I S 300 Midterm: Key Terms

CIO

Chief information officer

CSO

Chief security officer

CKO

Chief knowledge officer

CDO

Chief data officer

Views of IT over time

• Connection view: IT as tool (eg. landline phone)

• Immersion view: IT as environment (eg. classroom projector)

• Fusion view: IT as fabric (eg. wearable tech)

Web 1.0 vs 2.0 vs. Web 3.0

• Web 1.0: Information consumer

• Web 2.0: Information producer

• Web 3.0 (moving into): Consume, produce, & own info w/ blockchain (allows for compensation)

Information technology (IT)

Use of computers & software to convert, store, protect, process, transmit, & retrieve info

Information system (IS)

• System that collects & processes data (info) and provides it to managers at all levels for decision making, planning, program implementation & control.

• Broader than IT – also includes study/business discipline of managing IT in a business context

IS based on 6 factors

Technical

• Management science

• CS

• Operations research

Behavioral

• Psychology

• Economics

• Sociology

3 dimensions of IS

• Organization

• IT

• Management

How does IS fit into business?

Connects hardware, datamangement, & telecom w/ business strategic objectives & processes

Strategic business objectives of IT

• Operational excellence (eg. UPS fleet logistics)

• New products, services, & business models (eg. Uber disrupting taxi industry)

• Customer & supplier intimacy (eg. Zara fast fashion model)

• Improved decision making (eg. Verizon customer service & IT support)

• Competitive advantage (eg. Walmart’s scale)

• Survival (eg. Blockbuster vs. online streaming)

More tech [= / ≠ ] more productive

Not always equal - depends on complementary assets

Complementary assets

Assets that amplify tech’s utility

• Organizational assets

  • Appropriate business model

  • Efficient business processes

• Managerial assets

  • Incentives for management innovation

  • Teamwork & collaborative work environments

• Social assets

  • Internet & telecom infrastructure

  • Tech standards

Business processes

• Flow of material, info, & knowledge

• Logically related set of tasks that define how specific business tasks are performed

• May be tied to functional area or be cross-functional

Business = collection of business processes

Types of business processes & example tech used

• Sales & marketing (up until sale)

• Finance & accounting

• Manufacturing & production (everything after sale - including fulfillment & tracking order status)

  • eg. package tracking system

  • eg. self check-in system at airport (side job is sales of add-ons)

• HR

POS System

Point-of-sale system (eg. self-checkout)

Order fulfillment process

• Sales: Generate order & submit order (→ accounting)

• Accounting: Check & approve credit (→ manufacturing & production) → Generate invoice

• Manufacturing & production: Assemble & ship product

Organizational structure & IS system used

• Senior mgmt: ESS (Executive support system)

• Middle mgmt: MIS & DSS (Decision support system)

• Operational mgmt: TPS (Transaction processing system)

TPS

Transaction processing system

Collects data & connects it to existing info in database

Eg. Payroll, order processing, material resoruce planning system, general ledger

MIS

Management information system (descriptive)

Compile, organize, process, analyze, & generate reports from data

Used by middle management

Relationship between MIS & TPS

Multiple TPS systems feed into MIS files to generate reports

eg. Sales + production + accounting info → Report on planned & actual sales by product & region

DSS

Decision support system (prescriptive)

Eg. voyage-estimating system

Used by middle management

ESS

Organizational dashboard

Used by senior management

EAA

Enterprise application architecture

Combine different information systems into one super system

ERP Systems

Enterprise resource planning

• Integrate data from key business processes into one system

• Speed up communication of info throughout firm

• Greater flexibility in responding to customer requests & greater accuracy in order fulfillment

• Let managers see overall view of operations

SCM Systems

Supply chain management systems

• Manage supplier relations, logistics, & order/production/inventory info

• Goal: move correct amt of product as quickly & cheaply as possible

• Automate flow of info across org boundaries

CRM System

Customer relationship mgmt

• Coordinate business processes related to sales, mktg, & customer service

Goals:

