Management Information Systems: Managing the Digital Firm PDF

Management Information Systems: Managing the Digital Firm Sixteenth Edition Chapter 11 Managing Knowledge and Artificial Intelligence Copyright © 2020, 2018,...

Management Information Systems: Managing the Digital Firm Sixteenth Edition Chapter 11 Managing Knowledge and Artificial Intelligence Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Learning Objectives 11.1 What is the role of knowledge management systems in business? 11.2 What types of systems are used for enterprise-wide knowledge management, and how do they provide value for businesses? 11.3 What are the major types of knowledge work systems, and how do they provide value for firms? 11.4 What are the business benefits of using intelligent techniques for knowledge management? Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved What is the Role of Knowledge Management Systems in Business? Knowledge management systems among fastest growing areas of software investment Information economy – 37 percent U.S. labor force: knowledge and information workers – 55 percent U.S. GDP from knowledge and information sectors Substantial part of a firm’s stock market value is related to intangible assets: knowledge, brands, reputations, and unique business processes Well-executed knowledge-based projects can produce extraordinary ROI Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Important Dimensions of Knowledge (1 of 2) Data, knowledge, and wisdom Tacit knowledge and explicit knowledge Important dimensions of knowledge – Knowledge is a firm asset. – Knowledge has different forms. – Knowledge has a location. – Knowledge is situational. Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Important Dimensions of Knowledge (2 of 2) Knowledge-based core competencies – Key organizational assets Knowing how to do things effectively and efficiently in ways others cannot duplicate is a prime source of profit and competitive advantage – Example: Having a unique build-to-order production system Organizational learning – Process in which organizations gain experience through collection of data, measurement, trial and error, and feedback Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved The Knowledge Management Value Chain (1 of 3) Knowledge management – Set of business processes developed in an organization to create, store, transfer, and apply knowledge Knowledge management value chain – Each stage adds value to raw data and information as they are transformed into usable knowledge  Knowledge acquisition  Knowledge storage  Knowledge dissemination  Knowledge application Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved The Knowledge Management Value Chain (2 of 3) Knowledge acquisition – Documenting tacit and explicit knowledge  Storing documents, reports, presentations, best practices  Unstructured documents (e.g., e-mails)  Developing online expert networks – Creating knowledge – Tracking data from TPS and external sources Knowledge storage – Databases – Document management systems – Role of management Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved The Knowledge Management Value Chain (3 of 3) Knowledge dissemination – Portals, wikis – E-mail, instant messaging – Search engines, collaboration tools – A deluge of information?  Training programs, informal networks, and shared management experience help managers focus attention on important information. Knowledge application – New business practices – New products and services – New markets Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.1 The Knowledge Management Value Chain Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Building Organizational and Management Capital: Collaboration, Communities of Practice, and Office Environments Developing new organizational roles and responsibilities for the acquisition of knowledge Chief knowledge officer executives Dedicated staff / knowledge managers Communities of practice (COPs) – Informal social networks of professionals and employees – Activities include education, online newsletters, sharing knowledge – Reduce learning curves of new employees Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Types of Knowledge Management Systems Enterprise-wide knowledge management systems – General-purpose firm-wide efforts to collect, store, distribute, and apply digital content and knowledge Knowledge work systems (KWS) – Specialized systems built for engineers, scientists, other knowledge workers charged with discovering and creating new knowledge Intelligent techniques – Diverse group of techniques such as data mining used for various goals: discovering knowledge, distilling knowledge, discovering optimal solutions Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.2 Major Types of Knowledge Management Systems Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved What Types of Systems Are Used for Enterprise-Wide Knowledge Management? Three major types of knowledge in an enterprise – Structured documents  Reports, presentations  Formal rules – Semistructured documents  E-mails, videos – Unstructured, tacit knowledge 80% of an organization’s business content is semistructured or unstructured Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved What Is Artificial Intelligence? (1 of 3) Grand vision – Computer hardware and software systems that are as “smart” as humans – So far, this vision has eluded computer programmers and scientists Realistic vision – Systems that take data inputs, process them, and produce outputs (like all software programs) and that can perform many complex tasks that would be difficult or impossible for humans to perform. Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved What Is Artificial Intelligence? (2 of 3) Examples: – Recognize millions of faces in seconds – Interpret millions of CT scans in minutes – Analyze millions of financial records – Detect patterns in very large Big Data databases – Improve their performance over time (“learn”) – Navigate a car in certain limited conditions – Respond to questions from humans (natural language); speech activated assistants like Siri, Alexa, and Cortana Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved What Is Artificial Intelligence? (3 of 3) Major Types of AI – Expert systems – Machine learning – Neural networks and deep learning networks – Genetic algorithms – Natural language Processing – Computer vision – Robotics Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Capturing Knowledge: Expert Systems Capture tacit knowledge in very specific and limited domain of human expertise Capture knowledge as set of rules Typically perform limited tasks – Diagnosing malfunctioning machine – Determining whether to grant credit for loan Used for discrete, highly structured decision making Knowledge base: Set of hundreds or thousands of rules Inference engine: Strategy used to search knowledge base – Forward chaining – Backward chaining Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.3 Rules in an Expert System Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Machine Learning How computer programs improve performance without explicit programming – Recognizing patterns – Experience – Prior learnings (database) – Supervised vs. unsupervised learning Contemporary examples – Google searches – Recommender systems on Amazon, Netflix Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Neural Networks Find patterns and relationships