Modeling the business value of information technology

Information & Management 39 (2001) 191±210

Modeling the business value of information technology C. Sophie Lee* Department of Information Systems, College of Business Administration, California State University, Long Beach, CA 90840, USA Received 11 September 2000; accepted 8 February 2001

Abstract Modeling and measurement issues have been considered the heart of information technology (IT) productivity paradox problem. By collecting data from seven mortgage ®rms, this research attempts to shed light on the causal relationships and complementarity properties among IT and performance variables. The result is a multi-level business value model that connects the use of IT to a ®rm's pro®t. It is concluded that although there exists a causal relationship between IT and pro®t, this relationship is indirect and complex. Due to the complementary nature of the relationships, such a complexity is not reducible. All complementary factors must be in favorable conditions for a positive return of IT investments. # 2001 Elsevier Science B.V. All rights reserved. Keywords: IT productivity; Complementarity; Modeling and measurement; Business value of IT

1. Introduction The question of the ``productivity paradox'', why information technologies (IT) have not provided a measurable value to the business world, has puzzled researchers and practitioners. Although the power of computing to achieve higher quality with less time and effort is unquestionable, its bene®ts do not seem to be re¯ected in bottom line business performance Ð at least not according to a number of studies. While some studies have found positive associations between IT spending and workers' productivity or ®rm performance, most ®nd weak or even negative associations [3,6,16,41,42]. Measurement and modeling issues are most likely at the heart of the problem and may lead to the current inconclusive results in this line of research [4,24]. The many unique characteristics of IT make it particularly * Tel.: ‡1-562-985-1940; fax: ‡1-562-985-5543. E-mail address: [email protected] (C.S. Lee).

dif®cult to measure or model their value. For instance, capital spending of IT may not be an adequate predictor of ®rm performance because converting spending into effective IT utilization is still an open problem for management [25,37,39,45]. In addition, IT's effects can vary dramatically according to how and where they are used; measuring IT's contributions in isolation without controlling contextual variables cannot produce a meaningful indication of IT's business value. Furthermore, some studies have used a single production function to try to ®nd a direct correlation between IT spending and performance. However, the impacts of IT on performance variables may be indirect, and would not be discovered through this kind of modeling. The adequacy of methodology used to tackle this complex problem has often been a subject of debate [3,16]. Understanding IT's business value is a vitally important issue in today's technology-intensive world, and there is a need to establish a method that appropriately represents IT's value in a business context.

0378-7206/01/$ ± see front matter # 2001 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 7 2 0 6 ( 0 1 ) 0 0 0 9 0 - 8

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Such a method should capture the interactions between IT and the business environment, and provide a basis from which to evaluate IT's value. By adopting the grounded theory approach and studying seven mortgage ®rms, this study builds an IT business value model of the mortgage origination process from empirical data. The model of this process identi®es what and how IT are used, variables complementary with IT and the directions of such complementarity, and multi-layered causal relationships between IT and performance. The data suggest that there exist recognizable gaps between technology's availability and its use. It is also found that in the mortgage origination process alone, IT directly or indirectly interact with many other variables, going through layers of interactions before ®nally making an impact on performance. The complex nature of the business world sheds light on prior modeling and measurement problems. This paper makes a number of contributions to our understanding of IT's business value. First, this model attempts to uncover ``What'' is going on in the black box, and ``How'' these variables interact from empirical data. By discovering the variables and relationships from the viewpoint of real users, this research presents a closer picture of how IT work in reality. Since modeling IT presents many unique challenges to conventional methods of modeling, this paper draws new theoretical conclusions from the practices of the business world. As a result, it not only demonstrates the complexity of the environment, it also shows that such a complexity is not reducible. Second, it emphasizes the discovery and modeling of the complementary nature of IT from empirical data. Although it is generally agreed that IT do not exist in a vacuum, this study speci®cally tries to discover and model such a relationship. As will be seen later in this paper, data from this study suggest that such complementarity is likely to exist, and IT's value can be undermined if IT's complementary factors have unfavorable conditions. The study shows that for IT investments to pay off, one needs to closely monitor these complementary factors, not merely IT alone. Third, this study combines research methods from both the qualitative and quantitative schools, It uses the grounded theory approach to identify variables and their relationships, and formalize such relationships

into an economic model. This research strategy combines the strengths of both approaches and produces conclusions that are both relevant and rigorous. 2. Background Modeling and measurement problems can be fundamental to our understanding of the productivity paradox, and numerous papers have been published to examine the methodologies, modeling, and measurement issues [16,19,20,24]. Among many, several topics are considered critical to the current study and are reviewed in the following sections. 2.1. IT spending versus utilization One of the measurement problems involves using IT capital spending as an independent variable to predict performance. Many studies measure IT capital spending, but do not study whether such spending is transformed into actual hardware and software functions or whether such functions are actually used. A unique characteristic of information systems is the likely gaps between spending, functions, and use. Many companies spend millions of dollars on information technologies and systems but are unable to develop adequate or usable functions. The infamous IRS Tax Systems Modernization information systems project has spent over 9 billion dollars for over 10 years with practically no usable functions to show for it [2]. Furthermore, it is often reported that despite the availability of hardware and software, many users decline to use them, for usability reasons as well as for political and other reasons (for a complete review of IS use, please refer to [10]). Information technologies that are not used do not generate any value for the company. The ``conversion effectiveness'' problem has been recognized by many [25,27,45]. Although the difference between IT spending and IT utilization has been noted by many, data collection can be a painstaking process. Most IT utilization and management data are not collected as public data. In addition, researchers further face the problem of adequately measuring ``utilization'' of IT. This study reports the actual IT functions, uses, gaps between functions and uses, and any policy established to shorten such gaps in seven mortgage ®rms.

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2.2. The complementary nature of IT It is widely recognized that IT do not exist in vacuum, and their effects or uses are often accompanied by other factors, the status of which may determine how much value IT generate. For example, it is clear that IT used in an ef®cient process brings more value to performance than the same IT used in an inef®cient process. Measuring IT's contribution without controlling these other factors is a possible cause for the mixed results of this line of research [16,22]. The notion that ``x (e.g. IT) works better (e.g. generates more value) with a certain condition of y (e.g. an ef®cient process)'' has been referred to as ``®t'', ``synergy'', or ``complementarity''. It is a powerful concept because it shows that the effect of x should not be considered alone; it is always affected by another variable y. To make a wise investment in x, we should ensure that y is in a favorable condition; otherwise, the investment in x will generate a less favorable return. Modeling in complementarity provides a precise language to describe the usually complex interactions, and enables more inferences to be drawn from the formulation (such as optimization behavior), on account of an accumulation of theories and mathematical tools of complementarity [11,38,43]. Especially, Topkis' work on discrete problem domain and optimization has been referenced as foundation for a number of recent works [5,29]. Recently, there have been a growing number of studies in the literature that use complementarity to explain phenomena in organizations. Since organizational factors are often tightly connected, using complementarity as an analytical framework presents a natural ®t between theory and practice. Milgrom and Robert [29] showed that due to the complementary nature of new technological advancements such as shorter cycle time, smaller batch size, and more product improvements, it is optimal for manufacturing ®rms to adopt an entire series of new changes instead of isolated ones. In another study, the ef®ciency of process, the extent of IT used, and users' incentive systems are identi®ed as major complementary factors in a reengineering project [5]. The model shows that in order to achieve the highest possible return, the reengineering initiatives should simultaneously implement all of the changes in complementary directions. It also suggests that

