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Running head: SYSTEMS DEVELOPMENT LIFE CYCLE 1 Systems Development Life Style: Predictive Models James Taubitz Grantham University

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systems development life cycle, the predictive model. Grantham University project paper.

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Page 1: Week 2, Ba649, Sdlc

Running head: SYSTEMS DEVELOPMENT LIFE CYCLE 1

Systems Development Life Style: Predictive Models

James Taubitz

Grantham University

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SYSTEMS DEVELOPMENT LIFE CYCLE 2

Abstract

Information Technology (IT) projects are particularly challenging due to the uncertainty of

what the final product is going to look like and the overabundance of competing standards,

capabilities and possibilities associated with these type of projects. A systems approach is one

way (and very popular way) to deal with how to tackle a large project. This paper discusses a

systems approach to viewing a project, and how the systems development life cycle can provide

a more complete view to project managers in the execution of a project to maximize successful

completion and minimize failure.

keywords: information technology, systems development life cycle, project management

process group, stakeholder, system, holistic,

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SYSTEMS DEVELOPMENT LIFE CYCLE 3

Systems Development Life Style: Predictive Models

Managing projects is a concept that most companies take very serious these days. Due to

numerous failures, increases in cost, excessive extensions in time, and various other factors that

result in difficulty (or total failure) to complete not only complex projects but also much simpler

ones, organizations are going back to school to understand how to best plan and execute a

project. Project failures can be attributed to many different problems and one area, that would

produce a multitude of mechanisms for failure, would be a project manager conducting a project

in his own little bubble without understanding how the organization or business, as a whole,

operates. Schwalbe (2014), stated, "To handle complex situations effectively, project managers

need to take a holistic view of a project and understand how it relates to the larger organization"

(p. 45). Why use this term "holistic"? The Merriam Webster Dictionary (n.d.) has defined

holistic as "relating to or concerned with wholes or with complete systems rather than with the

analysis of, treatment of, or dissection into parts". As you can see this is more of a medical use

for this word. However, if you think about an organization as a complex system that has many

components that must work together to make it operate efficiently, like the human body, you can

see how a systems approach to project management would result in a more complete, and whole,

view such that the conduct of the project will have less chance to leave out crucial components to

successful achievement. A systems development life cycle (SDLC) is the term with how good

project managers encapsulate the needs of all the project stakeholders. A project stakeholder is

meaning the organization as a whole as well as customers and others affected (either positively

or negatively) by the outcome of the project. Even further, these life cycles can be defined as

predictive, adaptive (agile) or extreme. We will discuss further the predictive life cycle

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SYSTEMS DEVELOPMENT LIFE CYCLE 4

management and show how this is a good means to manage a project that is, in the end,

"predictable".

Predictive Systems Development Life Cycles

The first SDLC is the waterfall model. According to Schwalbe (2014), the waterfall

model is one that "has well defined linear stages of systems analysis, design, construction, testing

and support" (p. 60). This cycle has all five project management process groups of initiating,

planning, executing, monitoring and controlling, and closing that all the other predictive (and

agile and extreme) models have. The main determinant in this life cycle is that no process

groups repeat themselves. In fact, Wysocki (2012), described this as a weakness in that

"knowledge gained from one process group, such as Launching [executing], cannot be used to

revise and improve the deliverables from a previously completed process group, such as Scoping

[initiating]. There is no going back to improve deliverables" (p. 42). This type of life cycle is

typically used where you generally know the end goal and the means to reach that goal.

The next predictive model is a modified version of the waterfall model, which is called

the spiral model. This life cycle is more attuned to software development projects. In fact, what

makes this more reasonable for an IT project management solution is the fact that change is

expected and planned for in the process. This change is not encouraged in the strict, linear,

waterfall cycle. The spiral approach "recognizes the fact that most software is developed using

an iterative or spiral approach rather than a linear approach. The project team is open to changes

and revisions later in the project life cycle, and returns to the requirements phase to more

carefully clarify and design the revisions" (Schwalbe, 2014, p. 60).

Another predictive version that is a bit more flexible is the incremental build life cycle.

Like the spiral model, change is expected and planned for such that what is learned on one phase

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SYSTEMS DEVELOPMENT LIFE CYCLE 5

can be applied to further refinement of the final project. The biggest difference here, from the

spiral model, is that a build (or incremental program solution) releases to the public or others.

Then, information is received from these users, testers or others, from that build, and that

information will be input into the next build cycle to achieve a final product (or next increment

of the program). For a business however, this model of "getting a partial solution into the market

is viewed as a way to get an early entry position and therefore create some leverage for

generating increased market share" (Wysocki, 2012, P. 43)

A model that requires a significant amount of user interface and input is the prototyping

life cycle. In an effort to clarify user requirements, prototypes are developed, users then tinker

with the program and report issues to the developers who in turn, "generate functional

requirements and physical design specifications simultaneously" (Schwalbe, 2014, p. 61).

Finally, the RAD life cycle (or Rapid Application Development) is similar to the

prototyping with the exception that RAD software is used to further develop new software and

provide prototypes for the end user to evaluate and provide feedback to the developer.

End Analysis of Predictive SDLC Models

While these are some of the predictive SDLC models, and there are more radical SDLC

models to use when the end-point is unknown, predictive models will get the project

management team to the end-point of a problem even if the solution was not readily apparent or

known. In IT projects, with the fierce competition all around, a project manager may decide to

use a model more agile to get the product to the market and continue to refine it while making

money on the early release. Bottom line however is that all the predictive models include all the

project management process groups. A smart project manager, looking at the whole business as

a system, reaching out to clients and any other stakeholder affected by the project, will have a

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SYSTEMS DEVELOPMENT LIFE CYCLE 6

much better chance at successfully completing any project over someone who willy-nilly tries to

jump from initiating to the closing phase without proper thought at the whole system.

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References

Holistic. (n.d.). Merriam-Webster Dictionary online. Retrieved from http://www.merriam-

webster.com/dictionary/holistic

Schwalbe, K. (2014). Information Technology project management (7th ed.).

Boston, MA: Course Technology

Wysocki, R.K. (2012). Effective project management: Traditional, agile, extreme (6th ed.).

Indianapolis, IN: John Wiley & Sons