Timeliness of Business Intelligence Data

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1 Timeliness of Business Intelligence Data Walter Cunningham Paul McNamara BenchMark Consulting International Introduction The previous article in this series of business intelligence papers discussed the importance of business intelligence in the formulation, implementation, and maintenance of corporate strategy. The understanding that business intelligence can provide regarding relative competitive performance is vital in defining how an organization will differentiate itself from its competitors. A recent discussion of business intelligence identified three key questions that must be answered to establish an effective program for gathering business intelligence data: 1. What to measure? 2. What does the information mean? 3. How timely is the information? (Go to Click on the December 2006 hyperlink on the homepage to hear the podcast) What to measure is dependent upon several factors such as the industries and markets an organization competes in, the strategy the company chooses to serve those markets and the regulatory and competitive requirements in the company s industry. What the information means is perhaps even more specific to each company and depends largely on how it chooses to position itself in the market relative to its competitors, as well as, trends in relative performance compared to the company s closest competitors. Regarding the question of timeliness of data, the answer is somewhat more straightforward - the fresher the data, the better! Nowhere is this truer than in the financial services industry and it is especially true in the credit business. There is no process more critical to success in the lending industry than the effective management of credit risk. Because of this, financial institutions have built tremendous infrastructure to manage credit risk by evaluating historical repayment and utilization of credit facilities thus allowing them to analyze trends and performance over time to project future delinquencies and credit losses. As a result, banks and other lending institutions have greatly invested in data storage and mining capabilities to constantly monitor trends in their loan portfolios. These investments allow financial institutions to quickly identify changes in credit risk, hence fostering more proactive management of origination, pricing, collection, and recovery policies. Of course, improvements in the timeliness of data come at a price. Historically, technology and process limitations tended to preclude the possibility of delivering real-time data. However, with the explosion of personal computers and network technology in the business world and at home, barriers to real-time availability of data continue to fall. As a result, real-time access to business intelligence information - once a practical impossibility - has now become a reality. Companies that recognize the value of fresh data and are willing to make judicious investments can gain a real, competitive edge in the market. Technological Transformation Availability of data in a digital format is a key enabler of the evolution of business intelligence. Consider the evolution of the financial services industry. It seems hard to believe that only a few decades ago, banking processes relied almost exclusively on the movement of paper. Checks, 2007 BenchMark Consulting International, N.A., Inc. All Rights Reserved.

2 currency, deposit slips, and ledger tickets made the banking world go round. Financial institutions became early adopters of computer technology, seeking to reduce the expenses associated with managing all of that paper. However, the earliest technological innovations in the financial world really focused on summarizing all the bits of paper for purposes of reporting and settlement. Information was transferred from the paper to punch cards then loaded to the mainframe in batches. Since the paper documents had to move by mail or courier, a transaction could take days (or sometimes weeks) to flow through the entire lifecycle. While the new technology was a revolutionary step forward, reports and information provided were not time-sensitive. However, as technology has evolved over the past several decades, and particularly in the past 2 decades, a process that used to take days or weeks can now be completed overnight, if not same-day. The advent of the personal computer and its availability to bank employees, customers, and suppliers has transformed the financial services industry. Similarly, easy access to data networks has facilitated the movement away from paper transactions to electronic processing at every step of the lifecycle. Customers, merchants, tellers, clerical staff, and back room operators can now capture and share data electronically. As a result, if a transaction is initiated on paper, the associated data can be converted from paper media to digital data as soon as it is received by the bank. Furthermore, as the old legacy, core banking systems are being replaced, the batch approach to processing has been supplanted with new technology that enables immediate, real-time processing of transactions regardless of where, when, our how data is received. Technology is no longer an afterthought, but a key component of every process in banking. As a result, the key data required to generate meaningful business intelligence can be spun off and captured in real time. As technology continues to become embedded in the banking process, the previous barriers to immediate capture data needed for business intelligence purposes continue to melt away. The Challenges of Capturing Competitive Business Intelligence Data As more processes moved from paper to computer, data warehouses became standard fare in every organization of any size. Production systems feed critical (and some not-so-critical) data to separate, MIS databases where analysts, managers, and any one else with interest and access can query and massage that data however they see fit. These data warehouses facilitate internal analysis of company performance. They can be used to study trends over time as well as to compare and benchmark teams, departments, or individuals within the company against each other. However, as discussed in the last article in this series, to unleash the strategic value of the data, organizations generally recognize the need to compare key pieces of performance data to competitors in their industry. This desire to compare performance data between competitors presents a whole new set of challenges. First, while every one wants information on how their competitors perform, most are unwilling to share the same information with others. There are a number of reasons for this. Foremost among them is the reluctance to give away proprietary information to competitors. Also, as mentioned in Cheryl Yaeger s previous article on the value of benchmarking 1, many firms hesitate to share detailed performance information for fear that the company s results will not compare favorably with its competitors. Of course, it is impractical to expect that a company will lead its industry on every performance metric. In fact, as mentioned in the preceding article in this series, one of the most important steps in defining a strategy is making specific choices regarding where average performance is acceptable. Unfortunately, the fact that a company has strategically chosen to accept relatively lower performance on a given measure will not stop competitors from pointing out their superior performance in those areas. An additional concern is the ability to define a common set of metrics that can be calculated and 1 Yaeger, Cheryl. The Value of Benchmarking. April BenchMark Consulting International 2 Timeliness of Business Intelligence Data June 2007