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companies with ®xed, unfavorable conditions would not pro®t from drastic reengineering. In modeling IT's business value, it is important not only to realize that IT is complementary with many other variables and that such complementarity is critical, but we also need to know what variables are complementary with IT and in what directions such complementarity exists. To that end, this study intends to identify IT's complementary factors and the direction of such complementarity from empirical data. Such a ®nding can help identify possible control variables and study the best IT strategy for a given organizational context. 2.3. Modeling IT's business value Modeling problems have been at the center of the dif®culty in measuring IT's business value. First, ``information technologies'' as a general term includes so many different functions and features, some of them may have been designed for purposes other than increas-ing short-term pro®tability. For instance, in a study by [45,46], it is suggested that IT can be categorized as transactional, strategic, and informational. The purpose of strategic IT is to sustain long-term strategic advantage, or growth; therefore, a measure between strategic IT and performance should not show positive association. In addition, ``performance'' is often de®ned differently in different studies. Some de®ne it more as an end variable, such as pro®tability, while others de®ne it more as an intermediary variable, such as productivity. Secondly, some studies model IT's value by examining the direct associations between IT spending and a ®rm's performance, leaving the important interim process of transformation unexamined. Findings from this type of modeling are often puzzling, which shows that IT's impact on performance in a more complex process. More recently, it is recognized that there may exist layers of interactions between IT and a ®rm's performance [19,31], and studies have been conducted to examine the intermediary variables in the ``black box'' [4,32,33]. An extensive business value model of a customer service process in a reengineered context was established to describe the web of causal relationships between the drivers (various IT functions, incentives, characteristics of processes), intermediate variables (lead time, quality, and cost), and an end variable (pro®t) [5].

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This study uses data from empirical ®ndings to model speci®c intermediate-level variables and relationships in the mortgage origination process, and builds multilayered business value functions that link IT usage, intermediate variables, and performance. Many intermediate variables that are not covered in traditional literature but play crucial roles in reality are included through empirical ®ndings. Such a model helps us to understand what goes on in the black box between IT input and ®rm output and identify what variables are more likely to be directly or indirectly impacted by IT.

origination process involves approving new loans for customers. Despite the advance of computer automation in other ®nancial sectors, the origination process is still characterized by unnecessary handoffs and inef®ciencies [9]. In recent years, mortgage ®rms have become aware of the many inef®ciencies and nonvalue-added activities in the origination process and sought ways such as automation and new process design to improve it.

2.4. Research method

The selection of research sites in this study follows the theoretical sampling approach (or purposive sampling) in grounded theory; the purpose of sampling is to replicate or contrast cases in order to build a rich theory. I started the study with an inde®nite number of sites in mind. After interviewing mortgage of®cers from four mortgage companies Ð two are larger, national lenders and two are smaller, local lenders, I developed a knowledge of what constitutes ``hightech'' and ``low-tech'' for mortgage ®rms. I found that large lenders are usually more ``high-tech'' and can provide much richer, more contrasting perspectives into technologies and process redesign. ``Low-tech'' ®rms tend to provide a base-line description. Therefore, I deliberately looked for national, larger mortgage companies for later cases. These companies were identi®ed both through my own research (reading local trade journals), and through the recommendations of my prior cases. After interviewing three more companies, I stopped collecting data. In the later cases, no more new technological categories, process items, values of IT, insights, or ideas were introduced. At this point, I did not feel that more cases would add more richness into the theory; the study had reached theory saturation. Moreover, at each interview, I would ask the interviewee to recommend companies in the Boston area that do things differently or from whom I may learn something new. Most of the them pointed to three ®rms; all three have been included in my study.

Over the years, the methodology deployed to study the business value of IT has received almost as much attention as the subject of the research. Each method has its strengths to solve different facets of this complex problem. The case study approach is outstanding in its ability to detect causal relationships and gain insights into the question, but its generalizability or scienti®c basis (replicability) is questioned by many [40]. Economic modeling provides explicit assumptions and models, but the practicality of such assumptions are often in question. Researchers have called for an integration of different methods, or utilization of a portfolio of methods [21,22]. This study deploys combination of quantitative and qualitative methods. It uses the grounded theory approach [7,12±15,26,28,36,44] to discover possible variables and causal relationships empirically from the ®eld, and formalizes the variables and relationships into hypotheses and a multi-layered economic model. It intends to integrate the strengths of both ``schools'' of the MIS discipline to generate ®ndings that are not only theoretically rigorous but also practically relevant. In particular, the complementarity between variables and the properties between the dependent and independent variables are captured. By linking all variables and relationships through one formal mathematical formula, this research presents a more complete picture of IT's effect on pro®t and on other variables. 3. Research design The residential mortgage origination process is chosen as the substantive area of study. The mortgage

3.1. Site selection

3.2. Data collection The research was conducted between the end of 1996 and the beginning of 1997. Data were collected by personal interviews, review of company documents,

C.S. Lee / Information & Management 39 (2001) 191±210

and direct observation of the computer systems. In each company, one branch manager or mortgage of®cer was interviewed. I personally interviewed, observed, and coded all seven cases. Every interview followed the same open-ended questionnaire and was audiotaped. Each interview lasted between 1 and 4 h. In addition to providing background information, each interviewee was asked to describe in detail and in sequence each step in the mortgage origination process, from receiving a mortgage application to the sending of a commitment letters (a letter that indicates the formal, legal decisions on the loan case). For each step, the interviewee described the nature of the task, the participants in the task, any type of technologies and their use in the task, the amount of time required to accomplish the task, and any prerequisite tasks. I was able to grasp and relate to their comments rapidly because I myself had been a customer of the mortgage process a number of times. I also asked the interviewees to describe their perceptions of the bene®ts and the values of information technologies. This question often opened up our conversation and caused the interviewee to become very active and vivid in describing what computers can and cannot do, and what unanticipated effects the introduction of computer systems had on their company. The interviewees were asked to be as speci®c as possible. For example, if the answer was ``ef®ciency'', I would ask them to describe speci®c ``things'' of ef®ciency. They were also asked to reason or elaborate on variables or causal relationships once mentioned. In addition to interviews, I also reviewed and collected many documents. These documents include government-standard and company-speci®c forms, such as mortgage application forms, rate locking forms, current rate forms, credit report forms, and company White Paper reports. By reviewing the forms and documents, I could further verify their degree of computerization and how much they still rely on noncomputer means, or how much they have actually changed their process. Company annual reports were collected whenever available. I have also reviewed literature relating to the mortgage industry to further con®rm the ®nding of the study [1,8,17,23,34,35]. Another extremely important data source was the direct observation of each company's computer system. In all but one company, the interviewees showed me detailed demonstrations of their computer systems.

