BUSINESS INFORMATION SYSTEMS
Simon Kuhn
H1. INFORMATION SYSTEMS, STRATEGY AND GOVERNANCE
1.1 WHAT IS AN IS?
MOTIVATION
We start off this course by asking ourselves 2 questions:
1. Why do we need to know anything about IT?
2. Why can't we leave IT to the IT-people?
From McKinsey's "Modernizing IT for a digital era"
Most companies prefer incrementalism (= step-by-step modernizing their IT-department)
but they are under great pressure of digital disruption (e.g. sudden tele-working through Zoom)
→ companies must choose for an end-to-end modernization (= fully integrated IT-modernization)
We can thus assume that IT is becoming a critical part of companies' DNA, not just a service provider.
We, therefore, need executives who are able to implement following steps:
1. Define how developed the IT-architecture should be in the entire organization
2. Decide which specific systems, people and processes need to change
3. Determine the sequence and scope of these changes
From McKinsey's "Culture for a digital age"
We notice that the most significant challenge to meeting digital priorities (end-to-end modernizing),
are cultural and behavioral challenges:
- a fear of taking risks
- functional and departmental silos that don't communicate or integrate
⇒ there is a strong need for integration (which cannot solely be done by IT)
In conclusion, IT is relevant to understand as we need business leaders with great IT capabilities in
our age of digitalization, automation and artificial intelligence.
→ organizations should move from siloed SBU's to holistically digitized organizations
→ therefore the organizational culture and skill-set need to change as well
→ and thus will everyone be involved in designing and implementing information systems
We need to have a basic understanding of IT and cannot leave it to just the IT-people, as in the future,
everyone involved in an organizational structure will need to design, implement and operate IS.
DATA, INFORMATION AND KNOWLEDGE
Data = raw observed facts of events like business transactions, logs,...
→ useless an sich: we cannot make decisions based on raw data
→ data are the building blocks of information
→ e.g. numbers, documents, raw facts,...
Information = processed data, useful for the decision making process
→ built out of data
→ provides context to raw observed facts (= data)
Knowledge = the ability to perform certain tasks by combining data with own information and
experience.
It is important to note that knowledge and information are personal:
one person's information is merely data for another unless a meaning is put on it!
This is dangerous → possibility that certain people are irreplaceable as they are the only
ones with the knowledge to operate certain business processes.
,An example:
data: 50109
information: - 5/01/09 (date?)
- 50,109 (payment information?)
- 50109 (ZIP code?)
→ data can be interpreted in many ways. It would be foolish to have only one person that is able to
process the data into useful information.
⇒ Information Systems provide the framework that allows everyone to understand data and process
for useful information.
METADATA
The way Information Systems make data more comprehensible is through metadata.
Metadata = information about data and/or information
Some examples:
1. Dublin Core → standard developed to describe electronic sources to improve the
traceability of a document
2. XML → standard language to make search queries more efficient
There are several elements why metadata information is so important:
- it makes information more comprehensible to humans and computers
- it increases the value of information (since everyone can use it now)
→ data is able to become information
- people are not irreplaceable anymore, since others can still use and understand information,
even if the other person left the company
- information can easily be shared between people / companies since the context remains
→ data is able to stay information
SYSTEMS
A system is a set of elements. These elements are related to each other and, possibly, to elements
from the universe of discourse and are joined for a specific purpose.
→ elements: physical objects, biological units, chips, machinery,...
→ relations: physical relations, logical relations, cause/effect relations,...
→ purposes: delivery of services, production of finished goods, obtaining profits,...
For example:
a traffic system
→ elements? roads, vehicles, drivers, police men, legislation,...
→ relations? traffic lights are adjusted to one another, speed limits are based on location,...
→ purposes? maximizing safety, optimizing traffic flow,...
,In general, a system can be visually represented as following:
Important is to remember the 3 requirements:
1. Elements
2. Relations to each other
3. Purposes
BUSINESS INFORMATION SYSTEMS
A business information system is a set of related components to collect, search, process, store and
distribute information in order to support the coordination and control of the decision making
process within an organization (company, government, NPO,...)
