Past exam papers

Past exam papers will refer to different case studies; you do not need the details of the other case studies, when you use past questions, base your answers on your current case study.

There is a copy of a past exam paper here:

past paper 2012

and on the past exams database:

past paper 2009

Here are some guidelines on a past exam paper:

Management Support Systems: Answer Guidelines from Past Examination Paper

These are guidelines, not perfect or complete answers

Question 1.

(a) Explain what is meant by a SWOT analysis, and how this may be used in formulating business strategy.  Give a SWOT analysis for the Marian Haste case study.  (16 marks)

A SWOT analysis uses a matrix/grid showing:

• internal factors of strengths and weaknesses (i.e. within the organisation itself)
• external factors of opportunities and threats (i.e. between organisation and environment)

Example SWOT diagram.

Pearson (1999) SWOT analysis: detailed assessment of strengths and weaknesses of a business and opportunities and threats, in its environment and how the two might advantageously related to each other.

Examples from the case study, e.g.

Strength - experienced well-trained sales staff

Weakness - poor quality of data in existing system

Opportunity - chance to expand in new location

Threat - from competing businesses with a greater range or cheaper prices

(b) Explain what is meant by a Boston Consulting Group (BCG) matrix, and how this may be used in formulating business strategy.  Explain each section of the matrix, and how it can be used. (17 marks)

BCG analysis technique explores the relationship between the current and future potential of a product or service and how management wants to deal with it.  Marketing analysis shows products that are cash generators and cash consumers.  Each will need to be managed differently.  Some items appear to give poor returns may be by-products of other more successful items, and should not be discontinued (if alternative might be to pay for disposal).

BCG matrix diagram. 

Star: High growth, high market share. Generates cash because of market position, and consumes cash due to growth rate; if it retains market share it will become a cash cow in future when market growth rate declines

Cash cow: Low growth, high market share. Exhibit ROI greater than the amount invested; provide the cash needed to run the company.

Dog: Low growth – low market share. Neither generates nor consumes large amounts of cash; typically divest, but could be supporting other areas of growth.

Question mark / wild cat / problem child: High growth, low market share. Growing rapidly, consume cash, but do not generate much cash; is it worth investing further? Become a star, then a cash cow, then a dog as the market declines

 Question 2

Databases, management information systems, expert systems and knowledge-based systems all support management decision-making.  However, different types of decision require different types of support.

(a) consider the types of decision that are made at the strategic level in an organisation

(i) describe the characteristics of decisions made at the strategic level (6 marks)

Strategic: long-term objectives, resources and policies of the organisation

Decisions: relatively uncommon, far-reaching effect on organisation, will affect tactical and operational levels, high level of uncertainty/risk associated, many unstructured, some semi-structured, a few may be structured

(ii) identify the type of management support system that would be appropriate at the strategic level, with specific reference to Marian Haste UK Ltd (5 marks)

EIS, OLAP.  Data in aggregate or summary, users can "drill down".  ES may also be consulted.

Internal and external data; data is static and updated periodically; example from case study.

(b) consider the types of decision that are made at the tactical level in an organisation

(i) describe the characteristics of decisions made at the tactical level (6 marks)

Tactical: medium-term objectives, targets; decisions relatively common, medium impact

feed up to strategic and down to operational level, often have some risk, most semi-structured, some unstructured, a few structured

(ii) identify the type of management support system that would be appropriate at the tactical level, with specific reference to Marian Haste UK Ltd (5 marks)

Data marts, expert systems; data may be fed from TPS into data marts, data warehouses, etc periodically

Mostly internal data is used; data may be static and is updated periodically; example from case study.

(c) consider the types of decision that are made at the operational level in an organisation

(i) describe the characteristics of decisions made at the operational level (6 marks)

Operational: day-to-day tasks, processing transactions, updating files/databases; frequent, short time-frame, do not have a great impact on organisation, mostly structured, some semi-structured, normally based on certainty, low level of risk, results feed to next levels up (tactical and strategic); example from case study.

(ii) identify the characteristics of management support system that would be appropriate at the operational level, with specific reference to Marian Haste UK Ltd (5 marks)

Databases, transaction processing systems; may feed into data marts, data warehouses, etc periodically

Expert systems may also be consulted for advice; mostly internal data; data is dynamic and updated as transactions occur; example from case study.

Question 3.

(a) Describe what is meant by each of the following terms, and how they may be used in the context of business and organisational strategy.  Give an example of each relating to the Marian Haste case study.

(i) Vision              (5 marks)

Core values, core purpose and goals in vision statement; differentiates organisation from competition.  Example from case study.

(ii) Mission statement          (5 marks)

Condenses vision into short description - aims and purpose of organisation. Example from case study.