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Although no company was willing to release their system or users manual, I did sketch and record the interface and functions of each system in my memo. Some systems appeared to be old mainframe based systems that only recorded basic information such as housing price and down payment. Other systems appeared to be more sophisticated with Windows interface and more functions. As each interviewee demonstrated their system, I took note of the speci®c functions and what they did. The demonstrations proved to be an extremely useful data source for this study. Computer functions are dif®cult to describe verbally without a demonstration. While every company has a ``computer system'', their levels of sophistication vary widely. The demonstrations also enabled me to further con®rm the content of the interview. For instance, although having used a particular function many times, one interviewee did not know it was called a ``decision support system'' when it indeed was. As the research progressed, follow-up phone calls were placed to prior interviewees to con®rm new variables or relationships suggested by other interviewees. 3.3. Data analysis After each interview, I transcribed audiotapes of the interview, organized sketches and functions of computer demonstration, and recorded any other observations, impressions, and my own memos immediately. I started open coding after each case. Open coding is the identi®cation of concepts from the data, combining and integrating concepts into categories, and ®nding dimensions and properties of categories. Axial coding was also done to relate categories through relationships. Since the goal of this study is to discover a causal map linking the use of IT to performance variables, causal relationships are of particular interest in this study. Individual causal instances are identi®ed through the interviewee's description (such as ``by using IT, we reduce the operation time . . .'') and my observation (using computer system indeed shortens the time to look up a customer's information). Causal relationships are hypothesized when there are either recurring causal instances across cases, or when a causal relationship offers a plausible explanation to phenomenon across cases.

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Each new case triggers the re-examination of all prior cases, including all categories and relationships. Categories and relationships were revised each time to ensure that the latest version of the model can ®t all data. Categories were given new labels or de®nitions; some were replaced by more immediate variables. New insights, contrasts, and comparisons to earlier cases also helped me to re®ne categories and relationships. Special attention was paid to instances when there are con¯icting facts or unexplainable phenomena. I would call interviewees from previous cases and seek their suggestions. This often resulted in modifying or adding categories into the model. Here is an example of how such a process took place. Each mortgage company has a ``decentralized'' or ``centralized'' underwriting style. While processing of paperwork is always done locally at each branch, underwriting is done either at the same local branch (a decentralized style), or at a centralized location (a centralized style). For companies of the centralized style, transporting of paperwork could take days since the centralized location could be in another state. ``Centralized versus decentralized underwriting style'' or ``physical distance'' was at ®rst a category that may affect ``processing time''. However, with a closer look at the data and ``cross examination'' of cases, I found that the document transporting time is actually longer for certain decentralized companies than centralized companies. Why? Several centralized ®rms installed telecommunication systems between local branch and central underwriting centers, and loan documents were posted to the network for both sites to view simultaneously. The transport of document literally takes no time. For many decentralized companies, however, moving a package from the third ¯oor to the fourth ¯oor takes one business day. Therefore, ``physical distance'' is immaterial to ``processing time''. ``Telecommunication systems'' becomes the key category that causes a decrease in processing time. Note that such a causality is not obtained from any individual interviewee's direct testimony. Each company has only one underwriting style, and none would have had a comparative perspective. Such a relationship was obtained through the iterative, overlapping data collection and analysis technique in grounded theory. Toward the later part of the study, selective coding was in place. This is an iterative process to direct the

study to a focused central theme, choose core categories, and basically move the research from ``data and relationships'' to ``a model''. Many categories are combined into abstract core categories, and appropriate labels and de®nitions are added. For instance, ``telecommunication systems'' and many other IT items are combined into the ``IT'' core category; more speci®cally, it is de®ned as the ``use of IT'' with two dimensions: the possession of it, and the use of it. Another example is the initial category ``number of steps'' with dimensions such as participants, time, and tasks. In order to relate this category to other categories in the model such as time and cost, the ``leanness of process'' core category is abstracted. Instead of counting steps in the process, I abstracted the notion to re¯ect how ``lean'' the process is. The properties and dimensions to quantify ``leanness'' are also abstracted by comparative examining of data. Finally, internal consistency and logic is developed and checked to ensure a complete model. 4. Research ®ndings The model emerged from the study data describes a causal map from the use of IT to higher level performance variables. The IT usage gap, complementarity of IT and other variables, technical and human aspects of IT use, and the multi-layered interactions between IT and performance are all captured in this model. This model helps to explain many of the productivity paradox problems, and offers opportunities for more insights on IT management to be drawn. This section presents the core categories, hypotheses, and the complete model of this study. 4.1. Categories 4.1.1. Leanness of internal process (P) A traditional mortgage origination process involves much paper shuf¯ing, handoffs, and inef®ciency. The process starts when a potential mortgage applicant, with the help of the loan of®cer, ®lls out a lengthy loan application, and submits many supporting documents. The package is organized by the loan of®cer and passed down to a ``loan opener'', whose job is to verify the data again and enter data into the computer. Between the loan of®cer, opener, and ``processor'' Ð a

C.S. Lee / Information & Management 39 (2001) 191±210

person whose job is just to process paperwork, another dozen forms need to be sent out to different places, including employment veri®cation, asset veri®cation, credit history request, and property appraisals. In the meantime, the applicant must be reminded to mail in any documents that he did not submit during the application. Each document needs to be received, veri®ed, and ®led. To make things worse, there are usually many people involved in the process and they operate in complex ways: the person who sends out the request form is not the person who receives it; several people call the applicant to ask for the same document; the same document is copied many times and kept in different locations in the company. Finally, after all the documents are in place, the package is turned over to the underwriting department. The ®nal decision and terms are then written on the commitment letter and passed to the customer. The concept is named as ``the leanness of the process''. It is de®ned as the ability to complete required tasks with a minimum amount of waste. A high P value indicates a lean process where as a low P value indicates a wasteful process. By comparing the detailed processes of the seven companies, synthesizing their similarities and differences, and understanding how one company's problem is solved in another company, I summarized several characteristics to represent the leanness of a company's process. 4.1.1.1. Degree of duplicate work. This refers to the degree to which the same work is repeated by multiple people. For instance, in many companies, it is a common practice that both the loan officer and the processor are involved in collecting documents for an applicant. A lack of clear job assignments and accountability often result in duplication of work. The interviewee from Company 6 described his personal experience: . . . you would have two or three people calling the customer on different days and essentially request the same information. I remember as a loan of®cer, having the customer calling me and yelling at me and saying, `Why are you asking for this again? I gave it to Susan and now Bob wants it again!' Since it (the process of applying for a mortgage) is so emotionally charged, the customer would feel that the bank is not on their

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side; they are just asking for so much information. Company 1 still uses this as common practice: If there is any additional information needed on the case, both the loan of®cer and the mortgage processor would call the borrowers and request it. . . .. Borrowers can send additional documents to either the loan of®cer or the mortgage processor. The packages are compiled by both the loan of®cer and the processor. The degree of duplicate work can be reduced through clear job distinctions and accountability. For instance, instead of having both loan of®cer and processor working on all the paperwork, some companies assign each person to handle a speci®c set of documents. 4.1.1.2. Degree of handoffs. This refers to the situation where work is passed from one person to the next. In addition to the time needed for the document to travel from one person to the next, it also involves learning time for the new person to familiarize herself with the material. While handoffs are inevitable, some handoffs are unnecessary and should be minimized through process redesign. One possibility of unnecessary handoffs is where the activity is divided too finely, so there are many handoffs from A ! B ! C. Another situation is when two people are assigned tasks that are too closely related, thus there are constant handoffs between them, or A ! B ! A ! B. The following quotes re¯ect the handoffs situation in companies. Most loan of®cers take applications on their portable computers. They also collect documents during application. They use the computer and the hard copy to verify data on the application. Then the package is sent to a loan opener, who is a different person from a loan processor. The opener veri®es the data again, then she prints the veri®cation forms and mails them. Then the package is sent to the mortgage processor, who assembles the paperwork, opens the mail, and collects the veri®cation. In the meantime the loan of®cer orders appraisal and credit reports, but the loan processor is responsible for collecting them. This is how another company does it: The loan of®cers take the application. The loan opener takes the hard-copy application and inputs

