This chapter will provide you with an overview of the systems development process. First we describe in detail the traditional Systems Development Life Cycle (SDLC), encompassing the stages through which each system should pass, from the initial survey to hand-over of the completed system.
Pressure for rapid development and future maintainability of systems has resulted in a number of alternative approaches to systems development, ranging from development by end-users, to the incorporation of formal methods to improve the quality and efficiency of the development process.
Systems Development Life Cycle (SDLC)
Systems development could be seen as the simple process of writing programs to solve the needs of the user. Unfortunately the user knows what he wants but has no technical expertise while the programmer understands the computer but not the user environment. This communication gap between the customer and the service provider must be handled by an intermediary, the systems analyst. Broadly speaking therefore the systems analyst translates user’s needs into detailed specifications for implementation by the programmer.
Over the years the software manufacturing process has become more formalized:
The basic idea of the systems development life cycle is that there is a well defined process by which an application is conceived, developed and implemented. The life cycle gives structure to a creative process. In order to manage and control the development effort, it is necessary to know what should have been done, what has been done, and what has yet to be accomplished. The phases in the systems development life cycle provide a basis for management and control because they define segments of the workflow which can be identified for managerial purposes and specify the documents or other deliverables to be produced in each phase.—Davis and Olson, 1985.
The number of stages and names to describe those stages differ slightly between organizations; but the SDLC normally covers the activities shown in figure 1, each with a primary purpose.
The preliminary investigation is carried out to determine the scope and objectives of the new system and to investigate whether there is a feasible solution. New applications normally originate from end-user requests and are weighed against the other requests for IS resources before approval to develop the system is granted. At this stage an analyst or small project team is authorized to investigate the real potential of the new application. During this brief study the analyst must investigate the problem and the existing system sufficiently to be able to identify the true extent and purpose of the new application.
In order to ensure that the new system would be of greater benefit to the organization than other competing requests for proposals, a feasibility study must be performed covering the following three major areas:
- Economic feasibility to measure the costs and benefits of the new system.
- Technical feasibility to ensure that the organization has sufficient hardware, software and personnel resources to develop and support the proposed system.
- Operational feasibility, the willingness and ability of management, users and Information Systems staff in the organization to build and use the proposed system
Issues such as the size and complexity of the new system and the skills and availability of user and IS staff, will determine the level of potential risk to the organization in developing the system.
The output from this preliminary investigation is a statement of scope and objectives (often termed the project charter) together with a feasibility report. This document is submitted to management where a decision is made as to whether or not the development project should continue.
In this stage the analyst investigates the needs of the user and develops a conceptual solution to the problem. One human failing we all tend to exhibit is to rush into proposing solutions before we fully understand the problem we are trying to solve. It is therefore important for the analyst to develop a broad, conceptual solution to the problem (what needs to be done) prior to launching into the detailed physical design where we specify how the system will work.
In the past analysis tended to be very much a pragmatic affair with success more dependent on the experience and capabilities of the analyst than on any formalized approach. The analysis phase should include the following discrete steps:
- Understand how the existing system operates. This information can be obtained by observing people at work, interviewing users, and studying procedure manuals and other supporting documentation, questionnaires and visits to other organizations.
- Document the current physical system. A major problem in the past was how to record all the detail about the system. Most of it could be found only in the analyst’s head or draft notes. Here the basic tools of structured systems analysis such as the data flow diagram (DFD), the entity relationship diagram (ERD) and data dictionary (DD) can be used to represent graphically and record the data and procedures. We will discuss these later in the chapter.
- Define the problem areas. These may include such issues as poor response times in the existing system, poor presentation of current information, high costs or weak controls in the current system, waste and sometimes duplication.
- Identify new requirements. The analyst must attempt to identify new user requirements and look for new and improved procedures that can be incorporated into the system.
