CCT 355: E-Business Technologies Class 2: Introduction to Information Systems

Administratrivia Article analysis scheduling – later today CI brainstorming – later today

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: 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 , 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 Knowledge and 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

Article Analysis Scheduling Sources Presentation Tips and Mechanics

Next Week Ch.3 First presentations