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data into the computer system. She also generates veri®cation forms and sends them out. She orders credit reports and appraisals. Then the ®le is turned to the processor who would collect returned documents. The processor does the initial review, sends a follow-up letter to the borrowers, telling them what things are needed and introducing himself to the borrower. Handoffs can be drastically reduced by work integration and redesign. Work can be horizontally integrated so that one's job responsibility is enlarged to include similar tasks. For instance, instead of having one person order the credit report, and the other order the appraisal, and yet a third person receive the return documents, all tasks are performed by one person. In a vertical integration scenario, many sequential phases performed by different parties are combined into fewer parallel phases, performed by the same person. For instance, instead of having the application phase followed by the credit veri®cation phase, at Company 2, the two are done at the same time. Company 6 started the document collection phase even before the applicant's ®rst meeting with the loan of®cer (the application phase). 4.1.1.3. Degree of duplicate ®les. This refers to the practice of keeping duplicates of the same paper file at multiple locations. Driven by the overwhelming amount of paperwork and the fear of misplacing documents, everyone who ever touched a case is in the habit of keeping a paper copy of it. This is not only a waste of resources and time (to make copies), it also creates a great deal of work to keep all the files consistent. The Vice President at Company 7 indicated that: ``Both loan of®cer and processor can do processing. . . .. All documents are copied and sent back and forth between of®cer and processor since each of them keeps a copy''. By having a centralized ®ling system (either computerized or on paper), everyone could access the most current version of the ®le. All the updates would be made to the ®le, and data inconsistency problems would disappear. Many companies ®nd reducing the number of people involved in a case to be an effective way to improve the leanness of the process: it reduces the possibility of duplicate work, unnecessary handoffs,

and duplicate ®le problems all at once. The most extreme examples are in Company 2 and 6, where only one person is involved in processing all paperwork of a mortgage. Table 1 summarizes the process characteristics by company. The ``Degree of Duplicate Work'' is rated ``High'' when there appears to be totally duplicate work by two or more people during processing, and there is no indication of any separate job assignments. It is rated ``Medium'' where there is some separation between job assignments but some jobs are still duplicated. It is rated ``Low'' where the degree of duplicate work is reduced to the minimum, either by reducing the number of people processing paperwork, or by clear job assignments. The ``Degree of Unnecessary Handoffs'' and ``Degree of Duplicate Files'' are rated similarly. 4.1.2. Use of information technologies (T) A variety of IT software and hardware are used in a mortgage origination process. The variable, ``use of information technologies``, is de®ned as the use of information technologies in the mortgage origination process. First, companies that have these IT features have a higher T value than companies that do not. Second, having these features, companies that exercise mandatory use have higher T value than companies that do not practice mandatory use. The software and hardware features are summarized as follows. 4.1.2.1. Ratio calculation program. A software program that calculates the mortgage payment, debt ratios, and various other ratios after the housing and borrower data are input. This feature is the most popular IT function; it has been adopted and is used by all firms. 4.1.2.2. Decision support systems for mortgage products. This software program recommends feasible loan products instantly after the housing and borrower data are input. Traditionally, recommendations of products are made based on the loan officer's knowledge, experience, and printed guidelines, which might be subjective, incomplete, and time consuming. Only two out of seven firms have this feature and its use is mandatory. It is connected to the Ratio Calculation Program and considered a very handy and helpful program.

Table 1 Leanness of internal process by companya Company

1

2

3

4

5

6

7

Degree of duplicate work

High: highly duplicated work assignment between LO and PR Medium: handoffs between PR and LO High: duplicate paper files

Low: no duplicate work

Medium: clear job assignments in some areas

Medium: clear job assignments in some areas

Medium: clear job assignments in some areas

Low: no duplicate work

Medium: clear job assignments in some areas

Low: virtually no handoffs

High: handoffs between PR, LO, and OP High: duplicate paper files

High: handoffs between PR, LO, OP, and accounting High: duplicate paper files

Low: virtually no handoffs

2

3

3

Low: centralized computer filing 1

High: handoffs between PR, LO, and OP High: duplicate paper files

2

Low: centralized computer filing 1

Medium: handoffs between PR and LO High: duplicate paper files

4

2

3

4

5

2

3

Low

High

Low

Low

Low

High

Low

Degree of unnecessary handoffs Degree of duplicate files Number of persons processing paperwork Number of persons involved in case Overall leaness of process a

LO: loan of®cer, PR: processor, OP: loan opener.

2

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4.1.2.3. Application record keeping program. An electronic database system that captures the borrower's application data, such as income, work history, and credit history. Traditionally, the borrower's application data were written on paper forms, and keyed into computer systems later. This feature is found in all seven companies and its use is all mandatory. 4.1.2.4. Laptop computer. Laptop computers give loan officers the flexibility to input application data at places convenient to the clients, such as their homes. Six out of the seven firms provide loan officers with laptop computers. The usage rate, however, is well understood to be low. Since traditionally the key-in of data was not performed by loan officers, many loan officers view learning and using this software as additional work. Only one company developed policies to make laptop computer usage mandatory. 4.1.2.5. Portable printers. Portable printers enable mortgage application forms to be printed anywhere, especially places convenient to customers. Printing forms can be a critical element in processing time because many forms require the borrower's signatures. If printed on site, the forms can be verified, signed, and filed right away; otherwise, the forms will be printed later and be mailed back and forth for verification and signature. Companies that provide loan officers laptop computers also give them portable printers; however, it is understood that the usage is not mandatory. Portable printers are very slow, and it was embarrassing for the loan officers to wait during printing. 4.1.2.6. Modem on laptop computers. This feature enables the officer to transmit mortgage application data and lock an interest rate from a laptop computer instantly. Four out of seven companies have this feature, and two make it mandatory to use (i.e. the loan must be registered through modem). 4.1.2.7. Status tracking program. This software program keeps track of the status of a loan file, primarily of the completeness of required documents. This feature is particularly useful, since chasing required documents is considered a very lengthy and laborintensive part of the process. With this program, it

is very clear to the borrowers and the processing center which documents are completed or still needed. Without it, processing personnel must manually search through mountains of paper files. As a result, mistakesanddelaysareverycommon,such thataneeded documentmayneverberequested,orthesamedocument is requested several times. In this study, only two out of seven companies have this feature; the other five companies still take manual notes. 4.1.2.8. EDI to credit bureau. Electronic data interchange (EDI) with credit bureaus enables the borrower's credit report to be composed and viewed in a matter of minutes. Without EDI, a paper request for a credit report can take 3 days to 1 week. This feature is becoming the norm of the industry, and six out of seven firms have this feature. Its use is mandatory. 4.1.2.9. Decision support system for underwriting. Artificial intelligence and credit scoring are used to generate an index for the quality of the loan profile. The system also includes a knowledge base of underwriting guidelines for the underwriters' reference. Without this system, loans are approved upon the underwriter's own knowledge and experience, sometimes subjectively. Only one company has this feature. After being scored, loans that have very good or poor ratings are approved or rejected right away; only borderline loans will need a human underwriter's approval. 4.1.2.10. Telecommunications between processing and underwriting. This feature enables the loan officer to transmit a complete loan file to underwriters for underwriting and to have immediate access when a loan decision is made. This feature eliminates the back and forth of mailing and the possible confusion and delay caused by phone tag, which has been the traditional way of doing business. Three out of seven companies have this feature, and its use is mandatory. 4.1.2.11. Automatic printing of commitment letters. This feature involves mail merge and links to the borrower's computer file, which enables the decision and conditions of a loan to be printed directly on a form letter. Traditionally, a loan processor would use a

