Self reflective report 2
toygikiller
MSS.pptx
28/07/2018
1
Housekeeping
o Acknowledgement to Dr Matt Mitchell and Dr Jason Sargent for use of some material in the preparation of this lecture
o This week has the look & feel of a traditional ‘theory-driven’ lecture
o Evidence, just see the length of the reference slides
o The ‘Manage this’ activity will occur at the end of the lecture
o Many supplementary slides this week
o A large general concept of MSS
o Assignment 2 issues let the Convenor know
o Assignment 3 rubric clarity
o Any software used for generating/rendering the mind map needs to be accessible by your marker. Have anything ‘special’ agreed upon prior to submission or risk losing a mark.
Information Systems Management
Management
Support Systems (MSS)
CRICOS 00111D TOID 3069
28/07/2018
2
Overview of MSS
Management Support Systems (MSS) are a broad class of systems whose fundamental purpose is the support of YOUR managerial actions and decision making.
Some common types of support systems include:
– Decision Support Systems (DSS)
– Executive Information Systems (EIS)
– Knowledge Management Systems (KMS) {See Supplementary Slides} and
– Business Intelligence (BI) {Tute/Online self-paced learning activities this week}
Roadmap for today’s lecture
› Management Support Systems (MSS defined)
› Decision support systems (DSS)
› Executive information systems (EIS)
› Intelligent techniques
› Some ‘takeaways’ from the topic
› Supplementary material
› Group Support Systems (GSS)
› Knowledge management systems (KMS)
› Geographical Information Systems (GIS)
› Business Analytics (BA)
› Business Intelligence (BI) (Tute & Online-Self-paced learning
activities)
› Case-based reasoning
28/07/2018
3
Overview of MSS /3
MSS’s function as an integrated approach to sharing information in an
easy-to-use, highly visual, and personalised way
MSS help promote a shared view of business activities due to integration of tools and distributed data/information
Managers can get up-to-date information/ ‘real-time’ on internal operations, industry news & competitor/market trends
What is an example of a highly visual input or output which can help a manager make an enhanced decision?
Overview of MSS /2
MSS is not a particular technology in a restricted sense, but primarily a perspective (vision) on managers and managing, the role of MSS and how to realise this vision in practice.
It is a misconception to think of MSS as systems that just provide managers with information.
MSS are systems that should support managerial cognition and behaviour.
MSS enables senior management to access common, shared sources of internal and external information that have been summarized in easy- to-access, graphical displays.
28/07/2018
4
Efficient & Effective support of the decision-maker
Systems designed to reduce uncertainty in the decision making process tend to focus largely on efficient and effective support of the decision maker (Arnott and Pervan 2005; Konsynski 1988). Umbrella terms that encompass these systems include:
– Group Decision Support Systems (GDSS){See Supplementary Material}, and
– Intelligent Decision Support Systems (IDSS) {Not covered in this lecture}
These systems provide both broad and deep information support as well as analytical capabilities for a variety of decision types (Eom 1998; Vandenbosch and Huff 1997; Xu and Kaye 2002).
Speed facilitated by algorithms, automated decision-making
Management dimensions of IS
Why the need for developing MSS?
Managers set organisational strategy for responding to business challenges and must act to create new products and services and occasionally recreating the organisation.
Systems to support decision making have been developed to meet ever increasing organisational decision making needs which leverage evolving technology that enables even more powerful support of decision making.
Organisations Complexity Strategy
Emerging Technology
(Enhanced) Decision making
28/07/2018
5
MSS may also focus on the problem situation itself
Not knowing the ingredients for bomb-making
Other decision making support systems have development, design, and research premises that centre largely around the problem situation itself.* These include:
– Knowledge management systems (KMS) and
– Business intelligence (BI)**
* Alavi and Leidner 2001; Anderson-Lehman et al. 2004; Lee and Choi 2003; Rouibah and Ould-ali 2002; Schultze and Leidner 2002.
** Alter 2004; Hult 2003; Konsynski 1988; Oppong et al. 2005.
Like to build a bomb?