- Identify possible solutions. Having derived objectives for the new system from the previous stage, the analyst now develops a conceptual model of the new system in conjunction with the user. This may involve the investigation of alternative physical designs, such as whether to remain with the existing manual system, or to choose a centralized or decentralized approach to the application.
- The culmination of the analysis stage is the preparation of the formal user requirement specification (URS) that incorporates a logical model of a system that will meet the user’s requirements. A large proportion of the functional description and data specifications is best communicated from the analysis stage to the design stage through the graphic and electronic output from the structured tools used in the analysis process (data flow diagrams, entity relationship models, decision trees and the data dictionary).
- Again management is required to review the status of the project and to make its go/no-go decision.
The analysis stage of the SDLC has clearly identified what must be done in order to meet the user’s requirements. One important decision that must be taken at this point is whether to “make or buy” the new software application. In the past, most large organizations developed their own applications as no two organizations were exactly alike, and they could afford the investment in systems developed around their user’s needs.
Today the picture is changing as custom-built software is becoming very expensive to develop and even more so to maintain. Computer applications are large, complex and integrated and many businesses have become non-competitive because of their inability to develop systems that adequately support their business activities.
On the reverse side, packages (pre-written software applications) are becoming more common and can be customized to meet the needs of each organization. With major benefits in terms of speed of installation, cost, low maintenance and low risk, more and more companies are switching to packaged applications software. It is at this stage in the SDLC that the “make or buy” decision must be taken. We have analyzed our user’s requirements and can use these as selection criteria in searching for an appropriate package to purchase and install. Where there is no suitable package available we can still look to other innovative ways of obtaining the software, such as hiring contract staff or appointing a software house to build the system for us. Purchasing pre-written software will obviously mean the detailed systems design, coding and testing phases of the project are bypassed, depending on the need for customization of the final system. In later courses we will look at the package selection process in more detail.
The objective of the design stage is to determine exactly how the new system will work, and to communicate this information in a document referred to as the detailed systems specification. If we take the analogy of an architect building a house, in the analysis stage he has determined the feasibility of the project and identified the owner’s requirements in terms of the positioning of the house on the plot, size and architectural style, number of rooms and so on. The architect may even have built a small model to demonstrate the look and feel of the new dwelling. Once the owner is happy that the proposed house meets his requirements, the architect must communicate the detailed design to the builders. This would entail the drawing of a detailed plan of the house, specifying exactly how every part of the building is constructed and defining dimensions, materials, construction techniques etc.
We need to go through the same process when designing computer systems. This includes the design of:
- the technical platform on which the software will run. The new application may need new hardware, operating systems software and network connections
- output reports and enquiry screens
- input forms and data capture procedures
- physical file and database layouts
- description of the workings of each program module
- new clerical processes and procedures that will be required to interface with the new system.
Whereas in the analysis stage the emphasis was on identifying the user’s needs with little concern for the way the computer would be used, the design stage also requires user involvement for the approval of detailed design, but the physical constraints imposed by the computer are also of major importance. Gane and Sarson  define the objectives of structured design as follows:
The most important objective of design, of course, is to deliver the functions required by the user. If the logical model calls for the production of pay cheques and the design does not produce pay cheques, or does not produce them correctly, then the design is a failure. But given that many correct designs are possible, there are three main objectives which the designer has to bear in mind while evolving and evaluating a design:
- Performance. How fast the design will be able to do the user’s work given a particular hardware resource.
- Control. The extent to which the design is secure against human errors, machine malfunction, or deliberate mischief.
- Changeability. The ease with which the design allows the system to be changed to, for example, meet the user’s needs to have different transaction types processed.
The output from systems design is a detailed design specification incorporating technical, input, output, data and process specifications. In the past, much of the information was communicated in written form which was difficult to understand and often ambiguous. Imagine the builder having to construct a house from a written description. Like the output from analysis we have a number of innovative tools to help users and developers understand and communicate the workings of the system. These include data models and data dictionaries, screen and report layouts, structure charts and pseudo-code. We will look at most of these later in this chapter.