Firstly, we can take a look at the nature of business systems:
Secondly, we can take a look at the nature of business information systems:
Ideally, the nature of a BIS is a virtual replica of the physical business system!
This would result in the following representation:
,TYPES OF BUSINESS INFORMATION SYSTEMS
Based on the following two-dimensional typology, we can differentiate between different kinds of
business information systems:
1. Based on the managerial levels
a. Strategic level
- long term decisions
- what-if analysis since there is a great uncertainty
- on an organizational level
b. Tactical level
- mid-long term decisions
- semi-uncertainty
- on a project-based level
c. Operational level
- daily operations and decisions
- immediate results so no uncertainty
- mostly automated
2. Based on the functional domains
a. Sales and Marketing
b. Manufacturing and Production
c. Finance and Accounting
d. Human Resources
e. ….
⇒ BIS should try to create a single integrated system, and thus avoid
so called "isolated silos" (= separated functional domains)
Operational Information Systems
- operational processes are well structured, unambiguous and routinely
- operational decisions regard the short term, occur relatively often and have no uncertainty
- mostly automated since there is no complicated decision making
Examples:
- Online Transaction Processing Systems (OLTP)
→ no inherent certainty about working hours and salary → operational IS
- Enterprise Resource Planning Systems (ERP)
→ "off-the-shelf" modules that can be integrated in many business processes
→ modules regard multiple functional domains
→ mostly simple and repetitive processes → operational IS
,Tactical Information Systems
- tactical decisions concern the mid-long term, are less often, less routinely and regard more
uncertainties or risks
- information required from the operational level + data warehouses
- more uncertainty thus less well structured and the need for external information increases
Examples:
- Management Information Systems (MIS)
→ broad: they span the entire organization
→ simple aggregation and visualisation (nothing too complex)
- Decision Support Systems (DSS)
→ specific: they concern specific departments
→ more complex reports, decision analysis and answers to specific queries (⇔ MIS)
Strategic Information Systems
- strategic decisions concern the long term, have an incidental and irregular character and
regard much uncertainty and risk
- information required is very hard to determine: depends on the individual, external
Examples:
- Executive Support Systems (ESS)
→ designed to support the executive decision makers
→ highly complex, uncertain decisions
- Data warehousing, OLAP, data mining, web mining,...
Although these kinds of information systems work on different managerial levels, they have mutual
relations between one another (= requirement of a system):
, 1.2 IS STRATEGY
"A majority of distinctive competencies of firms (both resources as well as capabilities) rely on
information systems and information technology."
→ we notice that nowadays most competitive advantages originate from IS and IT
→ it is, therefore, valuable to ask ourselves how?
PORTER'S COMPETITIVE FORCES MODEL
Let us begin by defining what a strategy exactly is.
A strategy is required to optimize business processes and maximize profitability.
Empirically, it is not hard to determine the profitability in
different industries.
The real question is how do these differences in ROIC
occur? → early literature couldn't explain this observation
In the eighties, Michael Porter laid out a model that
eventually did explain how certain companies in certain
markets were able to generate greater ROIC.
⇒ Porter's five forces theory
Threat of New Entrants
More entry barriers result in less threats and thus more profitability.
Examples of these entry barriers:
- capital costs (e.g. aviation industry)
- knowledge (e.g. Coca-Cola recipe)
- customer expectations (e.g. luxury clothing brand)
- network effects (e.g. 2B users on Facebook)
- switching costs (e.g. cable provider such as Telenet → will you seriously buy a new digibox?)
Logically, there are less entry barriers for starting a pizza business that for starting a computer
chip manufacturing business. Therefore, the electronics company -- if established well -- will
turn out to be more profitable.
Bargaining Power of Suppliers
More suppliers results in less bargaining power, and thus more profitability for the company.
The more suppliers, the better for our company:
- we can choose the supplier with the best quality, fastest delivery time,...
- we set our own prices (they produce at marginal costs)
Real-world examples:
- Microsoft (supplier) has an enormous market share in the OS-market and, thus, has huge
bargaining power over their buyers. PC manufacturers will have a low profitability.
- There is an enormous amount of milk farmers (suppliers) and, thus, the buying supermarkets
will have a greater bargaining power. Supermarkets will be more profitable.