in massive amounts of data too complicated for humans to analyze “Learn” patterns by searching for relationships, building models, and correcting over and over again Humans “train” network by feeding it data inputs for which outputs are known, to help neural network learn solution by example from human experts. Used in medicine, science, and business for problems in pattern classification, prediction, financial analysis, and control and optimization Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.4 How a Neural Network Works Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.5 A Deep Learning Network Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Genetic Algorithms Useful for finding optimal solution for specific problem by examining very large number of possible solutions for that problem Conceptually based on process of evolution – Search among solution variables by changing and reorganizing component parts using processes such as inheritance, mutation, and selection Used in optimization problems (minimization of costs, efficient scheduling, optimal jet engine design) in which hundreds or thousands of variables exist Able to evaluate many solution alternatives quickly Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.6 The Components of a Genetic Algorithm Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Natural Language Processing Understand, and speak in natural language. Read natural language and translate Typically today based on machine learning, aided by very large databases of common phrases and sentences in a given language Example: Google Translate Spam filtering systems Customer call center interactions: What is the customer’s problem? What solutions worked in the past? Digital assistances: Sire, Alexa, Cortana, Google Assistant Not useful for an ordinary common sense human conversation but can be very useful in limited domains, e.g. interacting with your car’s heating system. Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Computer Vision Systems Digital image systems that create a digital map of an image (like a face, or a street sign), and recognize this image in large data bases of images in near real time Every image has a unique pattern of pixels Facebook’s DeepFace can identify friends in photos across their system, and the entire web Autonomous vehicles can recognize signs, road markers, people, animals, and other vehicles with good reliability Industrial machine (robot) vision Passport control at airports Identifying people in crowds Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Robotics Design, construction, and operation of machines that can substitute for humans in many factory, office, and home applications (home vacuums). Generally programmed to perform specific and detailed actions in limited domains, e.g. robots spray paint autos, and assemble certain parts, welding, heavy assembly movement. Used in dangerous situations like bomb disposal Surgical robots are expanding their capabilities Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Intelligent Agents Work without direct human intervention to carry out repetitive, predictable tasks – Deleting junk e-mail – Finding cheapest airfare Use limited built-in or learned knowledge base – Some are capable of self-adjustment, for example: Siri Chatbots Agent-based modeling applications: – Model behavior of consumers, stock markets, and supply chains; used to predict spread of epidemics Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.7 Intelligent Agents in P&G’s Supply Chain Network Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Enterprise Content Management Systems Help capture, store, retrieve, distribute, preserve documents and semistructured knowledge Bring in external sources – News feeds, research Tools for communication and collaboration – Blogs, wikis, and so on Key problem: developing taxonomy Digital asset management systems Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.8 An Enterprise Content Management System Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Locating and Sharing Expertise Provide online directory of corporate experts in well- defined knowledge domains Search tools enable employees to find appropriate expert in a company Social networking and social business tools for finding knowledge outside the firm – Saving – Tagging – Sharing web pages Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Learning Management Systems (LMS) Provide tools for management, delivery, tracking, and assessment of employee learning and training Support multiple modes of learning – CD-ROM, web-based classes, online forums, and so on Automates selection and administration of courses Assembles and delivers learning content Measures learning effectiveness Massively open online courses (MOOCs) – Web course open to large numbers of participants Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Knowledge Workers and Knowledge Work Knowledge workers – Researchers, designers, architects, scientists, engineers who create knowledge for the organization – Three key roles  Keeping organization current in knowledge  Serving as internal consultants regarding their areas of expertise  Acting as change agents, evaluating, initiating, and promoting change projects Knowledge work systems – Systems for knowledge workers to help create new knowledge and integrate that knowledge into business Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Requirements of Knowledge Work Systems Sufficient computing power for graphics, complex calculations Powerful graphics and analytical tools Communications and document management Access to external databases User-friendly interfaces Optimized for tasks to be performed (design engineering, financial analysis) Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Figure 11.9 Requirements of Knowledge Work Systems Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Examples of Knowledge Work Systems CAD (computer-aided design) – Creation of engineering or architectural designs – 3D printing Virtual reality systems – Simulate real-life environments – 3D medical modeling for surgeons – Augmented reality (AR) systems – VRML Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved What Are the Business Benefits of Using Intelligent Techniques for Knowledge Management? Intelligent techniques: Used to capture individual and collective knowledge and to extend knowledge base – To capture tacit knowledge: Expert systems, case-based reasoning, fuzzy logic – Knowledge discovery: Neural networks and data mining – Generating solutions to complex problems: Genetic algorithms – Automating tasks: Intelligent agents Artificial intelligence (AI) technology: – Computer-based systems that emulate human behavior Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved Copyright This work is protected by United States copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning. Dissemination or sale of any part of this work (including on the World Wide Web) will destroy the integrity of the work and is not permitted. The work and materials from it should never be made available to students except by instructors using the accompanying text in their classes. All recipients of this work are expected to abide by these restrictions and to honor the intended pedagogical purposes and the needs of other instructors who rely on these materials. Copyright © 2020, 2018, 2016 Pearson Education, Inc. All Rights Reserved