In this stage we program the new system. If the system has been purchased “off-the shelf, this phase would consist of the customization of the system. The success of the implementation stage is heavily reliant on the previous stages. If the analysis stage was poorly enacted, the system may not be what the user requires. Poor design will make it difficult for the programmer to construct the system, and it may be inefficient and difficult to maintain.
However, if the required effort and expertise is invested in analysis and design, there will be a precise specification of what to build available to the IS programmers and technical staff.
Unlike the previous stages, the programming stage can be undertaken as a number of separate tasks, performed in parallel. Programmers can code, data base administrators set up the database, hardware suppliers install and test networks and equipment, and we can begin to train the end-users to prepare them for the implementation phase. With so much happening, and with the need for some tasks to be completed before others begin, the analyst must develop a detailed project implementation plan to ensure tasks are scheduled and delays are quickly identified and addressed. Programming includes the following steps:
- database construction
- program coding and testing
- systems testing to check the system can handle expected loads and meets physical performance criteria
- finalise manual procedures
This entails the transition of the completed system into the operational environment, and includes the following tasks (some of which will already have been started in earlier phases):
- installation and testing of any new hardware, systems software and network infrastructure
- train users and operations staff
- transfer data (data conversion)from the manual or old system to the new database where necessary
- perform acceptance testing. This requires careful planning to ensure all data flows, error procedures, interfaces, controls and manual procedures are tested
- complete project documentation
The change over carries some risk, as failure of the new system may result in the organization being unable to do business, There are a number of approaches to converting from the old system to the new. The least risky is to run the new system in parallel with the old until the new system is stable. There is obviously a cost to running both systems. Another approach is to convert one part of the organization at a time (for example one branch office at a time). This method (known as the pilot method) reduces risk and allows the development team to focus on one area. This approach can cause some integration problems as part of the organization is running on the old system and part on the new. A similar approach is the phased implementation method where organizations convert to a large system one step at a time. For example they may start with the stock system, then implement debtors and finally the order entry system. Some organizations use the big bang approach and just switch over from the old to the new system. This option is obviously high risk as there is no system to fall back on in an emergency.
When the new system has been in operation for a few months, a post-implementation audit should be carried out. This audit must ascertain whether the project has achieved the initial objectives specified in terms of:
- meeting initial scope and objectives
- anticipated costs and benefits to the organization
- user satisfaction with the new system
- performance (response/turnaround time, reliability)
- adherence to standards
- quality of final product
- project performance in terms of cost and time.
This exercise will help to highlight problems that require maintenance of the new system and provide valuable feedback to IS management and project teams to assist in future development exercises.
Finally resources will be required to maintain and enhance the system over its operational life which can vary between 4 and 10 years. There is normally a formal hand-over of the system from the project team to the maintenance team. This will ensure that there is a defined time when the project is completed and that all the required documentation is produced. There are many systems in existence that are still supported by the original developer; and all knowledge of the system exists only in that individual’s head. The problem is that when this person leaves (or worse gets run over by a bus), there is no one with any knowledge of the system and the organization is at risk.
Research has shown that this is the most expensive stage of the life cycle as program bugs (as a result of poor design or bad coding and testing) or enhancements (poor analysis of user’s requirements or changes to the business) require continual analysis and programming effort.
The following table summarizes the important tasks in the six stages of the SDLC and highlights the main deliverables from each task.
|Preliminary Investigation||Problem Definition Scope and Objectives Data Gathering Risk Assessment Feasibility Analysis||Project Charter Feasibility Study|
|Systems Analysis||Data Gathering Systems Modeling User Requirements Definition||User Requirements Specification|
|Systems Design||Make or Buy Decision Physical Systems Design Technical Design||Detailed Systems Specification|
|Systems Build||Programming and testing Platform Implementation||Production System|
|Systems Implementation||User Training Data Conversion Systems Conversion Post-Implementation Review||Live System|
|Systems Maintenance||Fix system “bugs” System enhancement||Working System|
Development of Structured Methodologies
New and innovative systems development techniques are frequently proposed by researchers and practitioners and, over time, these formal methods have replaced the traditional pragmatic approach to developing computer systems.
