Influence of User Ability On The Quality of Accounting Information System
Organic Information Systems
1. Organic Information
Systems
A look at making IS scalable within a
growing information age
Kevin Hackett
Keiser University
Organizational Behavior MANG562G3
Dr. Thompson
4/17/2015
2. Value of IS
IS Value= IS Reward / Penalty of Change
IS Reward = Utility and Usefulness
Penalty of Change = Cost and Time
Directly from (Furukawa & Minami, 2013)
4. First Stage of IS
Lvl 2 Executive
Marketing
w/Internal IS
Sales
w/Internal IS
Accounting
w/Internal IS
Finance
w/Internal IS
Inventory
w/Internal IS
Lvl 2 Executive Lvl 2 Executive
Lvl 1 Executive
5. Second Stage of IS
Executive
Marketing Sales Accounting Finance Inventory
Executive Executive
IS/BI Tool
(Usually ERP)
6. Typical IS Growth Pattern
Top
Executives
Division Division
Marketing
Sales
Accounting
Finance
Inventory
ERP/IS/
BI
Division
Marketing
Sales
Accounting
Finance
Inventory
ERP/IS/
BI
Marketing
Sales
Accounting
Finance
Inventory
ERP/IS/
BI
7. Organic Stage of IS
Marketing
Sales
Accounting
IS
Finance
Inventory
Marketing
IS
Sales
IS
Accounting
Finance IS
Inventory IS
Executive
Executive IS
Department
Relevant
interfaces
Executive data
8. Organic IS Growth Model
Top
Executives
Division A Division C
Division B
IS Management*
Marketing
Sales
Accounting
Finance
Inventory
Marketing
Sales
Accounting
Finance
Inventory
Marketing
Sales
Accounting
Finance
Inventory
IS
IS
IS
IS
IS
IS
IS
IS
IS
IS
IS
IS
IS
IS
IS
IS
9. Challenges with the Organic Growth Model
Cost of IS solutions
Availability of IS solutions
Personnel Resources
Cost of migrating existing solutions
Data Security
Customizability
10. The Growing Pains Payoff
Increased ability to adopt change
Better data management at each level of the
organization
Reduced bottlenecks
Reduced risk of systemic failures
Technology as a competitive advantage
11. Resources
Albaum, G. (1967). Information flow and decentralized decision making in marketing. California Management Review (Pre-1986),
9(000004), 59. Retrieved from http://search.proquest.com/docview/206234865?accountid=35796
Ball, N. L. (2005). Information systems (IS) structure and its relationship to IS functional performance: Conceptual frameworks
and empirical tests (Order No. 3198072). Available from ABI/INFORM Complete; ProQuest Dissertations & Theses Full Text: The
Humanities and Social Sciences Collection. (305476859). Retrieved from
http://search.proquest.com/docview/305476859?accountid=35796
Erickson, J., & Siau, K. (2008). Web services, service-oriented computing, and service-oriented architecture: Separating hype from
reality. Journal of Database Management, 19(3), 42-54. Retrieved from
http://search.proquest.com/docview/199603079?accountid=35796
12. More Resources
Furukawa, M., & Minami, A. (2013). A study on the 'flexibility' of information systems (part 1): Why do they
need to be flexible?International Journal of Business and Management, 8(20), 48-61. Retrieved from
http://search.proquest.com/docview/1468444394?accountid=35796
Li, S., Huang, S., Yen, D. C., & Chang, C. (2007). Migrating legacy information systems to web services architecture.
Journal of Database Management, 18(4), 1-25. Retrieved from
http://search.proquest.com/docview/199608072?accountid=35796
Marchand, D. & Bechler, K. A., 1994, Digital Equipment Corporation International: Fitting Information
Technology Architecture to Competitive Restructuring.
