Accounting Software

Perhaps the most significant addition to contemporary accounting has been the introduction of sophisticated computer programs to assist in the accounting function.Since their widespread introduction in business and government organizations in the 1950s, the primary applications of computers have been in the areas of record keeping, bookkeeping, and transaction processing (Holstein, 2003, p. 17).

Commonly known as data processing, these applications automated the flow of paperwork, account for business transactions (such as order processing and inventory and shipping activities), and maintain orderly and accurate records.Today, while data processing is vital to most municipal governments, most of the work involved in the design of such systems does not require the methods of operations research.

In the 1960s, when computers were applied to the routine decision-making problems of managers, management information systems (MIS) emerged.These computer-assisted systems used the raw (generally historical) data from data-processing systems in order to prepare management summaries, to chart information on trends and cycles, and to monitor actual performance against plans or budgets (Holstein, 2003, p. 19).

More recently, decision support systems (DSS) have been created to help project and predict the results of decisions before they are made. These projections permit managers and analysts to evaluate the possible consequences of decisions and to try several alternatives on paper before committing valuable resources to actual programs.

The development of management information systems and decision support systems brought operations researchers and industrial engineers to the forefront of business planning. These computer-based systems require knowledge of an organization and its activities in addition to technical skills in computer programming and data handling.The fundamental issues of importance in MIS or DSS include how a system will be modeled, how the model of the system will be handled by the computer, what data will be used, how far into the future trends will be extrapolated, and so on. In much of this work, as well as in more traditional operations research modeling, simulation techniques have proved of significant value (Holstein, 2003, p. 20).

A well-known example of the application of AI is to control machinery.Brookshear (2000) says that in this area, traditional techniques are applicable when the machine performs its task in a controlled environment; however, a major difference develops when machines must perform autonomously, and resolving such problems is an ongoing pursuit within artificial intelligence research.“A natural goal of data storage and retrieval systems is to be able to request information from these systems by means of a natural language rather than requiring the human using the system to conform to a special and cumbersome technical query language (p. 477).

Finally, there is an important extension of AI into expert systems, which Brookshear (2000) describes as software packages that are designed to assist humans in situations in which an expert in a specific area is needed (p. 479).Based on the power of algorithmic processes themselves, the author shows how a universal programming language should be addressed.He states that, “If a future programmer finds that a problem cannot be solved using our language, then the reason will not be a fault of our language.Instead, it will be that there is not an algorithm for solving the problem.A programming language with this property is called a universal programming language” (p. 492).

According to Friedman and Hoffman (1995), despite the importance of the goal, however, the daunting array of incompatible databases that may be in place in any organization is as likely to inspire paralysis as enthusiasm for decision support system applications.Based on their experiences in implementing such systems, it is their recommendation that any such database should be used principally for analytic purposes. This is communicated in the statements, “Transactions and reporting requirements--as well as the responsibility to collect and vouch for the accuracy of the data--should remain the responsibility of the owners of each data source.Freedom from reporting requirements allows the relational database to remain a dynamic creation, changing with new priorities, responding to the changing needs of users, and inspiring ever-more--sophisticated approaches to leadership and to resolving important management questions” (p. 19).

In order to better understand capacity and utilization, financial managers need the ability to create business models which provide timely and relevant decision-making information which reflect the operational realities of the enterprise.Babbini (1999) emphasizes that the introduction of Activity Based Management (ABM) software with scenario playing capability that understands capacity and utilization issues is a real asset to many companies because this type of technology provides the significant benefit of providing budgeting and business decision making for all types of organizations.According to Babbini, ABM (as distinct from Activity Based Costing or ABC), comes from using predictive models of cost behavior which the author regards as a significant development beyond the historical, product costing emphasis of ABC.Babbini points to Jim Smith of the Marmon Group, an advocate of ABM in his organization, with about 60 companies using ABM at one level or another, has some insightful observations.Smith says that many operational managers tend to make critical decisions based on a mixture of “seat-of-the-pants” intuition and a mix of different information sources.However, the financial data with which they are most comfortable is actual cost history.Babbini notes that this perspective is obsolete because it is “so at odds with the future-based view of ABB” (Babbini, 1999, p. 52).

The biggest benefit of the strategic approach to budget development is that “what-if” scenarios can be developed to help managers visualize what will happen when numbers are changed or fine-tuned.McCarthy enthuses:“We can examine alternative strategies and total impact on the enterprise, before we made decisions.We can adjust the forecasts to reflect competitive reality, good or bad, and recalculate resource requirements and associated dollars.”

Miranda (2001) states that enterprise resource planning (ERP) systems can provide organizations with the knowledge to mange their core business processes such as financial control, operational management, analysis and reporting, and decision support.Its strategic enterprise management provides the capability to evaluate issues relative to:

• Process improvement – provides cost driver analysis and evaluation business processes for reengineering.
• Investment decision – provides resource allocation and investment decisions.

ERP is a relatively new software package that integrates traditional financial management applications such as accounting, budget control, accounts payable, and payroll with non-financial applications such as purchasing, inventory, and human resources through a common database standard (Miranda, 2001).It is commercial-off-the-shelf software that encompasses the enterprise and focuses on resources.The tasks provided by this software package include financial control, operational management, analysis and reporting and routine decision support.

According to Miranda (2001), ERP systems consist of software applications that provide organizations with the knowledge to manage their core business processes.These systems differ from previous generations accounting software because ERP relies on a common database for both financial and non-financial applications that is accessible on a real time basis.In addition, it enables organizations to redesign existing processes as they implement new software.

Miranda (2001) states that ERP systems generally have the following features:

Yi (2002) states that ERP’s provide two aspects that traditional systems do not.The first aspect is that it links standalone systems into an integrated whole in order to share information.For example, the procurement component can check to make sure that a purchase request has sufficient funds in the account to purchase the system.On the other hand, the human resource system is allowed to pull data from the budget component to assure that all positions are budgeted prior to hiring a new employee.Therefore, through an integrated system, public officials and managers can make more informed, timely, and accurate decisions based on a comprehensive view of the organization.

The second aspect is that ERP’s also link standalone departments.Government agencies have independent units that often work independent of other units.A local government redevelopment agency is an example of such an independent unit.Linking all component units of a government agency through ERP would be expected to provide managers with more centralized control over the various components through financial and process controls and uniform policies and procedures.

According to Yi (2002), ERP programs have both risks and concerns relative to its use.One concern is that it can be an expensive program to implement.The cost of implementation is generally separate from the software cost.A risk involved in the program is the amount of custom code built into the architecture.The more custom code, the more difficult and costly it is to maintain, operate, and upgrade.