In the 1960’s, the major concern in IS development environments was the efficient utilization of expensive computer hardware. Programs were written in low level languages with little or no support documentation and, over time, the code became almost impossible for maintenance programmers to understand and fix. So arose the need to introduce a set of standard rules and procedures for writing programs, often referred to as structured programming. Some of the key techniques in the structured programming approach include:
- a limited set of simple control structures (to control branching and looping)
- standard naming conventions for data and procedures
- self documenting programs.
Structured programming techniques ensured that programs were easier to write and test and much easier to maintain.
In the mid 1970s the focus in systems development moved from program coding to systems design. Computer applications were becoming more complex with the introduction of large on-line, integrated systems.
IS researchers, and in particular Larry Constantine, studied the problems of program size and complexity, and determined that, as a problem grew in size, so there was a more than proportional growth in the complexity of the problem and therefore in programming time. He advocated that all systems should be made up of small modules each no longer than fifty lines of program code.
Fragmenting a problem into a number of modules can be done in many ways; and he urged that the best technique would be to segment the program by function (task) with each module being as functionally independent of other modules as possible. This would ensure that changes to one program module were unlikely to affect other modules.
This technique was known as structured design; and a graphical representation of the modules and their relationships known as a structure chart, was developed to assist in the process.
In the late 1970s the focus in systems development moved again, this time to the analysis stage. IS professionals had formalized the design and coding of computer software but had neglected the most important development issue – what are the user’s real requirements. Written specifications were the main source of communication throughout the project. In the same way that architects would never attempt to describe a building in a letter, so analysts needed tools and techniques which could be used to define and communicate the user’s requirements to the systems design stage. These structured tools and techniques included:
- Data Flow Diagrams (DFD). These diagrams are used to show how data flows between the various processes in the system. DFD’s are an excellent communication tool as they are simple enough for users to understand and yet detailed enough to form the basis for the systems design process. A number of DFD techniques has been developed since the original work was published by Tom De Marco in 1978. However, they all basically perform the same task. Data flow diagrams are one of the most used and popular IS charting techniques.
- Entity Relationship Diagrams (ERD). Entity relationship diagrams identify the major objects about which data is stored and chart their interrelationship. Like most formal techniques, its major value is that it forces the analyst into a structured and detailed investigation of all the data used in the system.
- Decision Trees and Pseudo-code. These tools enable the analyst to express process logic clearly and unambiguously. In the detailed analysis of an information system, the analyst often has to describe a logical process that the future system will have to perform. Examples of these could be the way that a personnel system calculates pension benefits for employees or a sales system calculates sales commissions. Decision trees are diagrammatic representations of the process logic, showing the conditions that need to be tested and the resulting activities in a simple tree-like structure. Pseudo-code can be described as “structured English”. It permits the analyst to define process logic using English language couched in the logical structures inherent in program code. In reality it eliminates the verbosity and ambiguity from the English narrative.
- Project Dictionary. This tool enables the analyst to capture and catalogue the entire system specification on computer with the obvious advantages in reporting, cross-referencing and updating. In a database environment, data is no longer the property of each individual application but managed centrally as a corporate resource. Vast amounts of information about this data needs to be maintained, for example field names, types and lengths, validation rules, data structures and relationships. As systems move from the development to production environment, this data about data is transferred from the project dictionary into a production data dictionary to enable the database administrator (DBA) to build and maintain the corporate database.
As we will discuss later, most of the new computer assisted software engineering (CASE) tools are now built up round a project dictionary.
