cct 355: e-business technologies class 2: introduction to information systems
Post on 26-Dec-2015
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Data, Information, Knowledge, Wisdom
• Data - raw bits (e.g., 0’s and 1’s, many computer controls)
• Information - data organized into chunks that have semantic value
• Knowledge - Application of information to tasks and goals of value and importance
• Wisdom - Ethical and political judgements regarding tasks of importance
What is IT, then?
• IT transmits data - but data alone is rather difficult for use to process
• Information is generally central role (why IT has an I in it, I guess.)
• While knowledge is mostly human domain, IT increasingly supports knowledge communities, making knowledge creation easier
• Relation to wisdom?
Input Process Output (IPO)
• Data is provided, computer transforms, data is generated
• Output data usually then become inputs for other processes (including processes that make us understand data as information)
• Garbage in, garbage out (GIGO) - badly formatted inputs break processes, wrong inputs generate incorrect results
• What’s garbage? Depends on the problem.
Types of Information Systems
• Transaction processing (TPS)• Management and Decision Support (MIS/DSS)• Enterprise Resource Planning (ERP)• Customer Relationship Management (CRM)• Knowledge Management (KM)• Communication and social networking systems
Transaction Processing Systems
• Facilitate processing of transfer of goods and services
• Non-internet – electronic data interchange (EDI) systems
• Internet – e-commerce sites• Key concerns?
Management and Decision Support
• Culling and representing key data to support human decisions
• “expert” systems – e.g., diagnosis software• “dashboards” – key information about a given
information system presented for quick analysis
• Key concerns?
Enterprise Resource Planning
• Systems to manage key inputs of organization• Can be human, physical or more abstract
resources• HR systems• Inventory control and updating• Key concerns?
Customer Relationship Management
• Representing key information of customer base and history of interaction
• Sales support systems• Data mining for key customer habits• Affiliate and loyalty systems• Key concerns?
Knowledge Management and Communication Systems
• Representation and sharing of information within organization
• Supports knowledge building – but isn’t knowledge!
• Groupware systems• Learning Management Systems• Key concerns?
Application: CNC Machining
• Data - raw information fed to machine - makes sense to machine, but incomprehensible to most
• Information - dimensions, material, tool selection• Knowledge - design of part, choice of tools and
materials• Wisdom - relation to whole system, weighing of
alternatives
Application: Email
• Data - streaming of digital information and message metadata, perhaps encrypted
• Information - what you see - grammar, spelling, semantic value
• Knowledge - ability to discern logic of sender, message, response, etc.
• Wisdom – what to say when, gauging importance of email, choice of medium, etc.
Application: KM system
• Data - choice of formats and transmission of data
• Information - semantically valid data• Knowledge - what people do with
information, application to tasks at hand• Wisdom – what elements should be known,
what can be safely ignored when
Tacit Knowledgeand Explicit Information
• IT - superior at representation and transfer of explicit information
• Explicit information requires tacit knowledge to process correctly though - and IT has issues with tacit knowledge
• Example: understanding visual data – human recognition vs. image search engines
• Example: false assumption of some KM systems re: organizational knowledge
Example: Car Team
• Solid base of explicit information represented in reports
• Much tacit knowledge beyond that required to understand reports
• Many tacit and explicit learning mechanisms• Many learning styles among members – some
are more comfortable with some mechanisms• Learning ecology vs. learning management?
Competitive Advantage of IT?
• IT can increase speed and lower cost of distribution and production of information
• IT and the productivity paradox - for years, the above was true, but return on investment (ROI) was stagnant or even negative - why?
• Paradox solved - IT now trends positive ROI - why?
A Balance…
• IT alone doesn’t do much - it must be used intelligently by intelligent people
• People, business process, technology, end objectives, market dynamics, partners and competitors, ethical concerns, legal concerns - all interact to determine success or failure of implementation
• IS types/functions blend – create information ecology usually as robust as weakest link
• Right balance? Well, that’s where knowledge and wisdom come in.
CI
• Where to get companies of interest?• Who to talk to?• How to approach?• What questions to ask?• Proposal in two weeks – one/two pages of
approach and possibilities
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