“...it seems Amazon's recommendation engine may have been helping people buy bomb-making ingredients together.
Just as the online retailer's "frequently bought together" feature might suggest you purchase salt after you've put an order of pepper in your shopping cart, when users purchased household items used in homemade bomb building, the site suggested they might be interested in buying other bomb ingredients.
So what do these mishaps have to do with algorithms?
The common element in all three incidents is that the decision-making was done by machines, highlighting the problems that can arise when major tech firms rely so heavily on automated systems”.
CBC NEWS | Technology & Science October 2, 2017
ANALYSIS When algorithms go bad: Online failures show humans are still needed
28/07/2018
6
Types of decisions
Structured decisions are repetitive and routine (strictly determined), and they involve a definite procedure for handling them so that they do not have to be treated each time as if they were new.
Unstructured decisions are those in which the decision maker must provide judgment, evaluation, and insight to solve the problem (probabilistic, undetermined). Each of these decisions is novel, important, and non routine, and there is no well-understood or
agreed-on procedure for making them.
Many decisions have elements of both types of decisions and are semistructured, where only part of the problem has a clear-cut answer provided by an accepted procedure.
In general, structured decisions are more prevalent at lower organisational levels, whereas unstructured problems are more common at higher levels of the firm.
Decision making
Virtually everyone makes hundreds of decisions each day.
– What’s YOUR tally so far today?
These decisions range from the inconsequential, such as what to eat for breakfast, to the significant, such as how best to use a scarce resource in a production process.
Good decision making means that we are informed and that we have
relevant and appropriate information on which to base our choices.
In some case we support decisions using existing, historical data, while other times we collect the information especially for a particular choice purpose.
28/07/2018
7
Simon’s Decision-Making Model
Herbert A. Simon developed a model of decision making. See “Rational Decision Making in Business Organizations, 1979”.
http://www.nobelprize.org/nobel_prizes/economic- sciences/laureates/1978/simon-bio.html
Intelligence consists of discovering, identifying, and understanding the problems occurring in the organisation - why a problem exists, where, and what effects it is having on the firm
Design involves identifying and exploring various solutions to the problem
Choice consists of choosing among solution alternatives
Implementation involves making the chosen alternative work and continuing to monitor how well the solution is working
Information requirements of key decision-making groups in a firm
Decide to enter/exit markets Approve capital budget Decide long-term goal
Design a marketing plan
Develop a Dept. budget
Determine overtime eligibility, Restock inventory
Offer credit to customers, Determine special offers to to customers
28/07/2018
8
Improving the choice process of decision-making
To improve the choice process we need to improve the information collection and analysis processes. One way to accomplish this goal is to use Decision Support Systems (DSS).
– See this week’s readings in Blackboard
DSS are computer-based systems that bring together information from a variety of sources, assist in the organisation and analysis of information, and facilitate the evaluation of assumptions underlying the use of specific models.
DSS information may come from internally such as an organisation’s Transaction Processing System (TPS), externally (taxation department or bureau of statistics for example).
DSS must allow users to transform the enormous amount of data into information that helps to make an enhanced decision. The models may be simple summation or sophisticated mathematical models.
Information in the decision-making process
IS Managers need to MANAGE INFORMATION
The information comes in the form of facts, numbers, impressions, graphics, pictures, and sounds.
It needs to be collected from various sources, joined together, and organised.
The process of organising and examining the information about various options is the process of modelling.
The quality of the decision depends on:
– the accuracy of the available information,
– the quality of the information,
– the number of options, and
– the appropriateness of the modelling effort available at the time of the decision.
28/07/2018
9
Three (3) basic components of a DSS
1. DSS DATABASE - collection of current or historical data which has been extracted from corporate databases; DSS manipulates live organisational data to support decision making
2. A MODEL base - Collection of mathematical and analytical models
– model - abstract representation, e.g. statistical functions
– sensitivity analysis - models that ask “what-if” questions to determine the impact of changes in one or more factors on outcomes, e.g. what if we increase the price by 5%?