Simon Kuhn
H1. INFORMATION SYSTEMS, STRATEGY AND GOVERNANCE
1.1 WHAT IS AN IS?
MOTIVATION
We start off this course by asking ourselves 2 questions:
1. Why do we need to know anything about IT?
2. Why can't we leave IT to the IT-people?
From McKinsey's "Modernizing IT for a digital era"
Most companies prefer incrementalism (= step-by-step modernizing their IT-department)
but they are under great pressure of digital disruption (e.g. sudden tele-working through Zoom)
→ companies must choose for an end-to-end modernization (= fully integrated IT-modernization)
We can thus assume that IT is becoming a critical part of companies' DNA, not just a service provider.
We, therefore, need executives who are able to implement following steps:
1. Define how developed the IT-architecture should be in the entire organization
2. Decide which specific systems, people and processes need to change
3. Determine the sequence and scope of these changes
From McKinsey's "Culture for a digital age"
We notice that the most significant challenge to meeting digital priorities (end-to-end modernizing),
are cultural and behavioral challenges:
- a fear of taking risks
- functional and departmental silos that don't communicate or integrate
⇒ there is a strong need for integration (which cannot solely be done by IT)
In conclusion, IT is relevant to understand as we need business leaders with great IT capabilities in
our age of digitalization, automation and artificial intelligence.
→ organizations should move from siloed SBU's to holistically digitized organizations
→ therefore the organizational culture and skill-set need to change as well
→ and thus will everyone be involved in designing and implementing information systems
We need to have a basic understanding of IT and cannot leave it to just the IT-people, as in the future,
everyone involved in an organizational structure will need to design, implement and operate IS.
DATA, INFORMATION AND KNOWLEDGE
Data = raw observed facts of events like business transactions, logs,...
→ useless an sich: we cannot make decisions based on raw data
→ data are the building blocks of information
→ e.g. numbers, documents, raw facts,...
Information = processed data, useful for the decision making process
→ built out of data
→ provides context to raw observed facts (= data)
Knowledge = the ability to perform certain tasks by combining data with own information and
experience.
It is important to note that knowledge and information are personal:
one person's information is merely data for another unless a meaning is put on it!
This is dangerous → possibility that certain people are irreplaceable as they are the only
ones with the knowledge to operate certain business processes.
,An example:
data: 50109
information: - 5/01/09 (date?)
- 50,109 (payment information?)
- 50109 (ZIP code?)
→ data can be interpreted in many ways. It would be foolish to have only one person that is able to
process the data into useful information.
⇒ Information Systems provide the framework that allows everyone to understand data and process
for useful information.
METADATA
The way Information Systems make data more comprehensible is through metadata.
Metadata = information about data and/or information
Some examples:
1. Dublin Core → standard developed to describe electronic sources to improve the
traceability of a document
2. XML → standard language to make search queries more efficient
There are several elements why metadata information is so important:
- it makes information more comprehensible to humans and computers
- it increases the value of information (since everyone can use it now)
→ data is able to become information
- people are not irreplaceable anymore, since others can still use and understand information,
even if the other person left the company
- information can easily be shared between people / companies since the context remains
→ data is able to stay information
SYSTEMS
A system is a set of elements. These elements are related to each other and, possibly, to elements
from the universe of discourse and are joined for a specific purpose.
→ elements: physical objects, biological units, chips, machinery,...
→ relations: physical relations, logical relations, cause/effect relations,...
→ purposes: delivery of services, production of finished goods, obtaining profits,...
For example:
a traffic system
→ elements? roads, vehicles, drivers, police men, legislation,...
→ relations? traffic lights are adjusted to one another, speed limits are based on location,...
→ purposes? maximizing safety, optimizing traffic flow,...
,In general, a system can be visually represented as following:
Important is to remember the 3 requirements:
1. Elements
2. Relations to each other
3. Purposes
BUSINESS INFORMATION SYSTEMS
A business information system is a set of related components to collect, search, process, store and
distribute information in order to support the coordination and control of the decision making
process within an organization (company, government, NPO,...)