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201

Table 2 Use of IT by companya Company

1

2

3

4

5

6

7

Ratio calculations DSS for mortgage products Application record keeping Laptop computer and usage Portable printers and usage Modem on laptop computers Status tracking EDI with credit bureaus DSS for underwriting Telecommunication between processing and underwriting Automatic printing of commitment letters

‡‡

‡‡

‡‡

‡‡

‡‡ ‡ ‡ ‡ ‡‡ ‡‡

‡‡

‡‡ ‡‡ ‡‡ ‡‡ ‡ ‡‡ ‡‡ ‡‡ ‡‡ ‡‡ ‡‡

‡‡

‡‡ ‡ ‡

‡‡ ‡‡ ‡‡ ‡ ‡ ‡

Overall IT and use

Low

High

High

‡‡

‡‡

‡‡ ‡‡ ‡‡

‡‡ High

‡‡ ‡ ‡

Low

High

Low

‡‡ ‡ ‡ ‡‡ ‡‡ ‡‡

a

( ): Indicates that companies do not have this feature; (‡): indicates that companies have this feature but the use is not mandatory; (‡‡): indicates that companies that have this feature and the use is mandatory.

typewriter to fill in a form letter from the underwriter's hand-written notes. Any typo or mis-interpretation could cause the borrowers to fix the wrong conditions and delay the processing of the loan. Three out of seven firms have this feature, and its use is mandatory. Table 2 summarizes the actual functions and usage found in the seven companies. 4.1.3. Origination cost (C) The category ``origination cost'' represents the average unit cost of originating a mortgage. According to the Mortgage Bankers Association of America (MBAA) 1995 survey of 200 mortgage companies [30], on average, each mortgage production incurs US$ 2324 cost. The biggest cost item is ``loan processing expenses'', US$ 690, followed by ``in-house origination employees'', US$ 623, and ``loan origination of®cer'' (commissions), US$ 452. Notice that the processing employee salary and expenses represent well over 50% of the total origination cost. It is well known within the mortgage industry but not widely publicized that origination actually generates negative income ¯ow to the company. According to the same survey by MBAA, on average each mortgage production generates US$ 952 income while incurring US$ 2324 cost, which leaves a net loss of US$ 1372 per mortgage generated in house. An interviewee states that `` . . . on origination, you lose one half percent of the loan, counting commissions, rent, administration cost, and so forth''.

4.1.4. Cycle time (t) The cycle time category represents the elapsed time from the point where the borrower applies for the mortgage, to the point when the commitment letter is issued. The current industry standard is about 4 weeks, while more ambitious companies have expressed the hope of reducing it to 1 week. The importance of cycle time as a variable is stressed by many. The mortgage business is emotional, just like real estate. You would think that it is a rational business, but it's not. Customers sometimes apply for mortgages at two places and go with the one who approves them ®rst, even if their rates are higher. That is becoming the trend of the industry, where people want to be pre-approved before they even go to look for a house. Beginning to end, on average, the process takes 45 days. That has been the norm of the industry. Our goal is to shorten it, because we felt that we can do more business if we can close up the pipeline more quickly and get more loans in the system. 4.1.5. Mortgage of®cer retention (I) Mortgage of®cer retention is de®ned as the rate at which a company retains mortgage of®cers. Although to the naive eye mortgage products appear to be identical and differentiated only by interest rates, a ®rm's existing loan of®cers and their sales skills are

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critical to the company's pro®tability. Top producers can consistently bring in millions of sales every month, due to years of experience in the industry, the wide customer net they generate over the years, their ties with the high-priced housing industry, and personal characteristics (some people are just better at sales than others). The strategic importance of mortgage of®cers to a mortgage company is similar to that of realtors to a real estate company or faculty to a university. Since mortgage of®cers are the primary source the mortgage companies rely on to generate income, retaining mortgage of®cers, especially experienced ones, is a critical task. 4.1.6. Control over external process partners (B) This category is de®ned as the extent to which the company exercises control over external business partners, such as realtors, customers, and appraisers, in order to better manage the mortgage process. Many companies mentioned that despite managing in-house processes, the most time-consuming activities Ð which determine the total cycle time Ð are often in the hands of other business partners. One such partner is the appraiser, who needs to physically enter and inspect the property. Often times, this is not controlled for and may delay the whole process. The processor would order appraisals. The appraiser would call the realtor and set up a time to look at the property. If the broker says, `I do not have time until next week', it is going to slow down the process. To order the appraisal, I would call and fax the appraisal form to the appraiser. Time wise, it depends on the availability of the appraiser, real estate agent, and the property. It can take anywhere from 1 to 2 days to, well, um. . . usually not more than 2 weeks. One company exercises moderate control over the appraiser: As a lender, we can dictate some of the terms . . . with the appraisers. If the appraiser is going to take 2 weeks to get the appraisal back, we are not going to use them that often. So, we say we want to have it back in 2 days. Another company exercises strict control over the appraiser: We generally want to have the appraisal back within 72 h. If you cannot do that, we will send it

to somebody else. That's on a written agreement system. Again, that's our goal to press the process into 7 days, versus the industry average, which is about 3±4 weeks. Another source of delay is caused by customers themselves failing to provide complete documents. What we are trying to do as a company is to issue a commitment letter within a couple of days, but that's assuming that it is a good, complete package there. If it is going to take longer than that, that is because not all the information is there that we need. The borrower may not be providing it in a timely fashion. The majority of the companies I interviewed are aware of this problem but do not have a systematic method to speed up the document collection process, other than constantly calling the customers to remind them. Only one company has wisely enlisted the realtors to help them. Since most customers use realtors to locate a property, this company gives realtors their company's envelope with a checklist of needed documents. Customers are given the envelope during house hunting, and start to collect documents well before they actually apply for a mortgage. By the time the loan of®cer meets with the customers, they are more likely to provide complete documents. Since 50% of this company's customers are referred by realtors, this is a very effective way to attract customers and reduce document collection time. 4.1.7. Price (p) Price is de®ned as the average unit price the mortgage company charges the customers. Price items include origination fee, and various other fees charged to the customers. According to the Mortgage Bankers Association of America's 1995 survey of 200 mortgage companies, the total loan production income is US$ 952, which includes loan origination fee of US$ 737, document preparation fee and attorney fees of US$ 210, and other operating income of US$ 4. 4.1.8. Customer base (V) The category ``customer base'' is de®ned as the total number of customers who have mortgages originated by the mortgage company. Customer base is probably one of the most important variables in this business value model. It has direct association with sales, and it has an intangible effect on the ®rm's

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image, which contributes to possible increase in market share. The importance of this variable in the model was con®rmed by the numerous times the words ``our customers'', ``clients'', ``borrowers'' are mentioned in the interviews. 4.1.9. Marketing (M) The ``marketing'' category is de®ned as the marketing effort of the mortgage company to attract more business. It includes providing more innovative loan products, advertising, exploring new geographic territory, building reputation, exploring niche markets, and many other factors. We intend to open production of®ces in speci®c areas where we are not presently well represented. . . .. We also plan to add smaller satellite of®ces, which are relatively inexpensive to open and operate. It is important . . . to offer our customers as many ®nancial products as possible in order to increase our earnings. These new products include adjustable rate mortgage products, a pre-approval program which approves a loan application before the customer selects a home, another program which enables the home owner to temporarily buy down his mortgage rate, resulting in a reduced monthly payment, and a home equity line of credit which allows a home owner to borrow against the equity in his home. (The company)'s radio, television and print advertisements include a toll-free telephone number that potential borrowers can call to obtain information about home loan products. Looking ahead, management sees an increased emphasis on conducting business electronically. For example, borrowers will utilize the Internet with increased frequency to apply for a mortgage. 4.1.10. Pro®t (p) Pro®t is de®ned as V…p c†, or the customer base multiplied by average unit price minus average unit cost. This de®nition is consistent with that used in most economic literature. 4.2. Hypotheses Hypothesis 1. C (origination cost) is a function of T (information technologies) and P (leanness of internal