3. DSS SOFTWARE SYSTEM - permits easy interaction between users and the DSS database and model base
– Building a DSS - requires intense user interaction because customised to specific users and specific type of decision; must be flexible and able to evolve; use an iterative development method like prototyping
18
Types of DSS
Communication-driven DSS: support >1 person working on a shared task. Example includes Google Docs
Data-driven DSS: (sometimes data-Oriented DSS) emphasises access to and manipulation of a time-series of INTERNAL company data, and sometimes, EXTERNAL
Document-driven DSS: manages, retrieves, and manipulates unstructured information in a variety of electronic formats
Knowledge-driven DSS: specialised problem solving expertise stored as facts, rules, procedures, or in similar structures
Model-driven DSS: emphasis on access & manipulation of statistical, financial, optimisation, or simulation model.
Very popular tools for decision support activities:
28/07/2018
10
YES, Spreadsheets!
1. based on familiar way to view data (table) and relationships between data take form of a report
2. very easy to use
Allow users to make corrections, additions, and deletions quickly and easily
Can perform “what if” analyses by changing some values and viewing results
Thousands of templates for spreadsheet packages to help users - templates are prepared spreadsheet models into which users only enter data - all relationships and calculating formulas are provided and in place.
Gradebook used in previous semesters by IS staff
– Features...
DSS helps with scenarios & goal-seeking
Scenario generation - what-if mode
– user considers alternative scenarios and their results
– e.g. “What if advertising expenditures are increased by 5%?”
Goal-seeking
– user asks “What would it take in terms of input factors to achieve a particular outcome?”
Executive Information Systems (EIS) is a decision support system (DSS) used
28/07/2018
11
Executive Information Systems (EIS)
to assist senior executives in the decision-making process. It does this by providing easy access to important data needed to achieve strategic goals in an organisation.
The use of these systems by executives may become a particularly important component of their decision making behavior
The frequency of EIS use and the length of time of EIS use are shown to increase problem identification speed, decision making speed, and the extent of analysis in decision making
Making DSS a success: Four (4) reasons for DSS
acceptance
If systems such as business intelligence, knowledge management, decision support, and executive information all support decision making (Arnott and Pervan 2005), then the question arises:
– What is it that unites them?
– What is the thread of continuity, or what elements do these have in common, that organisations have pursued over the past several decades to make their decision making support systems
successful?
1. Movement towards desktop and then mobile computing.
2. Costs of NOT using computer technology are getting higher
3. Less computer anxiety from users
4. ‘Friendlier’ software packages
Need for the timely information
While EIS differ considerably in the number and sophistication of
28/07/2018
12
Informational characteristics of EIS
features, the most common feature of EIS is immediate access to a single database where all current financial and operational data can be found
– Flexibility and ease of use
– Provides the timely information with the short response time
and also with the quick retrieval
– Produces the correct information
– Produces the relevant information
– Produces the validated information
EIS INTERNAL factors (needs of snr managers)
Improved communications
Access to the operational data
Rapid status updates on the various business activities
Access to the corporate database
Highly accurate information
Ability to identify the various historical trends
EIS EXTERNAL factors (needs of snr managers)
Increasing and intensifying the global competition.
Rapidly changing the business environment.
Need to be more pro active.
Need to access the external database.
Increasing the various government regulations.
28/07/2018
13
Executive support CHARACTERISTICS of EIS
Supports the over all vision, mission and the strategy
Provides the support for the strategic management
Sometimes helps to deal with the situations that have a high degree of risk
Is linked to the value added business processes
Supports the need/ access for/ to the external data/ databases
Is very much result oriented in the nature
User interface/orientation characteristics of EIS
Consists of the sophisticated self help
Contains the user friendly interfaces consisting of the graphic user
Can be used from many places
Offers secure reliable, confidential access along with the access procedure
Is very much customised
Suites the management style of the individual executives
Problem indicators can be highlighted with the help of the Executive
28/07/2018
14
Executive support CAPABILITIES of EIS
Information System / executive support system
Open ended problem explanation with the written interpretations can be
done with the help of the Executive Information System / executive support
system
Offers management by the exception reports
Utilises the hyper text and the hyper media
Offers telecommunications capacity
Executive support CAPABILITIES of EIS
Helps in accessing the aggregated or macro or global information
Provides the user with an option to use the external data extensively
Enables analysis of the address and the hoc queries
Shows the trends, the ratios and the various deviations
Graphic & text in the same display, which helps to have a better view
It helps in the assessment of the historical as also the latest data
28/07/2018
15
Executive support BENEFITS of EIS /2
Communication capability and the quality are increased.