3 captured in a consistent manner across a given industry. Every company has a unique history and defines its own approach to the business. Firms choose what to emphasize as competitive differentiators. If a process is defined as a key differentiator, a company is likely to gather, save, and parse more data on that process than on a business-required function. As a result, some firms have more data on a given, differentiating process than others who view that process as business-required. And even if two firms call a piece of data by the same name, the reality is that data may be calculated, captured, and stored very differently by each organization. The Referees It is rare, if not unheard of, for competitors in an industry to share business intelligence directly. Companies generally rely on third parties to gather, analyze, and report business intelligence regarding relative performance. These third parties may be industry and professional associations, research firms, academic institutions, or consultants. They serve as referees among the competitors in the industry addressing the concerns identified above. In these arrangements, competitors share their information with the third party, instead of directly with other market participants, relying on the referee to maintain confidentiality in the process by summarizing and anonymizing data so as to protect all of the participant s proprietary information. Having provided the data to the third party, each firm knows where it stands on a particular measure, but only the referee knows every one s results. So confidentiality is preserved. Having a third party serve as the focal point to gather, summarize, and report business intelligence information also can address concerns related to a lack of standardization. As the referee in the process, the third party provider can facilitate (or dictate) the standard metrics to be gathered. This will generally be a collaborative effort. In established industries, a number of the key metrics are well understood by industry participants. However, as markets evolve and as the desire to dig deeper and better understand the underlying drivers of longstanding performance measures, the referee can once again serve as the middleman, working with competitors in the industry to reach a common understanding of what should be measured. In the same vein, a third party can play a powerful role in ensuring the consistency - or at least the comparability - of business intelligence data. In some cases, participants in an industry may choose to standardize the definition of the key metrics and voluntarily adopt those standards based on the simple understanding that, if the object of the exercise is to make meaningful comparisons of relative performance, the greatest value can be achieved by comparing apples to apples. However, even in industries where standards are not necessarily in place, the referee can add value. With access to all participants data and an understanding of how that data is gathered and reported, the third party provider may be able to provide guidance regarding relevant comparisons, even going so far as to provide customized results based on the understanding of the individual participant who is receiving the information. For instance, the referee may caveat particular metrics or even provide adjusted metrics for an organization which stratify or exclude results from other market participants based on factors such as size, geographic markets, or drastic differences in operating models. Of course, the third party provider can only fulfill this role if it has or can establish a high level of trust from the participants in the industry. In order to feel comfortable that proprietary information is protected and that the business intelligence data is meaningful, industry participants must be assured that the referee is treating all of them fairly and protecting their interests. As such, providers of business intelligence services must take all the steps necessary to build and maintain trust. Some providers (such as trade associations and academic institutions) are granted a high level of trust since they do not necessarily seek to profit directly from the business intelligence services they provide. However, organizations which seek to profit from their business intelligence services also have a vested interest in maintaining the trust of the industries they serve. Market participants who do not trust the provider will not share their information. Since the product these providers sell is information, the more they have, the more valuable the product they have to offer. To obtain the trust of their customers, these providers must BenchMark Consulting International 3 Timeliness of Business Intelligence Data June 2007

