Written Report IT 3

7/31/2019 Written Report IT 3

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In our life we encounter different problems. There are problems that arevery easy to solve and other problems take a little more time and effort.

Businesses have problems too, and they range from simple to complex,

from those easily dealt with to those that are insoluble. Analysts and businessmanagers take their time and effort on solving this diversity of problems.

In this chapter we will study problem-solving techniques and look at thesystematic approaches that analysts use in dealing with problems. The chapterdiscusses traditional and structured systems analysis techniques and how toapply the scientific method to solving business problems.

Cause and effect is the foundation of systems work. If a cause and effectrelationship exists, the cause will always generate the effect. This certaintyallows scientists, business managers, systems analysts and others to bring orderand structure out of chaos.

For many years businesses relied upon hunches, guesses, intuition, ortradition to guide them in . It was philosopher John Dewey whooutlined the steps of a logical approach for developing sound solutions problems.The is a procedure for solving problems that systematicallydeals with causes and effects, evaluating the results. It is useful for solving aproblem with the least expenditure of time and effort.

The scientific method of problem solving, an important part of thesystems analysts repertoire, is used to develop solutions for a wide range of information flow problems. Its major characteristics are:

1. Reproducibility of results . There is a good deal of assurance that procedures,operations, or tests carried out according to the scientific method will producethe same results each time they are performed.

2. Accuracy of results . Conclusions based on the application of factualknowledge, reproducible experiences, and intellectual proficiency rather thanon guesswork or chance, are more accurate.

3. Efficient expenditure of time and effort . Since procedures are executedlogically, there is more assurance that the activities of the systems analystswill achieve specified goals with the least effort.

4. Plan of action . The scientific method gives the systems analyst a reliable andtangible plan to follow when handling a complicated problem with manydiverse factors. It ensures that all relevant procedures, elements, and dataare considered and that none is omitted accidentally.


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5. Transferability of results . Because results obtained from the scientific methodare reproducible, the systems analyst can expect similar results to occur insimilar like situations without having to repeat the steps in the process, or toretest data.

The following is a list of the key aspects of the scientific method:

Precise statement of problem Careful attention to detail Objectivity in making observations Precision in analyzing data and reporting results Use of mathematics and statistical techniques Systematic, logical plan for solving problems Evaluation of results Readjustments of system to bring it more in line with objectives

Before we can solve a problem, if there is one, we must identify its causes. Inthis step, the systems analyst describes and isolates the factors pertinent to aparticular problem and tries to determine the causes. The analyst investigatesthe nature of the problem to decide if it is a unique situation, whether it isindicative of other problems, or whether it masks a deeper problem.

The problem cannot be solved if the wrong causes are attacked or the wrongsolution is implemented. If the problem is caused by inadequate keyboardingskills, rearranging the office furniture will not increase output. The real elementsof the problem must be identified before a solution can be found.


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In this case the systems analyst decides that the level of output from the dataentry department is below what can reasonably be expected.

The problem cannot be solved if the wrong causes are attacked or the wrongsolution is implemented. The real elements of the problem must be identifiedbefore a solution can be found.

The next step in the scientific method involves reducing the problem intoquantitative terms. It is done by transform observation in numbers so that itcould be easy to formulate result in the problem and solution are determined andmeasured.

For example: our variable is the volume of sales however during this past fewdays it decline through slow moving periods. But the person in-charge of suchsale measure it 11,500 pesos a day. There is amount involve so analyst canexpress it to quantitative terms.

In this phase, the systems analyst develops alternative solutions to the problemafter studying various methods of improving the situation. In selection a plan of


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action, the analyst uses if-then logic if a given solution is implemented thenthis will happen.If-then Logic

This phase may involve a considerable expenditure of time and money.Sometimes equipment vendors are called in, employees hired, training coursesdeveloped, new forms printed, computers installed, and so on. Patterns of

information flow may be changed and new procedures instituted or old onesaltered.

Probably the most important phase of the scientific method is evaluating theresults. In this step, the analyst determines whether the implementation solutionactually solved the problem and whether desired goals were reached.Few solutions produce perfect results the first time they are implemented. If theoriginal expectations were not met, the analyst must return to earlier steps in theproblem-solving procedure. He or she must repeat the activities of the steps,usually with some modifications, in an attempt to adjust the outcomes. Thisprocess of reentering the problem-solving loop at the point indicated by thecalled


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is the process of understanding how things influence oneanother within a whole. In nature, systems thinking examples includeecosystems in which various elements such as air, water, movement, plants, andanimals work together to survive or perish. In organizations, systems consist of people, structures, and processes that work together to make an organizationhealthy or unhealthy.