Firstly, we can take a look at the nature of business systems:
Secondly, we can take a look at the nature of business information systems:
Ideally, the nature of a BIS is a virtual replica of the physical business system!
This would result in the following representation:
,TYPES OF BUSINESS INFORMATION SYSTEMS
Based on the following two-dimensional typology, we can differentiate between different kinds of
business information systems:
1. Based on the managerial levels
a. Strategic level
- long term decisions
- what-if analysis since there is a great uncertainty
- on an organizational level
b. Tactical level
- mid-long term decisions
- semi-uncertainty
- on a project-based level
c. Operational level
- daily operations and decisions
- immediate results so no uncertainty
- mostly automated
2. Based on the functional domains
a. Sales and Marketing
b. Manufacturing and Production
c. Finance and Accounting
d. Human Resources
e. ….
⇒ BIS should try to create a single integrated system, and thus avoid
so called "isolated silos" (= separated functional domains)
Operational Information Systems
- operational processes are well structured, unambiguous and routinely
- operational decisions regard the short term, occur relatively often and have no uncertainty
- mostly automated since there is no complicated decision making
Examples:
- Online Transaction Processing Systems (OLTP)
→ no inherent certainty about working hours and salary → operational IS
- Enterprise Resource Planning Systems (ERP)
→ "off-the-shelf" modules that can be integrated in many business processes
→ modules regard multiple functional domains
→ mostly simple and repetitive processes → operational IS
,Tactical Information Systems
- tactical decisions concern the mid-long term, are less often, less routinely and regard more
uncertainties or risks
- information required from the operational level + data warehouses
- more uncertainty thus less well structured and the need for external information increases
Examples:
- Management Information Systems (MIS)
→ broad: they span the entire organization
→ simple aggregation and visualisation (nothing too complex)
- Decision Support Systems (DSS)
→ specific: they concern specific departments
→ more complex reports, decision analysis and answers to specific queries (⇔ MIS)
Strategic Information Systems
- strategic decisions concern the long term, have an incidental and irregular character and
regard much uncertainty and risk
- information required is very hard to determine: depends on the individual, external
Examples:
- Executive Support Systems (ESS)
→ designed to support the executive decision makers
→ highly complex, uncertain decisions
- Data warehousing, OLAP, data mining, web mining,...
Although these kinds of information systems work on different managerial levels, they have mutual
relations between one another (= requirement of a system):
, 1.2 IS STRATEGY
"A majority of distinctive competencies of firms (both resources as well as capabilities) rely on
information systems and information technology."
→ we notice that nowadays most competitive advantages originate from IS and IT
→ it is, therefore, valuable to ask ourselves how?
PORTER'S COMPETITIVE FORCES MODEL
Let us begin by defining what a strategy exactly is.
A strategy is required to optimize business processes and maximize profitability.
Empirically, it is not hard to determine the profitability in
different industries.
The real question is how do these differences in ROIC
occur? → early literature couldn't explain this observation
In the eighties, Michael Porter laid out a model that
eventually did explain how certain companies in certain
markets were able to generate greater ROIC.
⇒ Porter's five forces theory
Threat of New Entrants
More entry barriers result in less threats and thus more profitability.
Examples of these entry barriers:
- capital costs (e.g. aviation industry)
- knowledge (e.g. Coca-Cola recipe)
- customer expectations (e.g. luxury clothing brand)
- network effects (e.g. 2B users on Facebook)
- switching costs (e.g. cable provider such as Telenet → will you seriously buy a new digibox?)
Logically, there are less entry barriers for starting a pizza business that for starting a computer
chip manufacturing business. Therefore, the electronics company -- if established well -- will
turn out to be more profitable.
Bargaining Power of Suppliers
More suppliers results in less bargaining power, and thus more profitability for the company.
The more suppliers, the better for our company:
- we can choose the supplier with the best quality, fastest delivery time,...
- we set our own prices (they produce at marginal costs)
Real-world examples:
- Microsoft (supplier) has an enormous market share in the OS-market and, thus, has huge
bargaining power over their buyers. PC manufacturers will have a low profitability.
- There is an enormous amount of milk farmers (suppliers) and, thus, the buying supermarkets
will have a greater bargaining power. Supermarkets will be more profitable.