Provides with the better strategic planning and the control.
Facilitates pro active rather than a reactive response.
Provides the competitive advantage.
Encourages the development of a more open and active information
culture.
The cause of a particular problem can be founded.
Executive support BENEFITS of EIS
Achievement of the various organizational objectives.
Facilitates access to the information by integrating many sources of the
data.
Facilitates broad, aggregated perspective and the context.
Offers broad highly aggregated information.
User’s productivity is also improved to a large extent.
Used to capture individual and collective knowledge and to extend
28/07/2018
16
Intelligent techniques
knowledge base
– To capture tacit knowledge: Expert systems, case-based reasoning, fuzzy logic
– Knowledge discovery: Neural networks and data mining
– Generating solutions to complex problems: Genetic algorithms
– Automating tasks: Intelligent agents
Artificial Intelligence (AI) technology: computer-based systems that emulate human behavior
“AI systems are like YETI, nobody, has ever seen them, but everybody
Pattern recognition for character, speech and visual recognition
28/07/2018
17
Benefits of AI Systems
Systems that learn are more natural interfaces to the real world
than systems that must be programmed
High fault tolerance
Generalisation – in work with noisy, incomplete or previously
unseen input – generates reasonable response
Adaptivity – learns in new environment.
Artificial Intelligence (AI) Systems
has heard about them ...”
Artificial Intelligence Systems – is the study of how to make computers do things at which, at the moment, people are better; subfield of computer science concerned with symbolic reasoning and problem solving…
Three objectives of AIS:
1. Make machines smarter (primary goal),
2. Understand what intelligence is (that’s Nobel laureate purpose),
3. Make machines more useful (the company purpose).
Four key categories of risk must be managed:
28/07/2018
18
Manage THIS
The Australian Government’s attempt at Dashboards
https://dashboard.gov.au/
Implementing Management Support Systems
1. need thorough understanding of individual, team, and organizational
information requirements
2. involves mega-change to formal and informal policies and practices for
information management and communication information is power
3. implementation of an MSS should be considered an organizational
change initiative need to manage the change
4. must manage the simultaneous evolution of both the organization and
the technological infrastructure
28/07/2018
19
References
Botha A, Kourie D, & Snyman R 2008, Coping with Continuous Change in the Business Environment, Knowledge Management and Knowledge Management
Technology, Chandice Publishing Ltd.
Brown, J.S. & Duguid, P1998, Organizing Knowledge, California Management Review, 40(3).
Clark, T. Jr., Jones, M.C. and Armstrong, C.P 2007, The Dynamic Structure of Management Support Systems: Theory Development, Research Focus, and Direction,
MIS Quarterly, Vol. 31, No. 3 (Sep., 2007), pp. 579-615.
Davenport, T.H 1994, Saving IT's Soul: Human Centered Information Management, Harvard Business Review, March-April, 72 (2)pp. 119-131.
Duhon, B 1998, It's All in our Heads, Inform, September, 12 (8).
Gamble, P.R., & Blackwell, J 2001, Knowledge Management: A State of the Art Guide, Kogan Page Ltd.
Jasperson, J., Carter, P.E., and Zmud, R.W. "A Comprehensive Conceptualization of Post-Adoptive Behaviors
Associated With Information Technology Enabled Work Systems," MIS Quarterly (29:3) 2005, pp 525- 557
Martin, E., Brown, C., DeHayes, D. Hoffer, J and Perkins, W 2005 Managing Information Technology, 5th edition, Pearson Prentice Hall, Upper Saddle River, New
Jersey.