203

process). (T, P) are increasing1 and complementary in C. 2 Hypothesis 1 states that information technologies and leanness of process are both factors of origination cost. (T, P) increasing in C means that as information technologies increases, origination cost decreases ( C), and that as the leanness of process increases, origination cost decreases. In addition, the hypothesis further states that the two are complementary in C, which means that the same technologies have more power to reduce origination cost when the process is leaner, and the process has more power to reduce origination cost when there is more technology usage. IT reduces origination costs in a number of ways. By using an application record keeping program, a status tracking program, and telecommunications between processing and underwriting, the progress of a current ®le is under better control, the coordination among workers is better, work is performed with higher ef®ciency and less waste in terms of of®ce supplies and labor. There is less need for personnel whose job is simply to collect and distribute paperwork. The leanness of the process also has a signi®cant impact on reducing origination cost. A lean process reduces the amount of duplicate work, handoffs, and duplicate ®les. As a result, the company needs less non-value-added activities and fewer employees. For instance, by reducing the number of people working on the same ®le, the company eliminates the need to make multiple copies of the same ®les as well as the labor involved in keeping them updated and consistent. The study data suggests the possibility that the use of IT and the leanness of process has a complementary effect in reducing costs. That is, while using IT and improving the leanness of the process each reduces costs independently, doing both will have a more dramatic effect than the additive effects of each. One company was able to totally eliminate the position of ``mortgage processor'', because all the 1 For f(x), x is increasing in f means that if x00  x0 , then f …x00 †  f …x0 †; x is decreasing in f means that if x00  x0 , then f …x00 †  f …x0 †. 2 ``(T, P) are increasing in C'' means that as T increases, C decreases (or C increases) and that as P increases, C decreases. ``(T, P) are complementary in C'' means that T and P has complementary effect in reducing origination cost.

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processing tasks were automated and could be handled by loan of®cers. Without IT, such an elimination is impossible, or at best causes chaos in the organization. Similarly, if a company uses IT but still maintains the traditional process, the surplus generated by IT will be absorbed by the inef®ciencies. The real savings are achieved by using IT to create a new and more ef®cient process, rather than simply to automate parts of the old process. According to one manager (Table 2): In the traditional model, you have the processor, the opener, the closer, the underwriter, and the loan of®cer, at least ®ve people that have to interface with the customer. Now generally speaking, we have loan of®cers Ð mortgage specialists who combine the duties of the opener, processor, and closer into one job . . .. They can do that because they do not have to physically type in data. Because we reduce the documents, we can combine the four jobs into one. One company has achieved a positive income on mortgage origination in year 1995, which is highly unusual in this business: We were able to bring down the origination cost from 1700±1800 to 1200 per loan, including commissions. It was done by both technology and process, well managed process, so we can control cost much better. Hypothesis 2. Cycle time (t) is a function of T (information technologies), P (leanness of internal process), and B (external process). (T, P, B) are increasing and complementary in t. This hypothesis states that information technologies, leanness of process, and control over external process are all factors in cycle time. More information technology usage, leaner process, and more external process control contribute to the decrease of cycle time ( t). In addition, the hypothesis further states that the three are complementary in t. It means (1) keeping external process control (B) constant, T and P are complementary in reducing t (or, the same technology usage reduce cycle time more when the process is at a ``leaner'' status and the same lean process can reduce cycle time more when the usage of IT is at higher status), and (2) keeping P constant, T and B are complementary in t, and (3) keeping T constant, P and B are complementary in t.

IT has a signi®cant impact on reducing cycle time, according to the interviewees' experience. By using laptop computers, portable printers, DSS to ®nd the right loan products, and telecommunication between different parties, a loan of®cer can complete tasks that used to take days or weeks in a matter of hours. By tracking the loan ®le electronically, the time needed to coordinate multiple paper ®les and search through mountains of paper is reduced. With EDI, the time required to obtain a credit report was reduced from 3± 5 days to 3±5 min. IT has a great effect on reducing time. From application to commitment letter, it now takes 5± 7 days, versus the 4±6 weeks, which was the industry norm. If the package is complete, we can do it in 2.5 days. A lean process also reduces cycle time. A lean process has fewer handoffs and fewer duplicate ®les. People no longer spend time on non-value-added activities such as duplicating ®les or passing the same paperwork back and forth; rather, the time is spent on getting things done. The more integrated work design eliminates arti®cial ``phases'' of the process, and jobs are completed in a parallel fashion. In addition, the control of external partners such as customers and appraisers also contribute to cycle time reduction. By formalizing the expected turnaround time on the appraisal, a company was able to restrict its turnaround time to 3 days, instead of aimlessly waiting for 2 weeks. The most substantial cycle time reduction comes from using IT to implement a more ef®cient process instead of using IT or process alone, which demonstrates the complementarity of IT and process in reducing cycle time. Adopting IT without process redesign, a company may save hours of time from data entry and input, but more time is wasted in nonvalue-added and repetitive activities. Similarly, improving the leanness of a process is often impossible without the help of technologies. By adopting IT and improving process simultaneously, all paperwork is veri®ed, signed, entered, and credit issues are resolved in a one-stop process; the time savings can be dramatic. The entire cycle time also depends on the turnaround time of external processes, such as the customer's data collection and the appraisal. Even if both internal process and IT are well-designed, a slow customer or appraiser would still delay the process.

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From the above analysis, it is reasonable to hypothesize that IT, process, and other business partners are all important factors in determining cycle time; in addition, they are likely to have complementary effects on reducing cycle time since a low score in any of the three would signi®cantly increase the total cycle time. Hypothesis 3. I (loan officer retention) is a function of T (information technologies) and P (leanness of internal process). (T, P) are increasing and complementary in I. This hypothesis states that information technologies and leanness of process are both factors in retaining loan of®cers. Somewhat surprisingly, a higher level of information technology adoption and a tightening of the process may have a negative impact on retaining loan of®cers, and such negative impacts are complementary. This hypothesis seems counter intuitive at ®rst, but an understanding of the organization culture and an analysis of the interview data suggest otherwise. In the past, loan of®cers were responsible for attracting customers and retaining them. Once an application was hand-®lled, the loan package was passed on to the ``processing'' division. Chasing documents, making copies, and ®ling paperwork were processors' duties. The loan of®cer was involved in processing just enough to keep in touch with the customer. In many companies, the loan of®cers and the processors are on different ¯oors in the same building, and their skills, responsibilities, and status are distinctively different. Since they were trained this way and expectations were set this way, it is not surprising that many loan of®cers view learning about and using computers as additional work. Loan of®cers are used to the people-oriented, sales-type tasks. Using computers to enter data or generating reports is considered ``processors' work'', not ``loan of®cers' work''. Also, using computers do not directly increase their customer base; they only create more work for the loan of®cers. In addition, the lean process Ð usually coming with tighter cost and ef®ciency monitoring Ð may also have a negative impact on mortgage of®cer retention. As a result of the new process, loan of®cers are often asked to do things that were done by processors, which means more work for the same pay.

