It is worth considering that the history of information systems is in the administration of messengers, pictures, letters, books, paper and spoken communications between organisations. This helps a modern day analyst to keep a perspective on the human processes in the implementation of new information systems. The latest technology will not make poor business plans succeed. However, gathering data, interpreting information and disseminating knowledge faster, more concisely and more accurately is of interest to organisations. According to MIT business school, modern IT projects involve a mixture of four different management objectives: cost reduction, better information, shared infrastructure and competitive advantage.
There are competing schools of thought on how data, information and knowledge processing systems can be modelled in order to maximise value, which raise a number of questions for managing IT projects... How do we model existing data, information and knowledge processing systems? What are their present costs and revenues? With uncertain outcomes, how can an analyst quantify marginal costs and revenues of a new system? Is a new systems project feasible? If a project is feasible, what development techniques maximise project value? What stages are there in development? What are the likely problems and benefits involved with each stage of the project? Who are the people involved? What are the critical success factors? What is the impact of new technology? What happens after installation?
A methodology which best investigates these unknowns is the systems analyst's chief business process. These pages, which are under development, attempt to explore this further, for educating customers, analysts and managers, and for reference.
An analyst's approach to systems theory
- Research and understand existing systems, both manual and automated. Use rich pictures, context diagrams, systems boundary diagrams.
- Identify areas where automation is possible. Use P&L, ROI, NPV analysis, operational costs and revenues figures for each identifiable system.
- Define requirements for automation. List the goals of the system.
- Develop a set of possible technical and business systems options.
- Define the details of the chosen option. Use OO design, Data Flow diagrams, Logical Data Structures. This defines the details of the architecture you will use.
- Prototype your code and test the system to make sure that you obtain the desired results.
- Implement the system.
- Monitor operations, maintain and support the system.
An analyst's approach to problem solving
- Research and understand the problem
- Verify that the benefits of solving the problem outweigh the costs
- Define the requirements for solving the problem
- Develop a set of possible solutions (alternatives)
- Define the details of the chosen solution
- Monitor to make sure that you obtain the desired results
- Decide which solution is best and make a recommendation
- Implement the solution
What's missing here?
The missing element in the above is identifying, examining, negotiating with and managing the stakeholders in the system. Who is everyone? See Business Analysis process