Nonaka, I 1994, Theory of Organizational Knowledge Creation, Organizational Science, 5(1).
Pieptea, D. R., and Anderson, E 1987, Price and value of decision support systems, MIS Quarterly, 11(4), pp. 514-527.
Poon, P. & Wagner, C 2001, Critical Success Factors Revisited: Success and Failure Cases of Information Systems for Senior Executives, Decision Support Systems, 30,
Elsevier Science B.V., 393-418.
Rockart, John F 1979, Chief Executives Define Their Own Data Needs, Harvard Business Review, pp. 81-92.
Rockart J.F. & Treacy M.E 1992, Executive Information Systems: Emergence, Development, Impact, John Wiley & Son, Inc.,(3-12).
Sauter, V 1997, Decision support systems: An applied managerial approach, John Wiley & Sons, New York.
Wellman, J. L 2009, Organizational Learning: How Companies and Institutions Manage and Apply Knowledge, Palgrave MacMillan.
Some ‘takeaways’ from this topic
Management Support Systems (MSS) are intended to directly support you and other managers as you make strategic and tactical decisions for your organisations.
DSS incorporate data and models to help a decision maker solve a problem, especially a problem that is not well structured.
Costs of an MSS precede the benefits and are limiting factors in developing and using a system.
Although the costs are often easier to identify and quantify than
benefits (Pieptea and Anderson 1987), difficulties remain in making truly accurate assessments.
28/07/2018
20
Group Support Systems (GSS)
An important variant of DSS. Sometimes called Group DSSs.
GSS are systems designed to support a group rather than an individual. Work on the principle and strive to take advantage of the power of a group
to make better decisions than individuals acting alone.
GDSS proponents claim that these sorts of technologies can advance the promotion of participation, help to streamline group communications and foster learning. Different vendors have begun to offer group decision support system products like ThinkTank and MeetingWorks, among others. There is also a move to develop open-source tools that are often called discussion support systems*.
*Techopedia
Supplementary Slides
Use the following slides to supplement your breadth & depth on the topic of Management Support Systems (MSS)
28/07/2018
21
Knowledge Management
Group Support Systems (GSS)
https://vimeo.com/31504510
28/07/2018
22
Tacit and Explicit Knowledge
Tacit knowledge: was originally defined by Polanyi in 1966. It is sometimes referred to as know-how (Brown & Duguid 1998) and refers to intuitive, hard to define knowledge that is largely experience based. Because of this, tacit knowledge is often context dependent and personal in nature. It is hard to communicate and deeply rooted in action, commitment, and involvement (Nonaka 1994).
Tacit knowledge is also regarded as being the most valuable source of knowledge, and the most likely to lead to breakthroughs in the organization (Wellman 2009). Gamble & Blackwell (2001) link the lack of focus on tacit knowledge directly to the reduced capability for innovation and sustained competitiveness.
KMS have a very hard time handling this type of knowledge. An IT system relies on codification, which is something that is difficult/impossible for the tacit knowledge holder.
Tacit and Explicit Knowledge
Understanding the different forms that knowledge can exist in, and thereby being able to distinguish between various types of knowledge, is an essential step for knowledge management (KM)
Botha et al (2008) point out that tacit and explicit knowledge should be seen as a spectrum rather than as definitive points
Explicit knowledge: is formalized and codified, and is sometimes referred to as know-what (Brown & Duguid 1998). It is therefore fairly easy to identify, store, and retrieve (Wellman 2009). This is the type of knowledge most easily handled by KMS, which are very effective at facilitating the storage, retrieval, and modification of documents and texts.
From a managerial perspective, the greatest challenge with explicit knowledge is similar to information. It involves ensuring that people have access to what they need; that important knowledge is stored; and that the knowledge is reviewed, updated, or discarded.
28/07/2018
23
Knowledge Management Systems (KMS)
Knowledge management is the process of capturing, distributing, and effectively using knowledge (Davenport, 1994).
