L9 - Business analytics and knowledge management Flashcards

1
Q

What is information evaluation?

A

The systematic determination of the merit and worth of information.

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2
Q

Why do managers gather info?

A

In a belief that more information improves decision making

To justify decisions

To verify previously acquired information

To “play it safe” by making sure they do not miss any relevant information

In the belief that the information may be useful later

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3
Q

What is information overload and what are the consequences?

A

Being faced with more info than we can effectively process. The more info we have to sift through, the less attention we have to devote to other tasks. Reduces productivity, increases stress, can lead to physical health problems.

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4
Q

What are 2 major strategies for dealing with info overload?

A

Filtering: knowing what info we need and what info merits attention and use
Withdrawal: involves disconnecting from sources of info

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5
Q

What is information quality?

A

Info that is fit for its intended use, the info is useful toward the achievement of whatever task is at hand.

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6
Q

What are 4 dimensions of information quality?

A

Intrinsic quality: dimensions of quality that are important regardless of the context or how the info is represented (accurate, believable, objective)

Contextual quality: the dimensions that may be viewed differently depending on the task at hand (relevant, timely, complete, current)

Representational quality: how the information is provided to the user.

Accessibility quality: has to do with whether authorized users can easily access the information.

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7
Q

What are information quality costs?

A

May seem like we want highest quality info possible. However, few are willing to invest in resources necessary. We want “good enough” info quality. Important to consider the costs of information quality and what level of cost is justified. At a more micro level, a good way to think about the costs of information quality is to consider the possible consequences of poor-quality information. More important with high quality info when it is high impact decisions.

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8
Q

What are 2 things we need to consider about info obtained from external sources?

A

First: Is it useful (relevant, appropriate, sufficiently current)? Second: Is it believable (whether the information
comes from a credible, objective source, is well supported, and sufficiently comprehensive)?

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9
Q

What is knowledge management?

A

A process that allows organisations to generate value from their knowledge-based assets. Involves capturing and documenting what employees and other stakeholders know and developing systems that make it easier to share and use that knowledge.

Definition: Generating, capturing, codifying and transferring knowledge across the organization to generate value

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10
Q

What are benefits of effective knowledge management?

A
  • Better problem solving
  • Improved customer service
  • More effective product management
  • Increased innovation
  • Improved processes (more efficient and more effective)
  • Increased intellectual capital through better leveraging of intellectual assets
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11
Q

What is explicit vs. tacit knowledge?

A

Explicit: can be expressed relatively easily and thus more easily shared, stored and managed, “knowing that”.

Tacit: not easy to express or communicate. Internalized and highly individualized, rooted in life experience, values and biases, “knowing how”.

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12
Q

What is a complete knowledge management system?

A

A complete knowledge management system should consist of knowledge creation, capture, codification, storage, retrieval, transfer, and application (knowledge management process). Knowledge management processes form a cycle. Applying knowledge often leads to the creation of new knowledge, which restarts the cycle.

  1. Create
  2. Capture and Codify
  3. Store and Retrieve
  4. Transfer and Apply
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13
Q

How do we transfer and apply knowledge?

A

To manage knowledge transfer, you must consider the sources of knowledge you have, the media you can use to transfer this knowledge as well as who should use this knowledge.

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14
Q

What is critical to knowledge management?

A

Information technology is critical to modern knowledge management, but technology alone cannot ensure effective knowledge management. Effective knowledge management also requires social and structural mechanisms that support knowledge management.

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15
Q

What is the SECI model of organisational knowledge creation?

A

Knowledge creation is a continuous process consisting of interactions between implicit and explicit knowledge. Form a cycle of increasing knowledge. There are four processes by which knowledge is created.

Socialization: sharing tacit knowledge through direct communication or shared experience. Tacit knowledge to tact knowledge communication.

Externalization: tacit to explicit communication. Tacit knowledge is converted to explicit knowledge by developing specific concepts, models, and the like. This conversion allows the knowledge to be understood and interpreted by others. This also serves as a foundation for creating new knowledge.

Combination: the process of combining the externalized explicit knowledge to form broader concepts, models, and theories.

Internalization: when explicit knowledge transforms to tacit knowledge and becomes internalized by individuals within the organization. This can start a new cycle, beginning with the socialization of the new tacit knowledge.

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16
Q

What is capturing and codifying knowledge?

A

Once knowledge is created or otherwise acquired, it needs to be captured and codified. There are many techniques for capturing knowledge, including interviewing experts, observing groups as they make decisions, focus groups, “lessons learned” debriefings… etc.
Codifying knowledge means converting tacit and explicit knowledge into a form that organizational members can use. It is representing knowledge so that it can be reused. This also includes documenting knowledge that was previously undocumented.

17
Q

What should organisations do to codify knowledge?

A
  • Define the strategic intent. (How will the codified knowledge serve the organization?)
  • Identify the knowledge necessary to achieve the intent.
  • Evaluate existing knowledge’s usefulness and ability to be codified.
  • Determine the best way to codify and distribute the knowledge.
18
Q

What are 3 ways to codify knowledge and what is the purpose of the tools?

A

Cognitive maps: the mental model of the expert’s knowledge, key concepts and key relationships are shown

Decision tables: a list of conditions and their values along with a list of conclusions or actions, the conditions necessary for each conclusion are indicated

Decision trees: alternate paths that impact decisions. Various paths that can lead to certain outcomes.