Systems Thinking has been defined as an approach to problem solving, byviewing "problems" as parts of an overall system, rather than reacting to specificpart, outcomes or events and potentially contributing to further developmentof unintended consequences . Systems thinking is not one thing but a set of habits or practices within a framework that is based on the belief thatthe component parts of a system can best be understood in the context of relationships with each other and with other systems, rather than in isolation.Systems thinking focuses on cyclical rather than linear cause and effect.

For many years system analyst applied the scientific method to problem solvingin a traditional way , defining the inputs and the outputs of a system anddescribing how the information would be processed. This could be a difficult andtime-consuming effort because it required spending many hours preparingflowcharts and writing lengthy textual descriptions of the information-handlingprocess. Flowcharts were major tool of the systems analyst for many years.This was unstructured way of describing steps in a solution. Virtually all problemswere perceived as being sequential and linear in nature. The traditional systemsanalysis methodology became inadequate, however, as businesses andorganizations overtook solving more complex and interrelated problems. The task of describing all inputs, outputs, processing steps, and contacts with vendors,customers, programmers managers and others, using only flowcharts and textualnarratives, was too difficult.

The new method for solving system problems and describing their solutions wasdeveloped by Larry Constantine, Edward Yourdon , Chris Gane , Trish Sarson andothers. This methodology, known as , replaced

lengthy textual descriptions with diagrams that substituted words for figures andflowlines for written narratives. Structured analysis enabled analysis to visualize asystem graphically, as an interrelated group of elements, rather than merely as asequence of steps. Thus it became possible to visualize an overall system and itsstructure in a clear form. Structured systems analysis has become the preferredmethod of analyzing and describing systems.
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, This method visualizes the overall system indiagram form.

For many years systems analysts applied the scientific method to problemsolving in a traditional way, defining the outputs of a system and describing howthe information would be processed. This could be a difficult and time-consumingeffort because it required spending many hours preparing flow charts and writing

lengthy textual descriptions of the information-handling process. Flow chartswere a major tool of the systems analyst for many years.This was an unstructured way of describing steps in a solution. Virtually allproblems were perceived as being sequential and linear in nature. The traditionalsystems analysis methodology became inadequate, however, as businesses andorganizations undertook solving more complex and interrelated problems. Thetask of describing all inputs, outputs, processing steps and contacts with vendors


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, customers, programmers, managers, and others, using only flowcharts andtextual narratives was too difficult.

Systems analysts have refined the scientific method into a logical strategy that

can be applied to many kinds of problems. The five phases are somewhatarbitrary and often overlap. Some analysts prefer to view the process as havingsix or more phases.

The Systems development life cycle (SDLC), or Software development process insystems engineering , information systems and software engineering , is a processof creating or altering information systems, and the modelsand methodologies that people use to develop these systems.

In software engineering the SDLC concept underpins many kinds of software development methodologies . These methodologies form the framework forplanning and controlling the creation of an information system: the software

development process .

The systems life cycle (SLC) is a methodology used to describe the process forbuilding information systems , intended to develop information systems in avery deliberate, structured and methodical way, reiterating each stage of the life cycle . The systems development life cycle, according to Elliott & Strachan & Radford (2004), "originated in the 1960's,to develop large scale
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functional business systems in an age of large scale business conglomerates .Information systems activities revolved around heavy data processing and number crunching routines".

Several systems development frameworks have been partly based on SDLC, suchas the structured systems analysis and design method (SSADM) produced for theUK government Office of Government Commerce in the 1980s. Ever since,according to Elliott (2004), "the traditional life cycle approaches to systemsdevelopment have been increasingly replaced with alternative approaches andframeworks, which attempted to overcome some of the inherent deficiencies of the traditional SDLC".

In the planning phase, analysts recognize, diagnose, and define the problem.During this phase, they may conduct a study to assess and overall scope of theproblem and determine whether more money and time should be expended insolving it. They prepare a plan of attack and select the individuals who will direct

a project or serve on a committee. This phase lays the groundwork for furtherstudy and the stages that will follow.