205

One company took the drastic measure of forcing everyone to use IT and a new process. This resulted in losing many highly-successful and experienced loan of®cers, who simply felt that it was a degradation of their job (``I have to type my own report now!''). As a result, the company did save much on the expenses, but their sales were also badly hurt. The people who are willing to learn tend to be younger mortgage of®cers who have less experience and fewer connections than the more experienced ones. The following quotation re¯ects the situation: Use of a laptop computer is now a condition of employment. It is unusual. In some aspects it gave us problems. Because loan of®cers come in and say, `Now I have to learn all these new technologies. . . .. I have talked to some of the loan of®cers and they have said, `Well, I have to do all this work'. In some cases we have lost the top producers of the sales reps (representatives). They would say, `I write 15±20 million dollars of business every year, I can go anywhere, any one would hire me, and I am not going to do all this work'. They would go and work for our competitors. Sometimes they come back because they feel, `Ok, now it takes 6 weeks to get a loan'; sometimes they just move on. So, the type of reps we tend to attract is the 6±8 million dollar producers, who had to learn how to use computers . . .. We tend to get representatives who were not necessarily the top of the market sales reps, but we get middle type of reps who are good at technology, at computers. It is a tough process (to make the changes). The loan of®cer would tell you that processing papers is not their job. Similar experience was also noted in other companies. Although these companies knew their mortgage of®cers were not really using the new technologies, they did not pursue it further. One reason may have been to retain mortgage of®cers. As a regional manager put it: ``It was our intention to give them (the loan of®cers) laptop computers, and everybody would use them, but that is not happening. They do not like to use computers''. But when asked: ``What will you do about it?'' He just shrugged his shoulders. This hypothesis offers a very plausible explanation for the IT productivity paradox problem. Even though the companies are fully aware of the ``complementary''

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changes in technology and people, it is easy to change technology but dif®cult to change people. Under the pressure of pre-existing interests and conditions, their IT investments are not likely to be as effective. It is also noted that human reactions to work environment are very subtle, and there may be ranges of T and P value for this hypothesis to hold. That is, the of®cer retention rate is signi®cantly and negatively affected only when T and P reach a very high level. Hypothesis 4. V (customer base) is a function of p (price), M (marketing), I (officer retention), and t (cycle time). ( p, M, I, t) are increasing and complementary in V. First, this hypothesis assumes that price is a factor in customer base, and a lower price ( p) will increase customer base (increasing in V). This is consistent with most economic literature. Next, Marketing plays a signi®cant role in customer base. Heavy advertising increases name recognition, which helps to attract customers. Home owners with high interest rate mortgages are identi®ed as target customers for re®nancing by direct marketing efforts. Companies also seek to propose new and more ¯exible mortgage plans to lure customers with different backgrounds and needs. Other marketing efforts include providing convenient access to mortgage information and services. The effect of mortgage of®cer retention on customer base is also very strong. Mortgage of®cers are the company's most important sales force to solicit products, as well as to attract and retain customers. A top producer may bring in double or even triple the amount of an inexperienced loan of®cer. The study data also suggest that time is a factor in customer base; a shorter turn around time ( t) may increase customer base. ``Everyone wants the process to be faster. We typically get approval, instead of 2±3 weeks, in 2±3 days. It increases our credibility and the customers' happiness with the transaction''. It used to be 5±10 years ago, a 90-day contract. When I started, it was a 60-day contract. Now it is more like 45 days . . .. But to make the process, you have to set expectations for the industry. We envision ourselves to be the leader in the industry. A customer approved after 60 days is NEVER happy. Our feeling is that if we can get the customer satisfaction, we have good word of

mouth. The word of mouth is very favorable if we close the loan quickly. Does IT play a role in increasing customer base? ``Not directly'', according to many interviewees. Customers will not come because you have technologies; they come because you have better rates, faster turnaround time, and better services, which can be done through technologies. The complementarity of the four factors can also be justi®ed. For instance, marketing will not be as effective if the company offers expensive products, lengthy turn-around time, and inexperienced of®cers; marketing will be more effective if all the conditions are favorable. Similarly, a fast turn-around time would generate a larger customer base if all the other conditions are favorable. Hypothesis 5. Price (p) is a function of C (origination cost). Price (p) is increasing in C. This hypothesis suggests that price is a function of the origination cost. Companies view a reduced origination cost as an opportunity to lower price, which makes them more competitive in the market. Our goal is to lower cost, which can be achieved by technologies, by streamlining. After we lower the cost, we can lower the price and attract more customers, become more competitive. Similar observations were made in other studies [16]. According to the theory of competitive strategy, if any ®rm is able to obtain supernormal pro®ts by adopting technologies, other ®rms will join in and drive down the price. This may also help to explain the productivity paradox. Even though IT can help reduce cost, companies reduce price as a result. Therefore, their pro®t margin remains the same and does not correlate with IT spending. 4.3. Final model Finally, according to most economic literature, we assume that pro®t, p, is equal to V…p C†, where V is customer base, p the price, and C the origination cost. Combining Hypotheses 1±5, we have p ˆ V…p C†, or fp …M; B; T; P† ˆ fV …ft…T; P; B†; fp …C†; fI…T; P†; M†  …fp …C†

fC …T; P††

(1)

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207

Fig. 1. The model.

where p is the pro®t, p ˆ fp …M; B; T; P†; V the customer base, V ˆ fV …t; p; I; M†; p the price, p ˆ fp …C†; C the origination cost, C ˆ fC …T; P†; M the marketing efforts; I the mortgage of®cer retention, I ˆ fI …T; P†; t the cycle time, t ˆ ft …T; P; B†; T the use of information technologies; P the leanness of internal process and B the control of external process partners. The following is a graphical representation of the business value model (Fig. 1), where the arrows indicate causal relationships. According to this model, an organization can choose to set the value of the following variables: the leanness of internal process (P), the amount of information technologies usage (T), the control over external process partners (B), and the amount of marketing effort (M). As a result, P and T have a positive and complementary effect on reducing origination cost (C); P, T, and B have a positive and complementary effect on reducing cycle time (t); and P and T have a complementary and negative effect on the loan of®cers' retention rate (I). In addition, origination cost (C) has a positive effect on price (p) Ð that is, if the origination cost is lower, the price would be lower. Customer base (V) is impacted by four factors: price, cycle time, of®cers' retention rate, and marketing effort. Among the four, low price ( p), short cycle time ( t), high of®cer retention (I), and high marketing (M) have a positive and complementary effect on increasing customer base.