The purpose of these and other codification tools are to systematically document knowledge that is “stored’ in the minds of experts

ILLUSTRATION

19
Q

What are knowledge repositories?

A

The goal of knowledge repositories is to make it easy to find and retrieve documents that contain knowledge. There are three main types of knowledge repositories:

Externally focused

Structured internal knowledge, such as research reports and marketing materials

Informal internal knowledge, such as “lessons learned” reports and discussion databases and frequently asked questions collections.

20
Q

What are communication-oriented tools for knowledge management?

A

E.g. email

Social networks

Communities of practice that exist within networks, e.g. LinkedIn groups

21
Q

What are collaboration tools?

A

Combine elements of repositories and communication-based knowledge management tools e.g. Google Docs

22
Q

What are executive IS systems and dashboards?

A

Executive information systems help provide high-level managers with the information they need to monitor business activities and make decisions. EIS typically make heavy use of graphical displays of data. Digital dashboards provide graphical views of key data along with graphical warnings when data indicate areas that need attention

23
Q

What are expert systems?

A

Expert systems help users solve problems or answer questions in a way that mimics an expert’s thought processes. An expert system typically has a narrow focus on a particular problem domain. Many organizations use expert systems to guide nonexpert employees through complex decisions or problems such as technical troubleshooting.

24
Q

What are decision support systems?

A

Decision support systems (DSS) are computer-based systems that help decision makers use data and models to solve semi-structured or unstructured problems.

25
Q

What are 4 types of decision support systems?

A

Data-driven DSS focus on the retrieval and manipulation of data that is stored in an organization’s data stores. Data warehouses
are often important data driven DSS. Useful for unstructured decisions

Model-driven DSS focus on providing the decision maker with the ability to access and manipulate analytical models. These models are used to help the decision maker perform sophisticated analysis that would be difficult and time-consuming without the DSS. Useful for semi-structured decisions

Document-driven DSS focus on managing and retrieving documents that may help with decision-making. The term documents should be taken broadly Document driven DSS are particularly useful for less structured decisions.

Communication-driven DSS facilitate collaboration and group-based decision making. Communication-driven DSS support one or more of the following: communication, information sharing, collaboration, and/or group based
decision-making. Groupware is one type of communication- driven DSS. Others: Email, document sharing, and co-editing systems

26
Q

What is groupware?

A

Groupware refers to programs that help people work together collectively while located remotely from each other. Programs that enable real time collaboration are called synchronous groupware (opposite asynchronous).

When group members are in the same physical location, they are co-located. (Video conferencing, chat systems, e-mails, shared whiteboards)

27
Q

What is business intelligence?

A

Business intelligence is set of applications, technologies, and processes for gathering, storing, analysing, and accessing data to help users make better business decisions.

Often BI combines two sets of technologies, data warehousing and data mining, to help managers leverage the organization’s data resources for better decision-making. Goal – help managers make sense of data.

28
Q

How does business intelligence work?

A

Transactional databases “create” the data. The data from the transactional databases is put into the data warehouse by a process called extract, transform, and load (E/T/L). The data warehouse stores and organizes the data in a way that is better suited for supporting decision-making. Analysts and managers use data mining tools make sense of the data stored in the data warehouse.

29
Q

What is a data warehousing and what is a data warehouse?

A

Data warehousing is a process, the goal of which is to gain value from an organization’s information through the use of data warehouses.

A data warehouse is a copy of transactional data (and other data) that is formatted so that it is useful for decision support.

30
Q

Data warehouses have several characteristics that set them apart from transactional databases:

A

Data warehouses are subject-oriented. They are organized around particular subjects such as marketing, human resources, sales, or production.

Data in data warehouses are integrated from a variety of internal and external sources.

Data in data warehouses are typically transformed from their original format. Detailed data are often aggregated.

Data in data warehouses typically are non-volatile, which means that the data do not change. Once data are in the warehouse, they stay in the warehouse and are not changed.

31
Q

What is the E/T/L process?

A

Extract: Data are pulled from the source systems (such as the transactional databases).

Transform: Data must be changed into a form that is suitable for decision support. Often this involves aggregating detailed data. Data cleansing is also an important part of the transform process. Data in transactional databases is often messy. This problem gets worse when data are extracted from multiple systems. This messy data must be cleaned up before being loaded into the warehouse.

Load: The cleaned data needs to be put into the data warehouse. This must be repeated periodically

32
Q

What is data mining?

A

Data mining is the process of analysing data to identify trends, patterns, and other useful information. Data mining typically involves applying statistical techniques to identify trends and patterns

33
Q

What is the difference between data mining and traditional statistical analysis?

A

In most traditional statistical analyses you create a model (such as a regression equation) and then test that model using data. In data mining the emphasis is on discovering the model, then testing the validity of the model. Statistical techniques are used to uncover the relationships in the data that lead to the model.

34
Q

Name 5 types of data mining techniques

A

Detect associations: discovering patterns in which multiple events are connected

Sequence analysis: when one event leads to another

Classification: dividing data into mutually exclusive groups based on the variable you want to predict

Clustering: diving data into mutually exclusive groups based on all available data

Forecasting: making predictions using discovered patterns