Knowledge Management and Organizational Learning

Knowledge Management Systems in Business

• Knowledge management and collaboration systems are rapidly growing areas of investment.
• Knowledge that cannot be communicated and shared is nearly useless. It becomes useful when shared.
• Knowledge is a significant component of a firm's intangible assets, which also include brands, reputations, and unique business processes.
• Tacit knowledge exists in the minds of employees, undocumented. Explicit knowledge is documented.
• Knowledge is sticky, not generally applicable or easily moved. It is often situational and contextual.

Organizational Learning

• Organizations learn by collecting data, measuring activities, experimenting via trial and error, and gathering feedback.
• Learning leads to changing behavior and management decisions.
• Organizations that learn rapidly tend to survive longer.

Computer Vision Systems, Natural Language Processing, and Robotics

• Natural Language Processing (NLP) allows computers to understand and analyze human language.
• NLP allows computers to identify intent, extract information, and classify data points, without specific programming instructions.
• Computer vision systems allow computers to emulate the human visual system and extract info from images (like identifying faces).
• Robotics deal with designing, constructing, and operating movable machines that potentially substitute for humans.

Artificial Intelligence (AI) and Machine Learning

• AI is the attempt to build computer systems that think and act like humans.
• Machine learning (ML) is a major part of AI. It uses neural networks and deep learning to find patterns in data and classify inputs.
• Expert systems represent expert knowledge as rules.
• Expert system limitations: Experts cannot fully explain their own decisions (not always quantifiable) and large knowledge bases can be problematic.
• Value of expert systems: Improved decisions, reduced errors, costs, and training time, improving quality and service.

Neural Networks

• A neural network is composed of interconnected units called neurons.
• Neural networks use connections (weights) between neurons to produce outputs.
• Neural networks use a Learning Rule to alter connection strength.
• Applications in medicine, science, and business involve pattern classification, prediction, and control.

Deep Learning Neural Networks

• Deep learning networks have multiple layers for data transformation.
• Deep learning is often used for finding patterns in unlabelled data.
• Deep learning networks learn patterns from large data sets (hundreds of millions).

Genetic Algorithms

• Genetic algorithms use evolutionary biology concepts (inheritance, mutation, crossover) to find the optimal solution to problems with large quantities of variables.
• Genetic algorithms test the fitness of generated strings and use offspring strings and their fitness to evolve towards an optimal solution.

Enterprise Content Management (ECM) Systems

• ECM systems manage structured and semistructured knowledge.
• They handle everything from documents, reports, presentations and best practices to emails, memos, and videos.
• They improve business processes and decision-making by providing knowledge capture, storage, retrieval, distribution and preservation features.

Learning Management Systems (LMS)

• LMS are systems to manage, deliver, track and assess employee learning and training.
• LMS support various learning modalities (downloadable videos, online classes, group sessions).
• They consolidate learning data, and track effectiveness.
• LMS are increasingly integrating with massive open online courses (MOOCs).

Knowledge Work Systems

• Knowledge work systems like CAD (Computer-Aided Design) automate tasks and improve design and change processes.
• CAD reduces reliance on physical prototypes, which saves massive amounts of time and significantly improves design changes.
• Virtual reality systems, like those used in automotive design and development, also speed up design/development cycles through computer-aided design and prototyping instead of physical prototyping.
• augmented reality (AR) overlays digital data onto the physical environment. Augmented visualization facilitates medical procedures, maintenance, and design.

Types of Decisions

• Structured decisions are repetitive and routine (clear procedure).
• Unstructured decisions are novel and require judgment and insight (e.g., strategic decisions).
• Semistructured decisions have elements of both structured and unstructured.

Management Roles

• Managers use information for different roles, including interpersonal roles, informational roles, and decisional roles.
• They act as figureheads, leaders, liaisons, entrepreneurs, disturbance handlers, resource allocators, and negotiators.
• They gather, filter, and disseminate information.

Management Filters

• Filtering happens when managers use their own criteria, and cognitive biases to understand and interpret information, which often influence their decisions.

Transaction Processing Systems and Management Information Systems

• Transaction processing systems (TPS) record and process daily transactions.
• Management information systems (MIS) gather, process and analyze data to support decision-making.
• Production reports are standard, pre-scheduled reports.
• Parameterized reports allow for specific filter criteria.

Business Analytics

• Business analytics is the ability to model future events and behaviors to accurately predict outcomes.
• Predictive analytics use statistical analysis and data mining techniques.

Balanced Scorecard Method

• Balanced scorecards measure outcomes across different dimensions of firm performance (financial, business process, customer, learning and growth) and key performance indicators (KPIs).
• They align operational objectives to strategic plan.