Yoda, Y., & Yoshida, M. (2011). A CONSIDERATION IN DEVELOPING STRATEGIC INFORMATION SYSTEMS
THROUGHOUT BUSINESS TRANSFORMATION: A CASE STUDY OF SEIREN CO., LTD. Journal of International
Business Research, 10(2), 143-165. Retrieved from http://search.proquest.com/docview/912511320?accountid=35796
Editor's Notes
Long ago it was claimed that knowledge was power. Today, we’ve digitized knowledged and entered the Information Age where data is abundant. However, making the leap from data to knowledge requires some level of analysis and, to get the most out of it, it takes an information system (IS) designed to analyze more data than we could on our own.
As the amount of data we collect has grown, the stress on those information systems has caused an evolution. In this presentation we look at the reasons for the stress on IS teams and review the evolution of IS structures. Lastly, we’ll look at a new way to approach supporting company information systems that has the flexibility to grow with the organization in an affordable, scalable way.
The value of the information system is not only what information it can provide, but how much it costs to extract even more useful data. Furukawa and Minami, define the value of IS as a function of usefulness and ease of implementation over cost and time. In their equation, usefulness and ease of implementation define the reward of IS changes while cost and time reflect the penalty of change. If a IS solution is free, but doesn’t provide much use, it’s as worthless as a solution that is cost prohibitive. This is important for us in our evaluation of potential IS structural solutions. Does the new solution either decrease the penalty to change or does it increase the IS reward?
The advancement of information technology is rapid. It is hard for an old architecture to keep up with the changes in the current market. (Erickson & Siau, 2008). Traditional Models of the IS teams place a lot of pressure on IT and IS groups to facilitate the flow of information. As this figure depicts, each of the departments enter information into the IS, typically an ERP and expect sufficient value out of the system from which they can make decisions. As an organization grows more complex, the cost and time to make changes increases and the pressure on IS grows too quickly. The places the manager of IS in a difficult position (Furukawa & Minami, 2013).
The transformation of information systems has started with a ‘trickle-up’ method where each department provided a report to company executives who brought the pieces together for decision making (Albaum, G. 1967). Albaum (1967) noted this as a key challenge to departments like marketing which required an understanding of one or more departmental data in order to perform their jobs effectively. Not only does this model present a challenge to departments who would benefit from an exchange of information, it also doesn’t provide assurances that departments don’t doctor or filter their data prior to submitting reports to executives.
In the second evolution of the IS model, a sophisticated ERP provides customized views to each dependant party allowing the team to fully leverage the available data. This also provides executives with a comprehensive view of the organization that suits their decision making level.
This model is superior to the first because data is collected by the IS/BI/ERP tool. This eliminates the challenge of data being filtered and offers an intelligent computer system which can help make process and display the data in useful ways. Ball (2005) describes the value of IS performance in terms of IS organizational centralization, IS organizational formalization, IS services completeness, IS services centrality, IS process coordination, and IS technological integration. This research shows the thought process behind IS which understands the value drawn from data which is aggregated.
This is a popular model today which makes the good use of technology to aggregate and share data. Unfortunately, this model suffers from the stress it applies to the IS/IT professionals. As the organization grows more complex and even multinational, the complexity of the ERP becomes difficult to manage and the flexibility of an organization is reduced. Furukawa & Minami (2013) describe the flexibility as a key element in a business’s competitive advantage.
The typical growth pattern of Information systems uses the ERP to group company data and provide a comprehensive look at the division. This model can be seen as an extension of the second stage IS where IS is an aggregation tool for the information of each of the departments simply multiplied by the number of divisions to provide flexibility for growth. This model suffers from the aforementioned lack of flexibility due to multiple departments being managed by a single ERP. Due to the cost of integration, it’s nearly impossible to bring different business models into a single ERP, this naturally reverts to manual reporting to top level executives.
The third evolution of IS is organic. Instead of a typical horizontal structure with support groups. In this system, each department is now responsible for their own IS implementation. While an IS professional team can be utilized (or outsourced) to facilitate the implementation and maintenance of the IS, the responsibility of aggregating relevant information resides with the team in need of the information. This decentralization of IS, allows departments to remedy their own IS frustrations instead of depending on a backlogged IS team to solve it for them.