A knowledge management system (KMS) stores and retrieves knowledge, improves collaboration, locates knowledge sources, mines repositories for hidden knowledge, captures and uses knowledge, or in some other way enhances the KM process.
KMS tools may include: collaborative and social media tools; corporate knowledge directories; data warehouses and other repositories of organizational memory; business intelligence including data-mining; process automation; workflow and document management.
A light bulb in the socket is worth two in the pocket.
— Bill Wolf (1950 – 2001)
Approaches to KM
Process approach – attempts to codify organizational knowledge through formalized controls, processes and technologies, frequently involves the use of information technologies to enhance the quality and speed of knowledge creation and distribution in the organizations
Practice approach – assumes that a great deal of organisational knowledge is tacit in nature and that formal controls, processes and technologies are not suitable for transmitting this type of understanding. The focus of this approach is to build the social environments or communities necessary to the sharing of tacit knowledge.
28/07/2018
24
Major types of KMS
There are three major categories of knowledge management systems, and each can be broken down further into more specialized types of knowledge management systems.
Knowledge Management Systems (KMS /2)
The ability to manage knowledge is crucial in today ’ s knowledge economy. The creation and diffusion of knowledge have become increasingly important factors in competitiveness. More and more, knowledge is being thought of as a valuable commodity that is embedded in products (especially high-technology products) and embedded in the tacit knowledge of highly mobile employees. While knowledge is increasingly being viewed as a commodity or intellectual asset, there are some paradoxical characteristics of knowledge that are radically different from other valuable commodities. These knowledge characteristics include the following:
– Using knowledge does not consume it.
– Transferring knowledge does not result in losing it.
– Knowledge is abundant, but the ability to use it is scarce.
– Much of an organization ’ s valuable knowledge walks out the door at the end of the day.
28/07/2018
25
Geographical Information Systems (GIS)
The Knowledge Management Value Chain
Knowledge management today involves both information systems activities and a host of enabling management and organizational activities.
28/07/2018
26
Google Maps and Google Earth
Geographical Information System (GIS)
Geographical Information Systems (GIS), spatial decision support systems, location-based services, geodemographics, computer mapping and automated routing are names of a family of applications based on manipulation of relationships in space.
Geographic technologies such as GISs capture, store, manipulate, display and analyse data spatially referenced to the earth.
GISs are a generic term for systems that specialise in geographic data and feature a rich user display and an interactive environment that is highly engaging to human decision makers.
Google Earth
28/07/2018
27
Data Mining
Data mining is often considered a subset of DSS.
One key decision technique or approach used in data mining is decision trees.
A decision tree is a tree-shaped structure that is derived from the data to represent sets of decisions that result in various outcomes – the trees various branch end points.
Business Analytics
There are many software tools for users to create on-demand reports and queries and analyse data. (common name OLAP online analytical processing)
Users could analyse different dimensions of data and trends. Business users easily identify performance trends by using trend analysis and graphic tools There are three groups categories of tools:
Reporting and queries – we have to do with all types of queries, discovery of information, multidimensional view, drilldown to details and so on
Advanced Analytics – include many statistical, financial, mathematical and other models used in analyzing data and information
Data, Text and Web Mining – data mining is a process of searching for unknown or nonobvious relationship or information in large databases using intelligent tools (neural computing or advanced statistical methods) on quantitative data, text, or web data.
Descriptions of past experiences of human specialists, represented as
Case-based reasoning represents
28/07/2018
28
How CBR works
knowledge as a database of past cases and their solutions.
The system uses a six-step process to generate solutions to new problems encountered by the user.
Case-Based Reasoning (CBR)
cases, stored in knowledge base
System searches for stored cases with problem characteristics similar to new one, finds closest fit, and applies solutions of old case to new case
Successful and unsuccessful applications are grouped with case
Stores organisational intelligence: Knowledge base is continuously expanded and refined by users
CBR found in
– Medical diagnostic systems
– Customer support
