within them, and monitor how this information is used or disseminated.  But unless healthcare institutions have high-quality, complete patient records, they cannot begin to protect the privacy of a patient's medical information or provide the patient complete access to his or her records. A lack of data-related safeguards could open hospitals, physicians, and so forth to a variety of liabilities. 

Graham-Leach-Bliley, on the other hand, is designed to regulate the sharing of information about customers who purchase financial products or services from financial institutions.  As with HIPAA, the absence of a single, reliable view of the customer hinders a company as it begins to control how it shares customer information - and it opens itself up to fines and worse. 

The risks associated with an inaccurate, limited view of the customer should be apparent.  The question now is how to get a single, consistent and complete view.  To date, companies have used a variety of methods that have offered them only limited success.  A typical IT environment complicates the issue, as it is difficult to standardize on a single vendor's applications and have multiple customer data sources and multiple customer touch points.  Indeed, how does a company go about integrating all this customer information, information which is often incompatible (due to standards, application incompatibility, format, etc.), into a consistent, complete view of its customers and create a single view that can be shared by all of the applications and touch points. 

It seems an impossible task, but it can be done effectively with the right kind of technology. Emerging technologies, such as Customer Data Integration (CDI) solutions, that emphasize data quality are the best way to approach the single view of the customer.  The next article will explore some of the ways that companies have handled customer data and recommend an effective CDI solution. 

Click here to view the Customer Data Integration Info Pack.

Additional Information:
 

Enhancing Value Through Data Mining
 

Enhancing Value Through Data Mining
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