During the analysis phase, the analyst reviews data and information on the in-place-system. He or she takes measurements, conducts audits, gathersinformation, interviews individuals, samples work, and documents the kinds andtypes of information to be processed by the system. The objective is to clearly
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understand the present system, learn what is needed, and discover theshortcomings or faults that must be corrected or modified.

A new method for solving system problems and describing their solutionswas developed by Larry Constantine, Edward Yourdon, Chris Gane, Trish Sarson,and others. This methodology, known as , replacedlengthy textual descriptions with diagrams that substituted words for figures andflowlines for written narratives. Structured analysis enabled analysts to visualizea system graphically, as an interrelated group of elements, rather than merely asa sequence of steps. Thus, it became possible to visualize an overall system andits structure in a clearer form. Structured systems analysis has become thepreferred method of analyzing and describing systems.

The information gathered in the preceding phases allows the analyst to

put down on paper the elements of a new or improved system. In the designphase, the analyst identifies and considers alternatives. At some point, he or shewill select an alternative and conceive a design. During the design phase, inputand output records are prepared, forms laid out, and the file specificationswritten.

A major aspect of system design is the structure, organization, and formatof the information that will be contained in its database. Time and effort arespent in designing the database, specifying the content of records and files thatwill be included in it, and describing procedures for entering data and searching,updating, or querying the files.

The primary objective of the design phase is to create a design thatsatisfies the agreed application requirements. In the design phase the SDLCprocess continues to move from the "what" questions of the analysis phase tothe "how" questions.

The requirements prototype that was developed earlier during the analysisphase is gradually improved and extended to include all the specified functions of the application.

Also, the planning of the system documentation process should bestarted.


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In the development phase, the new system is actually built. The analystconcentrates on identifying vendors and suppliers who will be able to provide thenecessary equipment or facilities at a reasonable price. Equipment and machinesare ordered and set up, computer programs written or purchased, andcommunication lines leased and installed.

The last step of the cycle, the implementation phase, deals with thechangeover to a new or improved system. After the facilities have been installed,programs, software, and hardware must be tested to ensure that they meetdesign specifications. Final changes and modifications are incorporated in thenew system at this stage. The objective is to optimize and fine-tune the system.During this final step, systems documentation, which was begun early on, iscompleted and reports, paperwork and diagrams are prepared describing thesystem now in place.

In practice, the analyst may repeat one or more of the previous steps.Through a repeated series of problem-solving efforts, he or she will reach thegoal of designing and engineering a better system.

The waterfall model is a sequential design process, often used in software development processes , in which progress is seen as flowing steadily downwards
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(like a waterfall ) through the phases of Conception, Initiation, Analysis , Design ,Construction, Testing , Production/Implementation and Maintenance .

The waterfall development model originates in the manufacturing andconstruction industries: highly structured physical environments in which after-the-fact changes are prohibitively costly, if not impossible. Since no formal

software development methodologies existed at the time, this hardware-orientedmodel was simply adapted for software development.

The first known presentation describing use of similar phases in softwareengineering was held by Herbert D. Benington at Symposium on advancedprogramming methods for digital computers on 29 June 1956. This presentationwas about the development of software for SAGE. In 1983 the paper wasrepublished with a foreword by Benington pointing out that the process was notin fact performed in strict top-down, but depended on a prototype.

Few people in the modern computing world would use a strict waterfall model for their systems development life cycle (SDLC) as many modernmethodologies have superseded this thinking. Some will argue that the SDLC nolonger applies to models like Agile computing, but it is still a term widely in usein technology circles. The SDLC practice has advantages in traditional models of software development that lends itself more to a structured environment. Thedisadvantages to using the SDLC methodology is when there is need for iterative
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development or (i.e. web development or e-commerce) where stakeholders needto review on a regular basis the software being designed. Instead of viewingSDLC from a strength or weakness perspective, it is far more important to takethe best practices from the SDLC model and apply it to whatever may be mostappropriate for the software being designed.

A comparison of the strengths and weaknesses of SDLC:

Control. Increased development time.

Monitor large projects. Increased development cost.

Detailed steps. Systems must be defined up front.

Evaluate costs and completiontargets. Rigidity.

Documentation. Hard to estimate costs, project overruns.

Well defined user input. User input is sometimes limited.

Ease of maintenance.

Development and design standards.

Tolerates changes in MIS staffing.


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Written Report IT 3