• Optimize sales & revenue

• Improve customer satisfaction & retention

• Identify & retain most profitable customers

KM System

Knowledge management system

• Manage processes for capturing & applying knowledge & expertise

• Links firm to external sources of knowledge

Collaboration requirements

• Collaboration capability (org structure & culture)

• Collaboration technology

E-business vs e-commerce vs m-commerce

E-business: Managing enterprise through tech (eg. hire ppl online)

E-commerce: Buying & selling online

M-commerce: Buying & selling on mobile device

4 screens

1. TV

2. Computer/laptop

3. Phone

4. Car dash

Reach

Range of customers a company can reach

Defined by how far customers are willing to travel for your good

Types of e-commerce

• B2C (eg. Amazon)

• B2B (eg. Alibaba)

• C2C (eg. eBay)

How is e-commerce different?

• Ubiquity: Shop anywhere & anytime

• Global reach: Reach customers everywhere

• Universal standards: Seamless communication between different systems, lower entry/search cost

• Information richness: Multiple channels & more depth + scope

• Interactivity: eg. AR

• Information density: Reduced info cost & asymmetry

• Personalization/customization: Tracking tech

• Social aspect: User-generated content (eg. reviews)

E-commerce business models

• E-tailer: Sell physical products directly to customers or businesses

• Transaction broker: Process online B2C transactions

  • eg. Expedia

• Market creator: Digital environment for C2C transactions

• Content provider: Provide digital content

  • eg. Magazines, newspapers

• Community provider: Meeting place for people to communicate & find info

  • eg. Reddit

• Portal: Initial point of entry to web (categorize/classify webpages)

  • eg. Yahoo, MSN

• Service provider: Applications (eg. photo & video sharing, online data storage)

Disintermediation

Getting rid of middle man (manufacturer → customer, no distributor or retailer)

Digital vs traditional markets

• Info asymmetry: lower (for digital)

• Search costs: lower

• Transaction costs: low-none

• Delayed gratification: Higher for physical goods, lower for digital goods

• Menu costs: Lower

• Dynamic pricing: Low cost & instant

• Price discrimination: Low cost & instant

• Market segmentation: Low cost, more precise

• Switching costs: Depends on product characteristics

• Network effects: Stronger

• Disintermediation: More possible/likely

SDLC

Software design life cycle

• Concept

• Prototyping

• Development

• Testing

• Deployment

• Release

HTML

Hypertext Markup Language

WYSIWYG

What you see is what you get

Web development model

• Box-based layout

• Boxes & elements form tree

• Boxes & elements can be stylized

  • parent’s style gets inherited unless overridden

• Styles can be combined into classes

E-commerce revenue models

• Advertising

• Sales

• Subscription

• Free/freemium

• Transaction fee

• Affiliate

CPM

Cost per mille (thousand) impressions

Ad revenue/cost = (views / 1000) x CPM x Commission rate

Marketing channel w/ highest & lowest CPM

Highest: Direct mail

Lowest: Social media

Crowdsourcing

Obtaining info or input into task/project by enlisting services of large # of ppl (usually via internet)

eg. Yelp reviews, Wikipedia, YouTube

Information goods

Info-based (eg. movie, music album, good)

Properties:

• 0 marginal cost/unit

• High cost of production

• ~0 copying cost

• Low distribution & inventory cost

• Variable mktg cost

• Variable pricing

Main areas of growth in m-commerce

• Mass market retailing (eg. Amazon, eBay)

• Digital content sales (eg. music, TV)

• In-app sales to mobile devices

M-commerce gives businesses

More detailed customer info (eg. location)

Location-based services

• Geosocial services (where friends are)

• Geo-advertising (what shops are nearby)

• Geo-info services (price of house you are passing)

Example m-commerce services (not location)

• Financial account mgmt apps

• Mobile advertising (in Google, Facebook, games, etc.)