Alternative approaches to developing systems
Over the past 40 years, efforts have been made to improve the quality of new systems and to reduce the time and effort expended in their development. The following section provides an overview of some of the significant tools and techniques developed for this purpose.
One technique that has been incorporated successfully into the SDLC is prototyping. As the name suggests a prototype is a mock-up or model of a system for review purposes.
Looking at the traditional SDLC, one of the major problems is that the user is asked to provide detailed requirements prior to the system being built. Once a system is implemented he may find flaws in his original requirements or may see the possibilities of a new and improved approach.
For applications such as general ledger and payroll, the requirements are normally well understood (and usually standardized enough to suggest the use of packages) but many other areas such as personnel are unstructured and would benefit from the prototyping stage.
The two main approaches to the use of prototypes in the SDLC are:
- discovery prototyping where the analyst builds a skeleton of the final product in the analysis stage of the project in order that the user may better understand the workings of the final system. This prototype is normally built with a fourth generation language and while it is likely to include mock-ups of screens and reports, it is seldom a fully working model. The building and refining of the prototype is an iterative process between analyst and user and stimulates discussion on the functionality of the final product. Once the analyst and user are happy that the system’s requirements have been identified, detailed requirement specifications are developed and the prototype is no longer required. In some instances the prototype may serve as the specification.
- evolutionary prototyping where a working model is built with the intention of later refining it into the operational system. While this technique would appear to have great advantages in terms of productivity, the original prototype is often thrown together and not properly designed.
Prototyping can offer IS developers many advantages in that it assists in clarifying user’s requirements, improves user communication and commitment, should improve the functionality and quality of the user interface and will assist in identifying problems earlier in the development life cycle.
Where prototyping can be problematic is that it raises the user’s expectations that systems are quick to build and changes are easy. In addition there is a lack of experienced prototypers and quality prototyping tools.
Joint Application Development (JAD)
One major problem in systems development projects is the lack of real communication, understanding and consensus between users, management and the development team. Instead of the traditional one on one interviews spread over weeks and often months, the JAD approach involves a series of highly structured workshops where stakeholders focus on any one of the planning, analysis, design and implementation stages of the life cycle. One obvious advantage of this approach is a reduction in the time it takes to develop systems. However the real benefits of JAD come from better user requirements through improved communication and conflict resolution. Successful JAD sessions often depend on the competence of the session leader (termed the facilitator), the scribe (who is responsible for documenting the output from the sessions), strong top management support and a mix of participants with expertise and responsibility for the area under discussion.
Computer Assisted Software Engineering (CASE)
There is a famous saying, “The cobblers children have no shoes.” and this is very relevant to IS. Here we have a classic example of a group of IS professionals, dedicated to computerizing the organization in which they work, while developing these computer systems via manual means.
CASE environments attempt to address this problem by offering a set of integrated electronic tools for use in the SDLC. During the first phase of system development, CASE products provide the analyst with computerized tools to complete and document the analysis and detailed design stages of the development project by graphically modeling the data requirements and the business process flows that the intended application has to address. These models attempt to give a visual representation of a part of the business operations, following one of many modeling standards. The resultant application model is then used as a blueprint for the actual implementation in computer code. The tools that are geared specifically for this modeling phase are referred to as upper-CASE or JJ-CASE tools.
Lower-CASE tools specialize in the second phase of system development: the actual generation of executable applications or advanced prototypes. This is typically achieved through the use of a generic application generator, although CASE tools tend to be independent of any specific database management system.
Integrated or I-CASE aims to automate both phases i.e. a combination of upper and lower-CASE tools in one single package.
Most CASE environments use an electronic project dictionary as a repository and can include:
- graphic tools for charting diagrams such as DFD’s, ERD’s and Structure charts
- 4th generation languages or application generators to assist with prototyping
- data dictionary facilities to record and maintain data about data, processes and other system details
- quality control facilities to check specifications and code for correctness
- code generators to reduce programming effort
- spreadsheet models to assist with cost/benefit analysis
- project management tools to plan, monitor and control the development cycle.
