How unit 3 is examined
This unit covers how a decision-making system is represented, how information systems evolved into the DSS, what a DSS is and how it is built, how decisions are classified, and the principles of decision management. No topic has been asked in the supplied papers, so every topic is taught in full, in case it appears this year.
Representation of decision-making system
<span style="display:inline-block;padding:.16em .6em;border:1.5px solid currentColor;border-radius:999px;font-size:.68em;font-weight:700;letter-spacing:.06em;text-transform:uppercase;opacity:.75">Not asked since 2022</span>
Definition. <mark>A decision-making system is represented as a flow in which inputs (data, goals and constraints) pass through the phases of intelligence, design and choice to produce a decision, whose outcome returns as feedback.</mark>
Diagram.
<figure class="ds-fig" style="margin:1.4rem 0;overflow-x:auto"><svg xmlns="http://www.w3.org/2000/svg" id="dsfig-u3-01" viewBox="0 0 596 252" width="596" height="252" role="img" aria-label="Decision-making system. In = inputs (data, goals, constraints), Int = intelligence, Des = design, Cho = choice, Imp = implementation, Fb = feedback"><style>#dsfig-u3-01 .e{stroke:#454C5A;stroke-width:1.4;fill:none}#dsfig-u3-01 .e.hi{stroke:#2340B8;stroke-width:2.6}#dsfig-u3-01 .n{fill:#FFFFFF;stroke:#16181D;stroke-width:1.4}#dsfig-u3-01 .n.hi{fill:#E3E9FC;stroke:#2340B8;stroke-width:2.2}#dsfig-u3-01 .n.rb-b{fill:#16181D;stroke:#16181D}#dsfig-u3-01 .n.rb-r{fill:#BD3227;stroke:#BD3227}#dsfig-u3-01 text{font-family:"JetBrains Mono",ui-monospace,Menlo,Consolas,monospace;font-size:13px}#dsfig-u3-01 .t{fill:#16181D;font-weight:500}#dsfig-u3-01 .t.inv{fill:#FFFFFF;font-weight:700}#dsfig-u3-01 .kd{stroke:#16181D;stroke-width:1.2}#dsfig-u3-01 .dot{fill:#16181D}#dsfig-u3-01 .ann{fill:#2340B8;font-size:11px;font-weight:700}#dsfig-u3-01 .lbl{fill:#6F7787;font-family:system-ui,-apple-system,sans-serif;font-size:12px;font-weight:700}#dsfig-u3-01 .ptr{fill:#2340B8;font-size:12px;font-weight:700}#dsfig-u3-01 .ah{fill:#454C5A}#dsfig-u3-01 .ah.hi{fill:#2340B8}#dsfig-u3-01 .wl rect{fill:#FFFFFF;stroke:#DCE0E7}#dsfig-u3-01 .wl .t{font-size:12px;font-weight:700}#dsfig-u3-01 .wl.hi rect{fill:#2340B8;stroke:#2340B8}#dsfig-u3-01 .wl.hi .t{fill:#FFFFFF}html.dark #dsfig-u3-01 .e{stroke:#B1B7C3}html.dark #dsfig-u3-01 .e.hi{stroke:#8FA3FF}html.dark #dsfig-u3-01 .n{fill:#161920;stroke:#E6E8ED}html.dark #dsfig-u3-01 .n.hi{fill:#1E2748;stroke:#8FA3FF}html.dark #dsfig-u3-01 .n.rb-b{fill:#E6E8ED;stroke:#E6E8ED}html.dark #dsfig-u3-01 .n.rb-r{fill:#FF7E71;stroke:#FF7E71}html.dark #dsfig-u3-01 .t{fill:#E6E8ED}html.dark #dsfig-u3-01 .t.inv{fill:#0F1115}html.dark #dsfig-u3-01 .kd{stroke:#E6E8ED}html.dark #dsfig-u3-01 .dot{fill:#E6E8ED}html.dark #dsfig-u3-01 .ann{fill:#8FA3FF}html.dark #dsfig-u3-01 .lbl{fill:#858D9C}html.dark #dsfig-u3-01 .ptr{fill:#8FA3FF}html.dark #dsfig-u3-01 .ah{fill:#B1B7C3}html.dark #dsfig-u3-01 .ah.hi{fill:#8FA3FF}html.dark #dsfig-u3-01 .wl rect{fill:#161920;stroke:#2A2E37}html.dark #dsfig-u3-01 .wl.hi rect{fill:#8FA3FF;stroke:#8FA3FF}html.dark #dsfig-u3-01 .wl.hi .t{fill:#0F1115}</style><defs><marker id="ah6" viewBox="0 0 10 10" refX="9" refY="5" markerWidth="7" markerHeight="7" orient="auto-start-reverse"><path class="ah" d="M0,1 L9,5 L0,9 z"/></marker><marker id="ahh6" viewBox="0 0 10 10" refX="9" refY="5" markerWidth="7" markerHeight="7" orient="auto-start-reverse"><path class="ah hi" d="M0,1 L9,5 L0,9 z"/></marker></defs><path class="e" d="M59,40 L148,40" marker-end="url(#ah6)"/><path class="e" d="M188,40 L277,40" marker-end="url(#ah6)"/><path class="e" d="M317,40 L406,40" marker-end="url(#ah6)"/><path class="e" d="M446,40 L535,40" marker-end="url(#ah6)"/><path class="e" d="M540.2,50.5 L315.5,200.4" marker-end="url(#ah6)"/><path class="e" d="M286.6,196.8 L181.6,56.8" marker-end="url(#ah6)"/><circle class="n" cx="40" cy="40" r="18"/><text class="t" x="40" y="40" dy=".35em" text-anchor="middle">In</text><circle class="n" cx="169" cy="40" r="18"/><text class="t" x="169" y="40" dy=".35em" text-anchor="middle">Int</text><circle class="n" cx="298" cy="40" r="18"/><text class="t" x="298" y="40" dy=".35em" text-anchor="middle">Des</text><circle class="n" cx="427" cy="40" r="18"/><text class="t" x="427" y="40" dy=".35em" text-anchor="middle">Cho</text><circle class="n" cx="556" cy="40" r="18"/><text class="t" x="556" y="40" dy=".35em" text-anchor="middle">Imp</text><circle class="n" cx="298" cy="212" r="18"/><text class="t" x="298" y="212" dy=".35em" text-anchor="middle">Fb</text></svg><figcaption style="font-size:.82em;opacity:.72;margin-top:.45rem">Decision-making system. In = inputs (data, goals, constraints), Int = intelligence, Des = design, Cho = choice, Imp = implementation, Fb = feedback</figcaption></figure>
