Mismanagement of organization-wide resources. Some argue that when organization-wide resources exceed a threshold amount, say 5 percent of the total operations budget, they should be con- trolled and monitored centrally. Information processing services (such as computer operations, pro- gramming, data conversion, and database management) represent a significant expenditure for many organizations. Those opposed to DDP argue that distributing responsibility for these resources will inevitably lead to their mismanagement and suboptimal utilization.
Hardware and software incompatibility. Distributing the responsibility for hardware and software purchases to user management can result in uncoordinated and poorly conceived decisions. Working inde- pendently, decision makers may settle on dissimilar and incompatible operating systems, technology plat- forms, spreadsheet programs, word processors, and database packages. Such hardware and software incompatibilities can degrade and disrupt communications between organizational units.
Redundant tasks. Autonomous systems development activities distributed throughout the firm can result in each user area reinventing the wheel. For example, application programs created by one user, which could be used with little or no change by others, will be redesigned from scratch rather than shared. Likewise,
data common to many users may be recreated for each IPU, resulting in a high level of data redundancy.
Consolidating incompatible activities. The distribution of the IT function to individual user areas results in the creation of many very small units that may not permit the necessary separation of incom- patible functions. For example, within a single IPU, the same person may program applications, per- form program maintenance, enter transaction data into the computer, and operate the computer equipment. This situation represents a fundamental violation of internal control.
Hiring qualified professionals. End-user managers may lack the knowledge to evaluate the techni- cal credentials and relevant experience of candidates applying for a position as a computer professional. Also, if the organizational unit into which a new employee is entering is small, the opportunity for per- sonal growth, continuing education, and promotion may be limited. For these reasons, IPU managers sometimes experience difficulty attracting highly qualified personnel, which increases the risk of pro- gramming errors and systems failures.
Lack of standards. Because of the distribution of responsibility in the DDP environment, standards
for developing and documenting systems, choosing programming languages, acquiring hardware and soft- ware, and evaluating performance may be unevenly applied or nonexistent. Opponents of DDP argue that the risks associated with the design and operation of a data processing system are made tolerable only if such standards are consistently applied. This requires that standards be imposed centrally.
ADVANTAGES OF DDP. The most commonly cited advantages of DDP are related to cost savings, increased user satisfaction, and improved operational efficiency. Specific issues are discussed in the following section.
Cost reductions. In the past, achieving economies of scale was the principal justification for the cen- tralized approach. The economics of data processing favored large, expensive, powerful computers. The wide variety of needs that such centralized systems had to satisfy called for computers that were highly generalized and employed complex operating systems.
Powerful yet inexpensive small-scale computer systems, which can cost-effectively perform specialized functions, have changed the economics of data processing dramatically. In addition, the unit cost of data storage, which was once the justification for consolidating data in a central location, is no longer the prime consideration. Moreover, the move to DDP can reduce costs in two other areas: (1) data can be entered and edited at the IPU, thus eliminating the centralized tasks of data conversion and data control; and
(2) application complexity can be reduced, which in turn reduces development and maintenance costs.