With the proliferation of web service offerings (WSOs) like Salesforce for salespeople, quickbooks online for accounting professionals and Marketo for marketing teams, the needs of individual departments are more easily met by web services that are specific to their needs. The benefit to this architecture is that it provides much more flexibility than a centralized ERP.
Each IS should also be evaluated for it’s ability to intelligently integrate specific information needed from other information systems. This reflects our need for the data to be easy integrated into existing models. Asynchronous technologies make it possible to make this data sharing happen and, often, in real time (Erickson & Siau, 2008). Many WSO architectures grow to support multiple instances of each department (different regions, divisions, etc.). This means the IS systems need to be robust enough to support multiple departments by offering services like distinct user accounts and visibility configurations.
The organic IS growth model shares the same organizational layout as the typical growth model, but features a different use of information systems. Made possible by the Service-Oriented Architecture (SOA), an organic IS structure has the ability to provide loosely integrated solutions across an organization (Erickson & Siau, 2008). The first difference is the distinct IS solutions used across the models, this allows each group to find the solution that suits their needs.
This approach presents an obvious problem of IS overhead. Instead of a single IS department managing the data, this model depicts additional IS personnel for each department. It should be clarified that this IS person does not need to be highly technical. The role of the department IS is to act as a liaison for the department’s IS needs. The more technically capable the liaison is or the more intuitive the web service is, the more quickly IS needs can be met. For needs that cannot be met by the liaison, technically proficient personnel can be found in the IS management group.
The dotted boxes around the same named department IS solutions indicate the possibility of shared resources. The accounting team from division A is likely to have needs similar the accounting team from division B. If they can use the same tools as one another, it would lower the cost and time of training and may yield some volume discounts. Reflecting on our equation for the value of IS, the reduction of cost and time is a huge benefit to the organization.
The biggest difference between this model and the old one however, is the IS management layer between the top level executives and the Divisions. This layer serves two purposes, first to support the IS department liaisons when data integration becomes too technical and second to communicate effective information practices to the divisions. This could include a special numbering system needed to uniquely identify the division or it could be training departments on effective new IS tools. The IS management division could also serve as a communicator for divisions with difficulty interacting with one another. Note that it is not the responsibility of this group to provide reports or manage the IS tools of the organization. Their job is to empower and support the IS liaisons. This would allow important information to be spread more easily throughout an organization.
Cost: Instead of using one large ERP, you may find the monthly costs of a web service to be high. Erickson & Siau (2008) also mention a number of studies which bring into question the return on SOA investment. Alternatives include developing your own web service or sacrificing the quality of the platform for a less expensive option.
Availability: While there are many WSOs for businesses out there, not all are robust enough for adoption and not all integrate as well with others. In these cases, it may be worthwhile to work with an existing vendor to make the software work for the department or develop one in-house. This problem will go away as more web services are being offered every day.
Personnel: The organic IS architecture shows a large number of people responsible for the IS network. This can be misleading because the fact is, today, everyone is an IS professional. We are no strangers to web services and industry professionals will readily know how to use the IS tool they are given. Only a small number of integration members are needed to setup the initial connections.
Migrating: Migrating existing solutions to any new platform can be costly and time consuming. This should also be a consideration when choosing the IS for your department. A good IS solution should allow you to extract all information easily. Li et al. (2007) describes a model called which extracts business processes from a dataflow diagram to determine whether it makes sense for a service to use WSOs, Once migrated, the benefits of flexibility, relevance and real-time information should make up the costs quickly.
Data Security: Several challenges that face data security when relying on web services include the possibility of data breaches on their systems, the possibility of the IS provider going bankrupt, and the risk of data transmissions being intercepted. While one could argue data breaches could happen to anyone, the idea of an organization disappearing overnight with your company’s data is unnerving. It’s important to establish partnerships with well established companies for critical data services.
Customizability: Using web services to support IS solutions presents a challenge when existing IS solutions follow industry standards and appear useful, but fail to meet the needs of the company. Yoda & Yoshida (2011) present this challenge as one reason to keep IS services in-house. Marchand & Bechler (1994) offer one possible solution by developing the services in-house and selling them to internal departments.
