Information Systems Analysis and Design Practices


The design of systems and their analysis is a pivotal sphere of managerial knowledge that requires frequent updating due to the fast-paced nature of the flow of information. In the sphere of information systems (IS), system analysis and design are invaluable to project success because many endeavors require strategic organization and ordering of volumes of data, an impossible effort without some degree of classifying, layering, or structuring.

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In light of the pertinence of this topic to successful project decision-making in IS, the present report will synthesize best practices in systems analysis and design to provide updated knowledge and deepen understanding of the subject.


Many IS projects fail or contain flaws when they reach their final stages because of methodological, organizational, or mechanical errors, an outcome that can burden companies with tangible and intangible losses (Dwivedi et al., 2015). Creating a complex system frequently requires tracking a multitude of details that, unaddressed, have the potential to undermine the success of the whole endeavor. Besides, in the course of development, unanticipated issues may emerge that will also threaten the development team and parent organization with losses in terms of time or quality.

Furthermore, a variety of technical and cultural problems can pose an additional concern for modern decision-makers who work with large and diverse teams. These threats necessitate implementing review strategies and recommendations supported by academic knowledge and research to lead an IS project team to success.


  1. Always allocate sufficient time for planning. Tilley and Rosenblatt (2016) repeatedly emphasize the idea that inadequate planning is a source of major errors and failures, one reason why this early stage of project management should not be neglected. Although many problematic factors might emerge during the development stage, almost any project that incorporates systems design or analysis should place a high value on the planning stage. This focus, early on, will facilitate creating a framework for managing the overall development process and establish procedures for error management, saving time, money, and the emotional resources of the development team.
  2. Incorporate logical and physical design. These two constituents should also be present in an IS project when working with systems because all such projects require both a set of items to accomplish and instructions for specific parameters in element design. As evident from the case of Downtown! the company, the clarity, and uniformity granted by controlling for both how and what must be done can benefit project flow and automate certain processes (Tilley & Rosenblatt, 2016).
  3. Implement modeling and simulation to test assumptions. This recommendation is paramount for the majority of IS projects and accompanying systems design because these procedures are likely to increase data accuracy. Besides, modeling and simulation can identify certain flaws in the design and help eliminate them when the project has not yet reached the commencement stage (Saurabh, 2009). Such an approach offers the opportunity to economize in terms of time and resources. While the creation of a model or simulation is also likely to require team resources, this alternative is undoubtedly preferable to financial losses resulting from the implementation of an untested solution.
  4. Solve major problems by splitting them into components. The relevance of a reductionist approach to IS project management is derived from its reliability in locating the sources of problems in complex systems and helping to identify solutions. This methodology may also be incredibly efficient in reinforcing understanding of a system’s functioning in the analysis of existing systems. However, as Saurabh (2009) points out, such a tactic might not be appropriate in some cases as it may not correlate properly to analyzing the relationships among constituents.
  5. View a system in dynamics. It is also critical to consider a project at different points in time to identify influencing factors. Such an approach lends itself to uncovering potential problems and has the prospect of enhancing the system’s resilience across its life span (Saurabh, 2009).
  6. Base assumptions on current knowledge. While the ability to accurately predict and anticipate is vital, using existing data and experience is a reliable way to take into account the body of previous experience. This recommendation could be invaluable to system designers because it motivates them to use another’s mistakes to avoid one’s own (Tilley & Rosenblatt, 2016). Humanity has designed an infinity of systems, each with its flaws and drawbacks, and it is essential to acquire as much accumulated knowledge on working practices as possible in the interest of achieving success.
  7. Understand the requirements and needs of the business. As many systems are designed for the proper and effective functioning of companies, it is important to study and account for the requirements of the recipient; a project that fails to consider those needs can become useless (Tilley & Rosenblatt, 2016). Proper analysis and consultation should be established before drafting a system to make sure it performs following the client’s needs and requirements to ensure satisfaction.
  8. Anticipate the user experience. It is also critical to include consideration for end-users as the system is ultimately intended to serve their convenience. Thus, it is essential to examine and carefully design ways for the system to manage inputs and outputs so that they are easy to navigate and comprehend (Tilley & Rosenblatt, 2016).
  9. Make decisions on observable variables. This recommendation is proposed by Saurabh (2009), who notes that using levels instead of flows as predictors of present and anticipated states makes it easier to manipulate and witness functionality at a particular time. Also, under such a decision-making paradigm, corrective actions will be more closely aligned with status problem-solving, helping to establish a more understandable and predictable error-correction system.
  10. Evaluate alternatives. Because a problem will often entertain a variety of solutions, it might be the case that the designed system is not ideal in the given circumstances (Tilley & Rosenblatt, 2016). In light of this, careful assessment of options can help managers find the most suitable decision, even if an ideal solution is not feasible. Also, the evaluation process helps build experience in systems design and analysis, which may increase the probability of success in subsequent projects.


The purpose of this report was to provide a synthesis of best practices to provide knowledge and promote a deeper understanding of systems design. Among the identified practices are incorporating an extended planning stage, implementing a logical and physical design, and employing modeling and simulations to decrease the possibility of major errors. Besides, managers should pay heed to user experience, system dynamics, and alternative solutions when working to create a sustainable project.

Managers should account for business needs and variables to be able to tailor a solution that delivers reliable results and meets expectations. Finally, managers should consider past mistakes, solve problems using current knowledge, and aim to simplify major complications to gain a better understanding of the issues involved.


Dwivedi, Y. K., Wastell, D., Laumer, S., Henriksen, H. Z., Myers, M. D., Bunker, D.,… Srivastava, S. C. (2015). Research on information systems failures and successes: Status update and future directions. Information Systems Frontiers, 17(1), 143-157.

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Saurabh, K. (2009). Systems engineering modeling and design. In A. Bajaj & S. Wrycza (Eds.), Systems analysis and design for advanced modeling methods: Best Practices (pp. 96-114). New York, NY: Hershey.

Tilley, S., & Rosenblatt, H. J. (2016). Systems analysis and design (11th ed.). New York, NY: Cengage Learning.

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