Key points.
- Herbert Simon's model has three phases: intelligence (scan the environment and find the problem), design (develop possible alternatives) and choice (select the best alternative).
- Implementation is often added as a fourth phase, in which the chosen alternative is put into action and its results are monitored.
- The inputs are internal and external data, the decision maker's goals, and constraints such as budget, time and law.
- The output is a decision and an action, and the observed result flows back to the intelligence phase, so the system is a closed loop and not a straight line.
- In a model of the system the decision maker sits at the centre, using data, models and knowledge to move from problem to solution.
- A DSS supports one or more of these phases (for example, queries for intelligence and what-if models for design) but the human still makes the choice.
Example. A retailer sees falling sales (intelligence), lists options such as discounts, new stock or advertising (design), picks the discount after comparing projected profit (choice), runs it, and reviews next month's sales (feedback).
Answer frame. Open with the definition; draw the block diagram with the four phases and the feedback arrow; then develop points 1-6 in order; close by saying that feedback makes the process continuous.
Evolution of information system
<span style="display:inline-block;padding:.16em .6em;border:1.5px solid currentColor;border-radius:999px;font-size:.68em;font-weight:700;letter-spacing:.06em;text-transform:uppercase;opacity:.75">Not asked since 2022</span>
Definition. <mark>Information systems evolved from transaction processing to MIS, then DSS, EIS and finally business intelligence, each stage moving from merely recording data towards supporting better decisions.</mark>
| System | Main user | Purpose | Output |
|---|---|---|---|
| TPS (Transaction Processing System) | Clerks, operational staff | Record daily transactions | Bills, payroll, ledgers |
| MIS (Management Information System) | Middle managers | Summarise TPS data | Fixed periodic reports |
| DSS (Decision Support System) | Managers, analysts | Solve semi-structured problems | What-if and model results |
| EIS/ESS (Executive Information System) | Top executives | Quick strategic overview | Dashboards, key indicators |
| BI (Business Intelligence) | All levels | Analyse warehouse data | OLAP, mining, reports |
Key points.
- Transaction processing systems came first in the 1950s-60s and automated routine work such as billing, payroll and inventory records, but gave no help with decisions.
- MIS in the 1970s summarised TPS data into scheduled, structured reports for middle managers, but the reports were rigid and could not answer new questions.
- DSS in the late 1970s-80s added interactive models, databases and what-if analysis, so managers could explore semi-structured problems.
- EIS in the 1980s-90s gave senior executives simple, graphical, drill-down summaries of key performance indicators.
- Data warehouses, OLAP and data mining in the 1990s-2000s led to business intelligence, which integrates data from many sources for analysis.
- The trend is from recording to reporting to analysing to predicting, with each stage building on the data of the earlier one.
Answer frame. Open with the definition; give the timeline as the table above; develop points 1-5 in the order TPS, MIS, DSS, EIS, BI; close with the trend in point 6.
Definition and development of decision support system
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Definition. <mark>A decision support system is an interactive, computer-based system that helps decision makers use data and models to solve semi-structured and unstructured problems.</mark>
Diagram.
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Key points.
- A DSS has three main components: a database (internal and external data), a model base (mathematical, statistical and financial models) and a user interface through which the decision maker interacts.
- It is interactive, so the user asks questions, changes assumptions and sees results immediately.
- It supports what-if and sensitivity analysis, which show how the outcome changes when an input changes.
- It supports and improves the judgment of the decision maker and does not replace it, and it is aimed at semi-structured problems.
- It is flexible and adaptable, because the needs of decision makers change as they learn from the system.
