STIDK1013 Article Review Sample: TQM, Quality Data and MIS (UUM Individual Assignment 1)
For information and reference only – not to be submitted as your own work. This model extract shows how a strong STIDK1013 article review can be structured and argued. Use it to understand the approach, then write your own review in your own words, following your lecturer’s instructions and Universiti Utara Malaysia’s academic integrity rules. Your course includes a hands-on quiz that checks you understand your own review.
The brief this sample follows
This sample follows Individual Assignment 1 (10%) of STIDK1013 Information System in Organization at Universiti Utara Malaysia. Students write two article reviews, each a maximum of two pages, double-spaced, in font 12. Each review earns 4%: 2% for the critical article review and 2% for your own idea. A 2% hands-on quiz then tests whether you understood what you wrote.
You can read the full brief on our STIDK1013 Information System in Organization assignment brief page. For a step-by-step explanation of how to plan both reviews, see our full guide to the STIDK1013 article review.
How this sample is organised
| Part of the review | Rubric link | Target length (double-spaced) | What it must do |
|---|---|---|---|
| A. Critical article review | 2% per review | About 1 page (roughly 250 words) | State the article’s argument, judge its strengths and limits, and connect it to MIS |
| B. Self own idea | 2% per review | About 1 page (roughly 250 words) | Answer the brief’s question in your own voice, supported by a relevant case |
| References | Not marked separately | Short list | Harvard style, only sources you actually used |
Model extract – Article Review 1: TQM and Quality Data
A. Critical article review
Kang (2011) contrasts two research frameworks drawn from Deming’s thinking. An enumerative study describes the size of a problem and the variables that seem to move with it, usually through tests such as the t-test or chi-square. An analytic study asks why the problem happens, and Kang argues that Statistical Process Control (SPC) is the tool that answers that question.
The article’s main strength is its clarity about purpose. Kang shows that a correlation found in an enumerative survey does not prove cause, so managers who act on it may “fix” the wrong thing. This echoes Deming’s (1986) warning that most variation comes from the system, not from individual workers.
The paper is weaker on application. It explains the two frameworks in theory but gives little worked evidence from an organisation, and it does not discuss how data are captured in the first place. That gap matters for MIS, because SPC is only as reliable as the transaction data feeding it.
From an MIS perspective, the article suggests that information systems should not stop at descriptive reports. A dashboard showing last month’s defect rate is enumerative. A system that charts the same rate over time, with control limits, becomes analytic, because it separates common-cause noise from special-cause signals that need action (Deming, 1986; Laudon and Laudon, 2022).
B. Self own idea
In my view, quality theory improves MIS in three practical ways. First, it changes what the system reports: control charts and trend views help managers ask “why”, not just “how much”. Second, it raises the standard for the data itself. Wang and Strong (1996) show that users judge data quality on intrinsic, contextual, representational and accessibility dimensions, not on accuracy alone.
Third, it builds feedback into the system. Deming’s Plan-Do-Study-Act cycle fits naturally with an MIS that records a problem, tracks the change made and measures the result.
An illustrative case makes this concrete. Imagine a Malaysian food manufacturer whose MIS reports a rising number of customer complaints. An enumerative reading blames the night shift because complaints correlate with it. An analytic reading plots complaint data on a control chart, finds a special cause in one supplier’s batch, and the transaction records trace it to a single delivery date. The MIS has turned data into a decision.
The lesson for managers is simple. Investing in better reporting without improving data quality only produces faster, prettier errors.
Stuck on your own STIDK1013 review? Get one-to-one guidance from an information systems expert who can explain the articles, check your structure and help you prepare for the hands-on quiz. Submit your brief for a free quote.
Model extract – Article Review 2: Data Documentation and TPS (outline and opening)
The second review asks how data quality, normalisation and ISO documentation could improve MIS and TPS. A strong answer covers all three ideas, not just one. The table below shows how the two pages can be divided.
| Theme from the brief | Point to make | Supporting source |
|---|---|---|
| Data quality | A TPS records routine daily transactions, so errors at entry flow into every report above it | Laudon and Laudon (2022); Wang and Strong (1996) |
| Normalisation technique | Organising data into well-structured relations removes redundancy and update anomalies in transaction files | Codd (1970) |
| ISO documentation | Controlled, versioned documented information keeps procedures and records consistent and auditable | ISO 9001:2015, clause 7.5 (International Organization for Standardization, 2015) |
| Own idea and case | Link a filing or audit weakness to a TPS failure and show how documentation would prevent it | Your own case, plus the assigned readings |
Opening paragraph (model): A transaction processing system is the foundation of every other information system in an organisation, because it captures the routine sales, payments and stock movements that managers later analyse (Laudon and Laudon, 2022). The assigned readings argue that good filing and documentation are what make those records trustworthy. This review agrees, but suggests the argument is stronger when documentation is paired with database design. Codd’s (1970) relational model shows that well-normalised tables prevent the same customer or product being stored in conflicting versions, which is exactly the kind of error a paper filing audit tends to uncover too late.
Related resources
- IMS552 Information System Management assignment sample
- More Universiti Utara Malaysia assignment questions
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References
Codd, E.F. (1970) ‘A relational model of data for large shared data banks’, Communications of the ACM, 13(6), pp. 377–387.
Deming, W.E. (1986) Out of the crisis. Cambridge, MA: MIT Center for Advanced Engineering Study.
International Organization for Standardization (2015) ISO 9001:2015 Quality management systems – Requirements. Geneva: ISO.
Kang, E.T. (2011) ‘Quality research framework: enumerative study versus analytic study from Deming’s perspective’, American Journal of Economics and Business Administration, 3(1), pp. 126–131. doi:10.3844/ajebasp.2011.126.131.
Laudon, K.C. and Laudon, J.P. (2022) Management information systems: managing the digital firm. 17th global edn. Harlow: Pearson.
Wang, R.Y. and Strong, D.M. (1996) ‘Beyond accuracy: what data quality means to data consumers’, Journal of Management Information Systems, 12(4), pp. 5–33.
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