- When CASE environments were originally developed in the mid 1980s, IS managers viewed them as a possible “silver bullet” to resolve the growing demand for computer systems. The promise of CASE was better quality systems, reduced development time, enforced standards and improved documentation.
As yet CASE tools have failed to make a major impact. CASE environments are complex, the cost of implementing CASE is high (both in terms of the CASE software and analyst training) and many organizations are looking to other solutions (packages and object orientation) to resolve their applications backlog.
Object Oriented Development (OOD)
Using the traditional development approach where the analyst designs procedures focused on the user’s requirements can result in systems that are costly to develop and inflexible in nature. The object oriented approach attempts to build components (objects) that model the behavior of persons, places, things or concepts that exist in the real world and then to build systems from these components. We do not design and build unique systems for motor cars or televisions; they are mostly built up from a set of common, interchangeable components. Even when components are unique they are very similar to other components. In the same way we can construct computer systems from building blocks reusing objects from other systems, making modifications to similar objects or obtaining objects from commercial component libraries.
The OOD paradigm is only now gaining momentum in the market place and most programming languages and methodologies do not support 00 development. One exception is Small Talk, the language credited with pioneering the OOP (object oriented programming) concept. Today many of the popular programming languages are appearing with 00 versions (for example Pascal, C++, Visual Basic and even COBOL).
Other development tools
The above-mentioned new programming approaches were not the only attempts to improve developer productivity. The following presents some other development tools and approaches. Note that, since distinctions between the categories cannot always be perfect, some tools could be classified in more than one category.
- Visual programming tools. The power of graphical user interfaces and object-orientation has spawned a number of high-level front-ends or shells to enable non-programmers to generate their own straightforward applications. These visual programming tools allow for the construction of applications by selecting, connecting, copying and arranging programming objects. For simple applications, there is no need for any code to be written at all since all required objects can be copied from a large library with all commonly used, pre-configured objects and their associated standard methods.
- Report generators are generally associated with database management systems and allow users to create ad-hoc, customized reports using the data in the database by specifying the various selection criteria and the desired report layout.
- Application generators consist of standard building blocks that can be combined or customized to create the required systems. The user specifies the inputs, the output requirements and the various data validations and transformations. Screen and report painters allow on-line, visual layout of input and output modules. Generally, these generators are supported by a comprehensive database management system that integrates the data dictionary, graphics and reporting modules as well as other utilities such as data and process modeling, security facilities, decision support modules and query-by-example (QBE) languages.
- Logic programming for knowledge based systems. Programmers quickly discovered that conventional programming languages were inadequate to develop advanced knowledge-based applications, such as expert systems and other artificial intelligence systems. These systems require reasoning capabilities and have knowledge representation requirements that are difficult to implement using procedural languages. This led to the development of logic programming languages such as LISP and Prolog. The use of these languages is generally confined to researchers and scientists. Today, a number of shells has been developed that allow the automatic generation of straight-forward knowledge-based systems.
- End-user applications. Today’s end-user productivity applications have extensive programming capabilities and allow for customization by means of macros (pre-recorded sequences of commands, keystrokes) and formulae. A spreadsheet is essentially a model developed by an end-user whereby the equations (or data transformations) have been programmed by means of formulae. Many of these formulae look similar to the statements in programming languages. The following statement would calculate someone’s weekly wages taking into account an overtime rate of 50%, using Microsoft Excel or Access.
– IF ( hours > 42 , hours * wage , 42 * wage + ( 1.5 * wage ) * ( hours – 42 ))
Critical success factors
Regardless of the development approach that may be used, a number of factors have been identified that are critical to ensuring the success of a systems development project:
- well-defined system objectives
- careful test of feasibility
- top management support
- user involvement to ensure strong commitment
- rigorous analysis to ensure detailed, unambiguous user requirements
- sound detailed design to ensure an efficient, quality, maintainable system
- project management to ensure the development team is managed and controlled.