- Types include data-driven, model-driven, knowledge-driven, communication-driven and document-driven DSS.
Development steps.
Step 1: Identify the decision problem and the users.
Step 2: Gather requirements, data sources and models needed.
Step 3: Design the database, model base and interface.
Step 4: Build a quick prototype.
Step 5: Test with users and refine repeatedly.
Step 6: Deploy, train users and maintain the system.
- Development is iterative and prototype-based, because requirements are unclear at the start, and users take part in every cycle.
Example. A bank's loan officer enters an applicant's income and the DSS runs a credit model to show the repayment risk, and changing the loan amount shows the risk again at once.
Answer frame. Open with the definition; draw the three-component architecture; develop points 1-6; give the six development steps as a list; close by saying that a DSS improves the quality and speed of decisions.
Decision Taxonomy
<span style="display:inline-block;padding:.16em .6em;border:1.5px solid currentColor;border-radius:999px;font-size:.68em;font-weight:700;letter-spacing:.06em;text-transform:uppercase;opacity:.75">Not asked since 2022</span>
Definition. <mark>Decision taxonomy is the classification of decisions by their structure (structured, semi-structured, unstructured) and by the management level that takes them (operational, tactical, strategic).</mark>
| Basis | Structured | Semi-structured | Unstructured |
|---|---|---|---|
| Procedure | Clear rules | Partly known | None fixed |
| Judgment | Little | Some | Much |
| Example | Reorder stock | Budget allocation | Enter a new market |
| Support | TPS, automation | DSS | Executive judgment, EIS |
Key points.
- Structured decisions are routine and repetitive, follow a known procedure, and can be programmed and automated, for example calculating payroll.
- Unstructured decisions are novel and complex, have no agreed procedure, and depend on judgment and experience, for example launching a new product line.
- Semi-structured decisions combine a computable part with a judgment part, and these are the main target of a DSS.
- Operational decisions are short-term, day-to-day and taken by supervisors, such as scheduling shifts.
- Tactical (managerial) decisions are middle-term, taken by middle managers, and allocate resources, such as setting a quarterly budget.
- Strategic decisions are long-term, affect the whole organisation and are taken by top management, such as a merger.
Pitfall. Do not say a DSS is meant for structured decisions; automation handles those, while a DSS is for semi-structured ones.
Answer frame. Open with the definition; draw a pyramid or the table of structure types; develop points 1-3 for structure and 4-6 for levels; close by linking semi-structured decisions to the DSS.
Principles of Decision Management Systems
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Definition. <mark>Decision management treats decisions as reusable business assets that are modelled, automated and improved on their own, keeping decision logic (business rules) separate from application code.</mark>
Key points.
- Decisions are modelled explicitly, for example with decision tables and the DMN (Decision Model and Notation) standard, so that they are clear to business and IT.
- Decision logic is separated from processes and programs, so a rule can be changed without rewriting the application.
- Business rules are owned and edited by business users in a business rules management system (BRMS) and run by a rules engine.
- Analytics and predictive models supply scores and forecasts to the rules, so decisions are data-driven and consistent.
- Every decision is monitored and its outcome measured, and this feedback is used to refine the rules continuously.
- Automating high-volume operational decisions gives speed, consistency and an audit trail, and frees people for unstructured decisions.
Example. An insurer keeps its claim-approval rules in a BRMS; when the fraud limit changes, an analyst edits one rule and all claim systems use it the next minute.
Answer frame. Open with the definition; no diagram is needed, but a small decision table can be drawn; develop points 1-6 in order; close by saying that decision management makes decisions faster, consistent and easy to change.
Last-minute revision
- Simon's phases: intelligence, design, choice, then implementation and feedback.
- Decision-making system is a closed loop: inputs, process, decision, feedback.
- Evolution: TPS, MIS, DSS, EIS, BI.
- TPS records, MIS reports, DSS analyses, EIS summarises for executives, BI integrates and predicts.
- DSS components: database, model base, user interface (dialogue).
- DSS suits semi-structured problems and gives what-if and sensitivity analysis.
- DSS development is iterative, prototype based and user involved.
- Structured means routine and programmable; unstructured means novel and judgment based.
- Levels of decisions: operational, tactical, strategic.
- DMN is the notation for decision models; a BRMS manages business rules in a rules engine.
- Decision logic is kept separate from application code and improved by feedback.
Memory hooks
- I-D-C: "I Design Choices" gives Intelligence, Design, Choice.
- T-M-D-E-B: "The Manager Decides Every Battle" gives TPS, MIS, DSS, EIS, BI.
- DSS = Data + Models + Dialogue.
- Structured = rules, Unstructured = judgment, Semi-structured = DSS.
- O-T-S: Operational is today, Tactical is this quarter, Strategic is this decade.
Coverage checklist
- Representation of decision-making system: definition, Simon's phases, feedback loop diagram (no past questions).
- Evolution of information system: TPS to BI comparison table (no past questions).
- Definition and development of decision support system: definition, components, development steps (no past questions).
- Decision Taxonomy: structure and management-level classification (no past questions).
- Principles of Decision Management Systems: rules separation, BRMS, DMN, feedback (no past questions).