(iii) Key Performance Indicators (KPI)            (5 marks)

KPIs used as measure to identify success, check customer requirements are met, understand internal processes, identify bottlenecks, ensure decisions based on fact, check planned improvements took place. Example from case study.

(b) Identify one full SMART objective relevant to Marian Haste UK Ltd, and explain how the MIDAS system would assist in meeting this objective.                       (6 marks)

The SMART objective given must have a components for each Specific, Measurable, Agreed/Aligned/Achievable, Relevant/Realistic, Time-framed aspect.  Example from case study.

(c) In order to make effective business decisions, data needs to be gathered and processed before being presented to managers.  Explain how data may be processed before being passed to managers.  How might data be transformed to assist Cynthia Mullion, the HR Manager at Marian Haste UK Ltd, in considering the training needs of sales consultants?    (12 marks)

Information is data that has been processed for a purpose, for decision making; reduces level of uncertainty; supports decision-making.  Examples of processing data: classification, rearranging/sorting, aggregating, calculations, selection.  Graphical / tabular method of representation.

Question 4.

Expert systems support the management decision-making activity by allowing users access to expert advice.  Knowledge must be collected and stored in a suitable format for use in an expert system.  Systems analysis techniques are used in the development of management information systems, but these must be enhanced and extended to deal with the specialist requirements of an expert system.

(a)   Explain what is mean by knowledge elicitation, and how it differs from knowledge acquisition.  (3 marks)

Knowledge elicitation identification and gathering of knowledge from human expert. 

Knowledge acquisition collection of knowledge from various sources, including human experts. 

(b)   Explain the role of a knowledge engineer in the construction of an expert system.                  (5 marks)

Knowledge engineer may interview the expert and assist in formulating and representing knowledge so that it can be stored and accessed as appropriate by end users who would otherwise consult the expert.

(c)   How would a knowledge engineer gather expertise from Andrew Thomas, the Sales & Marketing Manager at Marian Haste?  Explain the following techniques that might be used.

            (i)         triads                                                                                        (5 marks)

Triads: involves sets of three items: two alike, one different in some way.  Different classifications. Example.

            (ii)        repertory grids                                                                          (5 marks)

Repertory grids generated following a structured interview with an expert.  Expert identifies important items and associated attributes in the domain.  A scale of characteristics created, items placed along scale.  Transferred to grid, where rating on scale may be reviewed.  Grid shows relative position of elements.

(d)        Explain each of the following in the context of knowledge representation:

            (i)         association lists                                                     (5 marks)

Association lists (or alists) are lists containing attribute- value pairs.  Alists useful for small amounts of data, but clumsy for larger amounts of data. Example.

            (ii)        production rules                                                      (5 marks)

Production rules have the structure pattern -> action and format if…then…

These rules can be implemented in prolog; the predicate is true if the components are satisfied (using facts within the data/knowledge base).  Example.

            (iii)       breadth first search versus depth first search in a tree structure        (5 marks)

Searching a binary tree: breadth first - following the structure horizontally before moving vertically, until the sought item is found (or not there); depth first - the structure vertically before moving horizontally, until the sought item is found (or not there).  Tree may be pruned to avoid searching where item cannot be.

Question 5.

Databases, management information systems, expert systems and knowledge-based systems all support management decision-making.

(a) Compare and contrast what is meant by each of the following terms:

            (i)         data                                                                                          (4 marks)

Data is that which is given, collection of numbers, letters, measurements little meaning attached.  Example.

            (ii)        information                                                                               (4 marks)

Information as processed data, data subjected to reveal meaning and connections.  Example.

            (iii)       knowledge                                                                                (4 marks)

Knowledge refers to the addition levels of value acquired by data and information to make it useful

(b) How does a data warehouse differ from a data mart and a database?  Under which classification would you place the data used by MIDAS?  Explain why.  (12 marks)

 A database is a collection of related data items stored together.  ERD, represents underlying connections between the items of data.  A database is volatile to reflect changes.

A data warehouse is a large non-volatile repository of data; copy of current data and archive of past data.  Data warehouse updated periodically, requires vast storage; efficient mechanisms for extracting data

A data mart can be seen as a subset of a data warehouse, focussed on a particular organisational function.; non-volatile and updated periodically.

MIDAS classified according to use and justification.

(c) (i) What is meant by the term ‘augmented reality’?                  (3 marks)

An overlay of computer-generated images/text on a real world image (e.g. through a smart phone) that provides additional information to the user, e.g. distance to the nearest underground station.

(ii) Give two examples to explain how augmented reality could be used to support management decision making in Marian Haste UK Ltd. (6 marks)

Augmented reality could be used within the case study (range of potential examples)

The user would need a smart phone with an appropriate application.