BSBINS601 Manage Knowledge and Information

Overview of BSBINS601

• BSBINS601 Manage knowledge and information is a unit that describes the skills and knowledge required to develop and maintain information and data systems to support an organization in making decisions, and to optimize the use of knowledge and learning throughout the organization.
• The unit applies to individuals who are responsible for ensuring that critical business information is readily available to review the organization’s performance and to ensure its effective functioning.

Collecting Business Information

• Collecting business information involves reviewing feedback and business performance data, identifying, defining, and analyzing business issues, and identifying information required to reach decisions on issues.
• Information and knowledge management systems are developed to retain, access, and improve business outcomes.
• Information management is about managing an organization's information resources to improve performance.
• Knowledge management is about the processes of acquiring, capturing, creating, sharing, and using knowledge to enable learning in organizations.

Information Management Systems (IMS)

• An IMS facilitates the collection, storage, organization, management, and retrieval of data.
• Examples of IMS include: • Learning management systems • Database management systems • Office information systems • Decision support systems • Customer Relationship management
• The purpose of an IMS is to turn raw data into useful information for decision making.

Knowledge Management Systems (KMS)

• A KMS supports information and knowledge sharing, collaboration, and organization of information.
• Examples of KMS include: • Document management • Content management • Data warehouses • Databases • Intranets • Wikis • Social networking platforms
• The purpose of a successful KMS is to: • Share knowledge and information • Avoid redundancy • Prevent duplication of effort • Increase productivity • Support decision making • Provide reliable and secure information

Managing Knowledge and Information

• Managing knowledge and information can be achieved through management information systems (MIS) and decision support systems (DSS) which have the following common key features: • Data management • Reports • Open access • Integration • Scalability
• Emerging technologies used in knowledge and information management include: • Collaboration tools • Visuals
• Existing technologies used in knowledge and information management include: • Content Repository • Communication Tools • Unified communications tools

Reviewing Feedback and Performance Data

• Reviewing feedback and performance data involves collecting and analyzing data to identify business issues and make informed decisions.
• Business performance management involves reviewing overall business performance and determining how to better reach goals.
• Business performance data uses results to monitor how an organization's efforts are aligning with overall business objectives.
• Staff and customer feedback can be obtained from various sources such as surveys, emails, online contact forms, website analytics, and social media channels.

Analyzing Business Issues

• Analyzing business issues involves identifying, analyzing, and defining problems or issues using collected business performance data.
• The 80-20 Rule (Pareto Principle) asserts that 80% of outcomes/outputs result from 20% of all causes (or inputs) for any given event.
• The core principle of the 80-20 rule is to identify an entity's best assets and use them efficiently to create maximum value.

Information Needed to Reach Decisions

• Decisions for the best options require looking at different factors such as associated costs, technical factors, human resources, and risks.
• The key steps of the decision-making process include: • Identify the decision • Gather data/information • Determine relevancy • Identify alternatives • Weigh up the evidence • Select the option • Take action • Review

Sourcing and Collecting Information

• The information required to reach a decision should be relevant and reliable.

• Information can be sourced from internal or external sources.

• Examples of internal sources include: • Records • Documents • Internal communications • Statistics • Data

• Examples of external sources include: • Government bodies • Professional industry • Competitors • Customers • Surveys • Social media analytics • Employee records • Interviews • Databases### Data Quality and Reliability

• Data quality is crucial when collecting information from a database or other sources.

• Information may not be reliable or relevant if records have not been maintained or updated.

• Sources of information can come from:

  • Quantitative data: numeric variables, measures of values or counts, expressed as numbers (e.g., statistics, polls, or collected raw data).
  • Qualitative data: categorical variables, measures of types, represented by names, symbols, or codes (e.g., interviews, written emails, images, or videos).
  • Primary sources: direct or firsthand evidence, including statistics, surveys, or blogs.
  • Secondary sources: interpretations and analysis based on primary sources, such as articles, reports, or journals.

Checking the Quality of Information

• The quality of information has five characteristics: accurate, timely, complete, reliable, and consistent.
• Integrity of data and information should be tested for reliability and validity.
• Poor-quality information can lead to detrimental business decisions.