4 be clear with their constituents on how profits will be derived from the data provided and on the steps the provider will take to secure their proprietary information The Holy Grail: An Industry Data Warehouse Historically, third party providers of business intelligence services have relied heavily on surveys, questionnaires, or snapshots of performance data for a given period of time. All of these methods of gathering performance data have their own limitations. One potential drawback is that the information derived from each of these methods has a limited shelf life. One of the primary benefits of business intelligence is the ability to take the ongoing pulse of the competitive marketplace. With the pace of change constantly on the rise, this type of business intelligence will only become dated faster over time. This freshness issue is only compounded for this type of data because it must be gathered and compiled before it can be distributed to the user community. With the evolution of technology and the rise of third party providers of business intelligence services, the opportunity exists now to gather and share business intelligence data almost as quickly as they can compile and report on their own performance internally ( near real-time ). This ambitious goal can be accomplished by leveraging third party providers of business intelligence services to host industry data warehouses. Just as companies currently provide periodic or real-time feeds of data from their production systems to an internal data mart, the information necessary to calculate business intelligence measures could be routed to the provider s database. In exchange for feeding data into the warehouse, companies could be granted access to a portal to query and download information from the warehouse. Based on this approach to gathering and distributing business intelligence, the information available would be as fresh as the oldest feed from any participant. With the query capabilities offered in such a model, users could receive updates on performance on their schedule rather than relying on a survey or publication calendar. Furthermore, users could build their own queries and potentially download and massage data themselves rather than relying solely on the third party to analyze and summarize the information. Of course, as discussed above, the role of the third party as a referee in this model is even more critical. The provider, as the host of the data warehouse, will be responsible for securing each participant s data and controlling access to the data warehouse to ensure that the confidentiality of proprietary data is maintained. The referee will also be responsible for ensuring the quality and consistency of the data. This may require periodic reviews or audits of participant data feeds to ensure that a given metric is being reported consistently across all the participants to ensure meaningful comparisons. While the process and the role of the provider is different in this model, the level of trust required of the third party provider is even greater in this data warehouse model. Conclusion The evolutions of technology and business intelligence continue to converge. This convergence is delivering a potential quantum leap in the timely delivery of the information organizations crave in order to define and maintain their strategy and assess their performance relative to their competition. Just as companies currently maintain their own data warehouses that have transformed internal analysis and reporting, independent providers of business intelligence data are poised to provide industry data warehouses that will provide near real-time access to competitive performance information. The challenge for these independent providers will be to ensure that they maintain a position of trust with their customers, provide verifiable and invaluable data, and ensure that the security of each participant s data is maintained. With near real-time access to industry performance information, the potential rewards for industry participants and the business intelligence provider are huge. BenchMark Consulting International 4 Timeliness of Business Intelligence Data June 2007

5 Walter D. Cunningham is President at BenchMark Consulting International and possesses more than 20 years experience in the financial services industry. In addition to his other responsibilities, Cunningham has the responsibility for auto finance practice with a core focus on the strategic relationship management and consulting services delivery. Paul McNamara is a consultant at BenchMark Consulting International with extensive experience in the financial services industry. He specializes in commercial, small business, mortgage, and consumer lending. During his successful career in the industry, Paul has worked in a variety of functional areas and roles at leading financial institutions including credit; underwriting; loan operations; system design, development and support; call center administration; direct marketing; project management; and process improvement. BenchMark Consulting International has specialized in improving the financial services industry since The company is a management consulting firm that improves the profitability of its financial services customers through the delivery of management decision-making information and change management services to realize the benefits of business process changes. BenchMark Consulting International s expertise is in the measuring, designing, and managing of operational processes. The firm has worked with 39 of the top 50 (in asset size) commercial banks, all 14 automobile captive finance corporations, several of the largest consumer finance corporations and many regional and community banks throughout the United States. Internationally, BenchMark Consulting International has worked with the five largest Canadian commercial banks, more than 40 European organizations in 11 different countries, in addition to financial institutions in Latin America, Australia and Asia. The company is a wholly owned subsidiary of Fidelity National Information Services, Inc., with clients in more than 50 countries and territories providing application software, information processing management, outsourcing services and professional IT consulting to the financial services and mortgage industries. BenchMark Consulting International has dual headquarters in Atlanta, Georgia and Munich, Germany. For more information please visit BenchMark Consulting International 14 Piedmont Center NE, Suite 950 Atlanta, GA (404)