Ch 8 - decision making and business intelligence

What is decision making in management?

Choosing from a range of alternatives.

• It’s a key part of management

Why is rational decision making complicated?

1. Rationality is hard to define.

2. Good outcomes can come from bad decisions, and bad outcomes can come from good decisions

3. Humans have limited ability to process all options, known as 'bounded rationality'.

Bounded rationality

Herbert Simon’s idea that humans try to be rational but can’t consider all options due to limited brainpower. We satisfice, or settle for a good-enough option.

Ackoff's criticisms of early MIS assumptions?

1. More data doesn't always help.

2. Managers have too much info, not too little (information overload).

3. Managers often don’t know what data they actually need.

Information overload

Having too much information to process effectively.

• It causes confusion and poor decision making.

• Ex: Asking for more data than needed just in case.

The challenge is for managers to find the appropriate data and incorporate them into their decision-making processes

Why does data growth matter in decision making?

Huge amounts of data are being created fast (e.g., 44 zettabytes by 2020).

If used properly, this data can improve decisions, but it can also overwhelm managers.

What are examples of bad data quality issues?

Raw data that is usually unsuitable for sophisticated reporting or data mining

Major problem categories:

• Dirty data (e.g., misspelled colors)

• Missing values

• Inconsistent formats (like phone numbers)

• Unintegrated data from different sources

• Inappropriate granularity

Data granularity

Refers to how detailed data is.

• Fine = very detailed (e.g., click-by-click)

• Coarse = summarized.

• Too fine can be combined, but coarse data can’t be split further.

How can information systems help with decision making?

They can process and summarize large data sets, helping managers find the right information and avoid overload, if the data is high quality and relevant.

Online Transaction Processing (OLTP)

OLTP systems collect data electronically and process the transactions online

• Can be in real time or batched transactions

• Backbone of all functional, cross function, and interorganizational systems in an organization

• Supports decision making by providing the raw information about transactions and status for an organization

Ex: banks, stores, and airline systems.

Real-time vs batch processing

Real-time processing: updates the system immediately after each transaction (e.g., Ticketmaster)

Batch processing: waits to group transactions before updating (ex: retail sales outlet sending sales data nightly to the head office)

OLAP (Online Analytical Processing)

Helps turn data from OLTP systems into meaningful insights

• Data is collected in OLTP, but this makes that data useful for decision making

• Provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data

• Provides reports which include more in depth information regarding transactions

• OLAP reports are also referred to as cubes

• User can alter the format of the report

Why are OLAP servers needed?

Standard databases aren’t made for complex analysis. OLAP servers handle the heavy lifting of sorting, calculating, and formatting large OLAP reports.

• OLAP itself isnt a server, but servers are used

What is the data resource challenge?

Even though companies collect lots of data, they often don’t use it well. The challenge is treating data like a valuable asset and using it for decision making.

Business Intelligence (BI) system

Provides information to improve decision making by analyzing data and offering insights that create competitive advantage.

5 categories of business intelligence systems

1. Group decision support systems

2. Reporting systems

3. Data-mining systems

4. Knowledge-management systems (KM)

5. Expert systems

Group Decision Support System (GDSS)

Allows multiple decision makers to collaborate (often anonymously) across different locations and times, reducing biases in group decisions.

• Input is automatically summed or communicated to the group and contributes to a decision

Reporting systems

These systems integrate and process data through mutiple sources, such as sorting, grouping, summing, averaging, and comparing, then formats the results into reports

• Improves decision making by providing the right information to the right user at the right time

Data-mining system

A system that uses sophisticated statistical techniques (such as regression or decision trees) to find patterns and relationships in data to anticipate events or predict future outcomes

• includes rfm analysis

Market-based analysis

A type of data-mining system that computes correlations of items on past orders to determine ones frequently purchased together

Knowledge Management (KM) system

Creates value from intellectual capital, collects and shares human knowledge

Benefits:

• Fosters innovation

• Improves customer service

• Increases organizational responsiveness

• Reduces costs

Expert system

Uses the knowledge of human experts in the form of “If/then” rules

• “If” the condition is true, “then” initiate procedure

• Ex: if patient temp > 103, then initiate high_fever_procedure

• Improves the diagnosis and decision making in non-experts by applying expert knowledge automatically

Characteristics and competitive advantage of business intelligence systems

What is RFM analysis?

A method for ranking customers based on how Recently (R) they purchased, how Frequently (F) they buy, and how much Money (M) they spend.

Analysis using operational data

Doing analysis using operational data is not recommended

• There are security and control concerns

• Operational data is not set up for analysis, but for fast and reliable transaction processing, and considerable processes is required for BI analysis

• Operational data gets extracted for BI processing: to a database for small companies and to a data warehouse for larger companies

Data warehouse

A repository for managing an organizations BI data

• Comes from operational systems, purchased data, and external data

• Stores metadata (data about data)

What are the functions of a data warehouse?

1. Obtain data

2. Cleanse data

3. Organize and relate data

4. Catalog data

Diagram of components of a data warehouse

Data mart

A data collection designed to serve a specific business function, problem, or opportunity.

• Companies may have more than one (ex: one for web log data, one for market-based analysis, one for inventory, etc)

• Smaller than a data warehouse

  Note: Data warehouses and data marts can be expensive to build and operate. Smaller organizations may only need a simple data mart for specific analysis needs.

Diagram of components of a data mart

Data Mining

The process of using statistical techniques to find patterns and relationships in large sets of data.

Areas of discipline for data mining:

• Stats/math

• AI and machine learning

Useful areas for data mining include:

• Future healthcare (predictions)

• Market basket analysis

• Education

• Manufacturing engineering

• CRM

What are the two types of data mining?

1. Unsupervised: No model or hypothesis beforehand; patterns are discovered from data. Ex: cluster analysis (identifies groups of entities that have similar characteristics)

2. Supervised: A model is made first, and data is used to test or build it. (ex: regression analysis, neutral networks, market-based analysis)

Regression analysis

Measures the impact of a set of variables on another variable

Neutral networks

Used to predict values and make classifications, such as “good prospect” or “poor prospect” customers

Market-based analysis

Determining sales patterns; items that tend to be bought together

Big data

Large amounts of varied data from a variety of sources over a period of time that could be used to make better decisions

Controversy over big data

• Lack of precision on its definition

• Adds to excessive data collection

• Expensive

• Imprecise (overly vague or general)