South African Perspective
Research by a group of Scandinavian computer scientists has suggested that prototyping is better suited than the traditional SDLC to systems development projects undertaken in developing countries. Although the SDLC provides a rigorous development methodology intended to generate clearly defined system requirements, it does not take into account problems resulting from social and cultural factors. These include the uncertain availability of technical skills, user anxiety about technology, and the need for adaptability of the final product to differing local conditions. A further dimension to this approach is the need to train users in basic computer literacy skills and to inform them about the business role of IS before any attempt is made to elicit system requirements. Once workers have been empowered in this way, they are able to provide more valuable participation in the development of a system. Developers must also see the project as a mutual learning experience, since they need to understand how future changes in the business environment may affect system requirements.
Beyond the Basics
Web pages can contain multimedia effects and interactive capabilities, and the development of web pages involves using a variety of special components. Among the jargon and acronyms that you may encounter are the following:
- Hypertext Markup Language (HTML) is not actually a programming language, but has specific rules for defining the formatting of text, graphics, video and audio on a web page. Tags are used to indicate how a page should be displayed on your screen, and the details underlying links to other web pages.
- Interactive elements such as scrolling messages, pop-up windows and animated graphics are controlled by small programs, generally scripts, applets or ActiveX controls. Basically, a script is an interpreted program that runs on the client computer, as opposed to an applet, which is a compiled program running on the client computer. ActiveX controls are object-oriented technologies that allow components on a network to communicate with one another.
- Web pages created using dynamic HTML can automatically update their content on the client’s machine, without having to access the web server, making them more responsive to user interaction. Extensible HTML (XHTML) uses XML technology to display web pages on different types of display devices, while wireless markup language (WML) supports browsing on PDAs and cellular telephones. Finally wireless application protocol (WAP) specifies how wireless devices such as cellular telephones communicate with the Web.
Stages of the SDLC
Read the following article, and then briefly explain, for each stage of the SDLC, which of the standard activities appear to have been omitted or not completed when developing the system, and what effect this had on the quality of the final product.
From: Machlis, S. “U.S. Agency Puts $71m System on Ice”, Computerworld, 12 May 1997.
The U.S Agency for International Development (AID) last week confirmed that it suspended overseas use of a new computer system plagued by integration snafus, data transmission bottlenecks, and response times so slow that employee efficiency suffered. For now, 39 field sites will go back to using the agency’s old system for core accounting services and procurement contracts while problems with the Washington-based computers are ironed out. “We need to get the core functionality established”, said Richard McCall, AID’s chief of staff.
The New Management System (NMS), budgeted at $71 million, has been under fire since it was deployed in October of 1997. The AID inspector general’s office criticized NMS for data errors and slow performance. In some cases, users had to spend days trying to process a single transaction.
The new system can’t handle the large amount of data that passes among AID offices, McCall said. The agency must decide whether to boost expensive satellite network bandwidth to handle real time transactions or move to some batch processing. “I don’t think people understood the amount of data that would be transmitted over the system”, he said.
Designers also initially failed to gasp the difficulty of integrating legacy accounting systems. “We thought we had three primary accounting systems,” McCall said. But numerous infield alterations to basic systems over the years meant the agency had closer to 80 different accounting systems. Some of the resulting data didn’t import correctly into the new system.
In addition, McCall said, system designers should have stayed focused on core requirements instead of trying to immediately add features that users requested after early tests. For example, some overseas employees wanted to be able to call up data from any foreign site. Although that is an attractive feature, he said, “that taxes the system. You don’t really need that now.”
Four different methods have been described for the conversion to a new system: the parallel, pilot, phased or “big bang” approach. Compare these four alternatives in terms of the likely time frame involved, level of risk incurred, and user “buy-in” to the new system.