• Games & entertainment

Mobile app payment systems

• NFC (Near field communication)

  • eg. Apple Pay

• QR Code-based payment systems

  • eg. Starbucks

• P2P (Peer-to-peer) payment systems

  • eg. Venmo, Zelle

Characteristics of entering digital market

• Extremely easy: Low barrier for entry, lots of opportunities

• Handling competition: Need clear definition of business model w/ target market

  • Relationship-based (eg. Starbucks) vs transaction-based (eg. Walmart)

  • Front-end (client-facing) vs back-end (internal); DIY vs outsourcing

  • Need to choose right tech to achieve business objectives

Parts of e-commerce presence map

• Websites

• Email

• Social media

• Offline media

Parts of e-commerce presence timeline

• Planning

• Website development

• Social media plan

• Social media implementation

• Mobile plan

Major types of AI

• Expert systems

• ML

• Neural networks & deep learning networks

• Genetic algorithms

• Natural language processing

• Computer vision

• Robotics

• Intelligent agents

Expert system

Decision flow chart/tree based on knowledge of experts

Machine learning

Given data & outputs, computer generates model to apply to new situations

vs. Traditional programming: Computer gets data & program to generate output

Machine learning is focused on

Recognizing patterns in very large sets of data

Types of (machine) learning

• Supervised learning (eg. neural network)

  • System given examples of desired inputs & outputs identified by humans in advance

• Unsupervised learning (eg. recommendations)

  • Humans don’t provide examples of desired outputs

Neural networks

Find patterns & relationships in large amounts of data too complicated for humans to analyze

Supervised learning

Limitations of neural networks & ML

• Require very large datasets

• Patterns may not “make sense”

• Can't explain how system arrived at solution

• Most useful for classifying into binary categories - not always possible in real world

• No sense of ethics

Genetic algorithms

Find optimal solution by examining large # of possible solutions

Used in optimization

Natural language processing

Process voice or text command using natural human language

Computer vision system

Emulate human visual system to view & extract info from real-world images

eg. Self-driving cars can recognize signs & road markers

Robotics

Design, construct, & operate movable machines & support computer systems to substitute for humans

Intelligent agents

Work w/o direct human intervention to carry out repetitive, predictable tasks

Benefits of outsourcing

• Cost saving

• Improve process speed

• Better quality

• Increase ability to focus on core business

Leavitt diamond

Interdependent:

• Information tech use

• Business processes

• Org form

• Requisite ppl skills

Enterprise systems architecture

Consolidate all info in centralized database

ERP benefits

• Quality & efficiency

• Cost saving

• Decision support & knowledge management

• Enterprise agility

Challenges of enterprise systems

• Difficult to build & costly to implement

• Complex technology & investments required

• Centralized org coordination & decision making

Key SCM processes

• Plan

• Source

• Make

• Deliver

• Return

Push vs pull-based supply chain model

• Push: Produce based on sales forecasts

• Pull: Produce after receiving order (eg. fresh pizza)

Touch points

Method of interaction w/ customer (eg. telephone, email, social media - increasingly popular)

Data hierarchy

Database → file → record → field → byte → bit

Problems with traditional record keeping

• Files maintained separately by diff departments

• Data redundancy & inconsistency

• Program-data dependence

• Poor security

• Lack of flexibility, data sharing, & availability

Relational database

Separate entity groups connected by relationships

Normalization

Break table or relation into set of tables so each only has one theme

Equivalent terms in data management

• Table = relation = file

• Row = record = tuple

• Column = field = attribute

Database entity

Object/thing about which info is stored

Characteristics of relation

1. Row contains data about an entity

2. Column contains data about attributes of entity

3. Cells hold single value

4. All entries in column are of the same kind

5. Each column has unique name

6. Order of columns & rows is unimportant

7. No two rows can have identical sets of values

Primary vs foreign key

Primary key: identifies each record in relation

Foreign key: primary key from another relation used to represent relationship

Referential integrity

Every value of foreign key must match a value of an existing primary key

Monte Carlo simulation

Generate random values for uncertain inputs in model multiple times & compute output to understand output distribution

Types of decision models

• Descriptive: Describe relationship & provide info for evaluation

• Prescriptive (optimization models): Determine best course of action

What-if analysis

Evaluate how specific combinations of model inputs affect outputs

aka sensitivity analysis