And ®nally, pro®t (p) is customer base (V) multiplied by unit pro®t, or price (p) minus unit cost (c). This model re¯ects the variables, causal, and complementary relationships found in the grounded theory research in one formula. According to this model, information technologies (T) and pro®t (p) do have a causal relationship, but this relationship is rather indirect. Using information technologies may very well improve cycle time or reduce origination cost, for instance, but the positive impact on the ®nal pro®t is only realized when other complementary factors are also in favorable conditions, such as a superior marketing plan and high loan of®cer retention. Empirical data of this study show that not every company is able to take advantage of the complementary moves. For instance, take the T (information technologies) and P (leanness of internal process) values for an example. Company 2 and 6 have both high T and P values. These companies adopted advanced information technologies and in the meantime, revamped their processes to take advantage of the investments. Company 4, on the other hand, had high T value but a low P value. This means that the company does use sophisticated information technologies but their process remains traditional and rather wasteful. That is, although they automate some of their operations, the entire management structure and reporting hierarchy is the same. However, Company 2

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and 6 do have a high revenue as payoff? Not necessarily. Company 6 admits that their revenue was badly hurt because, under the enforcement of new technology and process policies (high T and P values), many loan of®cers left the company (a low I value.) As a result, for the most recent quarter, their revenue was worse than before they adopted the technologies and internal processes. 5. Conclusions and limitations This study intends to model business value of information technologies by developing an economic model using the grounded theory approach. Choosing the residential mortgage origination process as the substantive area of study, this research identi®es the types of IT and their usage behavior in the ®eld. The business value model includes other variables such as origination cost, cycle time, loan of®cer retention, control over external partners of the mortgage company, and marketing effort. Behavior and properties of these variables are also described. Data from this research suggest possible causal relationships between the use of IT and variables such as cost and time. By examining recurring cases, hypotheses were developed to suggest the complementarity properties between IT and other variables. In summary, this study supports the notion that there is an indirect and complex causal relationship between IT and pro®t. This research helps to shed light on the productivity paradox problem, or the inconclusive association between IT spending and ®rm performance. By studying actual interactions inside the real world ``black box'' where IT generate value, this study ®nds that the ``black box'' is actually very vibrant and complex. In the mortgage origination process alone, IT are shown to interact with many other variables, going through layers of interactions to ®nally make an impact on pro®t. Since what goes on in the black box actually determines the level of value IT can deliver, previous models analyzing associations between IT and pro®ts in isolation of other controlled variables or intermediate variables may be inadequate to represent such interactions and the value of IT. In addition, the model also offers explanations as to why IT impacts lower- or intermediate-level variables, but not high-level variables such as pro®t. As the

model shows, the impact of IT on intermediate-level variables such as cycle time or origination cost is simple and direct. Toward the top level of the model, more variables and interactions come into play. Due to the complementary nature of IT and these variables, IT will not make a positive impact to pro®t if any of the complementary variables has an unfavorable condition. Therefore, more management efforts are needed to ensure a favorable overall results. It is perceivable that not every company is able to deliver this kind of careful planning and management. Many insights of IT management can be drawn from this study. The study shows that well-managed IT can generate tremendous value. IT can reduce cycle time and cost, and virtually change the way business is run. What used to take days or weeks can now be completed in hours with lower cost and higher quality. Companies with innovative ideas and visionary foresight can explore the unlimited potential IT bring. Also, IT's effects are best materialized when they are used to implement ef®cient processes. Judging from the complementarity of IT and process, adopting both strategies can provide much greater bene®ts than adopting IT alone. On the other hand, this research also shows that managing IT is a tricky and costly business. Due to the complementary nature of IT with many other variables, one has to know what variables to manage and how to manage them in order to make IT investments pro®table. One has to identify all other variables affected by technologies and align them to explore the full potential of IT. As witnessed by one company, top of the line IT and ef®cient processes may not produce pro®ts if the employees' incentives are not well managed; yet such incentive problems are actually caused by the new IT and processes. Since such impacts are usually not foreseeable or documented, companies have to experiment and learn from their experiences. Many key limitations facing this study call for more research efforts. One limitation is the potential of subjectivity. The identi®ed variables and causality are limited to the interviewees' personal perception and the author's interpretation. Moreover, the question of ``the value of information technologies'' may be beyond anyone's comprehension when discussed at a macro level. Another limitation is related to the dif®culty of modeling human behavior. Economic researches are

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often criticized for making unrealistic assumptions; however, without those, the model will become too complex and untraceable. We have seen economic literature that starts to model human feelings, such as peer pressure [18]. There is a need to model human behavior given its importance in understanding IT in organizations. This paper has incorporated human behavior as an important part of an otherwise pro®t and cost model: loan of®cer retention rate is modeled as a subtle reaction to changes of technological and process policy. However, whether organizational memory and culture also play a role in this interaction and how these behaviors can be modeled needs further work. Lastly, the increasing and complementarity assumptions in the current hypotheses are insuf®cient for an optimal solution to be derived. More properties such as higher orders of complementarity as well as ranges of complementarity are needed before more mathematical conclusions can be derived. This will rely on future work of data collection and testing. References [1] L. Allen, Sales force automation, Mortgage Banking 57 (2), 1996, pp. 101±103. [2] G.H. Athenes, IRS project failures cost taxpayers US$ 50B annually, Computerworld, 30 (42), 1996, pp, 1±4. [3] R. Banker, R. Kauffman, M. Mahmood (Eds.), Strategic Information Technology Management: Perspectives on Organizational Growth and Competitive Advantage, Idea Group Publishing, Hershey, PA, 1993. [4] A. Barua, C. Kriebel, T. Mukhopadhyay, Information technology and business value: an analytical and empirical investigation, Information Systems Research 6 (1), 1995, pp. 3±23. [5] A. Barua, C.S. Lee, A. Whinston, The calculus of reengineering, Information Systems Research 7 (4), 1996, pp. 409±428. [6] E. Brynjolfsson, The productivity paradox of information technology, Communications of the ACM, 36 (12), 1993, pp. 67±77. [7] L. Calloway, G. Ariav, Developing and using a qualitative methodology to study relationships among designers and tools, in: H.-E. Nissen, H.K. Klein, R. Hirschheim (Eds.), Information Systems Research: Contemporary Approaches and Emergent Traditions, Elsevier, North-Holland, Amsterdam, 1991, pp. 175±193. [8] S. Cocheo, Grooming the workhorse of mortgage technology, ABA Banking Journal 88 (9), 1996, pp. 92±98. [9] R. Cross, K. Monahan, Redesigning the process, Mortgage Banking, 57 (3), 1996, pp. 37±43.

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[39] N. Prattipati Satya, O. Mensah Michael, Information systems variables and management productivity, Information and Management 33 (1), 1997, pp. 33±43. [40] C.B. Schoonhoven, Problems with contingency theory: testing assumptions hidden within the language of contingency theory, Administrative Science Quarterly 26, 1981, pp. 349±377. [41] P. Strassmann, Information Payoff, Free Press, New York, 1985. [42] P. Strassmann, The Business Value of Computers, Information Economics Press, New Canaan, CT, 1990. [43] D.M. Topkis, Minimizing a submodular function on a lattice, Operations Research, 26 (2), 1978, pp. 305±321. [44] K. Toraskar, How managerial users evaluate their decision-support? A grounded theory approach, in: H.-E. Nissen, H.K. Klein, R. Hirschheim (Eds.), Information Systems Research: Contemporary Approaches and Emergent Traditions, Elsevier, North-Holland, Amsterdam, 1991, pp. 195± 225. [45] P. Weill, M. Olson, Managing investment in information technology: mini case examples and implications, MIS Quarterly, 13 (1), 1989, pp. 3±18. [46] P. Weill, The relationship between investment in information technology and ®rm performance: a study of the valve manufacturing sector, Information Systems Research 3 (4), 1992, pp. 307±332. C. Sophie Lee is an Associate Professor of Information Systems in the Department of Information Systems, College of Business Administration, California State University at Long Beach. She received her PhD in Information Systems in 1995 and MBA in 1991 from the University of Texas at Austin. Her research interests include utilizing complementarity framework on information technology productivity, mass customization, electronic commerce, and customer relationship management. Her papers have appeared in journals such as Organization Science and Information Systems Research.