Consulting with Stakeholders

• Consulting with stakeholders can provide further relevant knowledge that may not be formally captured.
• Stakeholders can include anyone using, managing, or controlling information within the system.
• Informal networks can be used to access this type of knowledge, such as departmental reports or information from personal memory.

Analyzing Information and Knowledge

• Objectives for analysis should be clear, relevant, and consistent, using SMART objectives.
• Analyzing information and knowledge involves:
  • Identifying and interpreting patterns and emerging trends.
  • Interpreting statistical analyses.
  • Using sensitivity analysis on relevant options.
  • Documenting is an approach to analyze information and knowledge.
  • Adjusting information and knowledge management decision support systems.

Patterns and Emerging Trends

• Patterns and emerging trends can be identified through:
  • Spreadsheet functions.
  • Statistical analysis.
  • Cause and effect data analysis.
  • Primary and secondary research.

Statistical Analysis

• Statistical analysis can be used to aid decision-making by establishing numerical benchmarks and providing patterns and trends for analysis.
• Methods commonly used in statistical analysis include:
  • Correlation calculations.
  • Short-term, medium-term, and long-term trend analyses.
  • Probability assessment.
  • Dynamic programming.
  • Linear programming.
  • Queuing theory.
  • Simulation.

Sensitivity Analysis

• Sensitivity analysis is used to assess how different values of an independent variable affect a particular dependent variable under a given set of assumptions.

Documentation

• Documentation of analysis should be recorded, structured, and presented in a readable format that shows a logical approach to the evaluation of evidence and any conclusions drawn.

Making Adjustments

• The objective of an information and knowledge management decision support system is to ensure the right information is delivered to the right people or place at the right time to support informed decision-making.

• Business process tools and techniques include:

  • Flowcharts.
  • Functional flow block diagrams.
  • Control flow diagrams.
  • Gantt charts.
  • PERT diagrams.
  • IDEF diagrams.### Rectifications for Business Issues

• Confirming sufficient valid and reliable information is available to support decisions

• Using risk management plans to identify potential risks and mitigate them

• Using quantitative methods to support decision-making

• Consulting with relevant stakeholders to ensure diverse perspectives

• Making decisions consistent with organizational objectives, values, and standards

Importance of Quality Information

• Quality information is essential for effective decision making
• Poor decision making can occur due to lack of information, too many factors, or high risk
• Information must be shared, reliable, secure, and support decision making

Risk Management

• Involves identifying, assessing, evaluating, and mitigating risks
• Risk assessment plan includes measures to respond to risks
• Risk mitigation options include accepting, controlling, avoiding, or transferring risks
• Controls must reduce the likelihood of risk or reduce the impact

Using Quantitative Methods

• Quantitative methods include linear programming, probability decision theory, game theory, queuing theory, and simulation
• These methods are based on scientific and statistical approaches
• Decision trees and network analysis can be useful techniques for analysis

Consulting Specialists and Stakeholders

• Specialist advice may be needed from internal or external sources
• Expertise may be required from IT, HR, finance, or business managers
• Project teams, functional departments, or users of the system may also be consulted

Accountability, Consistency, and Timeliness of Decisions

• Decisions must be made within the accountability of the responsible people
• Decisions must follow organizational policies, procedures, guidelines, and practices
• Decisions must be consistent with organizational objectives, goals, strategies, and values
• Decisions must be made promptly

Distributing Information

• Documenting information requirements is essential for development of information and data systems
• Databases must be updated regularly to ensure quality of data
• Information must be distributed to the right people at the right time
• Communication plans must be developed to ensure effective distribution of information

Designing and Testing Systems

• Systems development lifecycle (SDLC) includes analysis, design, testing, implementation, and development
• Testing must be conducted to ensure system is fully functional and without error
• Testing may include testing queries, searching, filtering, and sorting, and running data analysis

Ensuring Information Quality

• Information systems must be kept up-to-date and accurate
• Data must be validated before entering the system
• Tests and monitoring of results must be performed regularly
• New data must be added immediately, and updates of records must be done regularly