IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/ Edward de Bono, Creative Thinking Guru “Most executives, many scientists, and almost all business school graduates believe that if you analyze data, this will give you new ideas. Unfortunately, this belief is totally wrong. The mind can only see what it is prepared to see.” Edward de Bono, Creative Thinking Guru Chapter 7 Organizational Information Systems and Business Intelligence

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Learning Objectives Describe the concept of business intelligence and how it is used at the operational, managerial, and executive levels of an organization. 2. Explain the three components of business intelligence: information and knowledge discovery, business analytics, and information visualization.

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Learning Objectives Describe the concept of business intelligence and how it is used at the operational, managerial, and executive levels of an organization. 2. Explain the three components of business intelligence: information and knowledge discovery, business analytics, and information visualization.

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Business Intelligence (BI) 8-4 Business Intelligence (BI) is the use of information systems to gather and analyze information from internal and external sources in order to make better business decisions. BI is used to integrate data from disconnected:  Reports  Databases  Spreadsheets Integrated data helps to monitor and fin-tune business processes

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 BI: Responding to Threats and Opportunities 8-5 BI can help with reacting to various threats and opportunities, including:  Unstable markets  Global threats  Fierce competition  Short product life cycles  Wider choices for consumers

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 BI: Continuous Planning 8-6 Organizations need to continuously monitor and analyze business processes Results lead to ongoing adjustments Involves decision makers from all levels

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Decision-Making Levels of an Organization 8-7

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Operational Level 8-8 Day-to-day business processes Interactions with customers Decisions:  Structured  Recurring  Can often be automated using IS BI used to:  Optimize processes  Understand causes of performance problems

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Operational Level (cont’d) 8-9

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Managerial Level 8-10 Functional managers  Monitor and control operational-level activities  Focus: effectively utilizing and deploying resources  Goal: achieving strategic objectives Managers’ decisions  Semistructured  Moderately complex  Time horizon of few days to few months BI can help with:  Performance analytics  Forecasts  Providing key performance indicators on dashboards

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Managerial Level (cont’d) 8-11

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Executive Level 8-12 The president, CEO, vice presidents, board of directors Decisions  Unstructured  Long-term strategic issues  Complex and nonroutine problems with long-term ramifications BI is used to:  Obtain aggregate summaries of trends and projections  Provide KPIs across the organization

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Executive Level (cont’d) 8-13

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Providing Inputs into BI Applications 8-14 Decisions made by different departments need to be based on the same underlying data “Single version of the truth”  BI systems access multiple databases or data warehouses  Data aggregated from operational systems  E.g., Transaction processing systems

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Transaction Processing Systems (TPS) 8-15 Operational level Purpose:  Processing of business events and transactions  Increase efficiency  Automation  Lower costs  Increased speed and accuracy Examples:  Payroll processing  Sales and order processing  Inventory management  Product purchasing, receiving, and shipping  Accounts payable and receivable

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of a TPS 8-16

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of a TPS: Inputs 8-17 Source documents  Different data entry methods

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of a TPS: Processing 8-18 Online processing  Immediate results Batch processing  Transactions collected and later processed together  Used when immediate notification not necessary

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of a TPS: Outputs 8-19 Counts, summary reports Inputs to other systems Feedback to systems operator

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Summary of TPS Characteristics 8-20

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Learning Objectives Describe the concept of business intelligence and how it is used at the operational, managerial, and executive levels of an organization. 2. Explain the three components of business intelligence: information and knowledge discovery, business analytics, and information visualization.

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Business Intelligence Components 8-22 Three types of tools  Information and knowledge discovery  Business analytics  Information visualization Information and Knowledge Discovery  Search for hidden relationships  Hypotheses are tested against existing data  E.g., customers with a household income over $150,000 are twice as likely to respond to our marketing campaign as customers with an income of $60,000 or less

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Business Intelligence Components 8-23

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Online Analytical Processing (OLAP) 8-24 Complex, multidimensional analyses of data beyond simple queries OLAP data concepts:  Measures (or facts) —values or numbers the user wants to analyze  Categorized data  Dimensions  Provide a way to summarize data  Dimensions are organized as hierarchies, allowing to drill down or roll up Example: Sales (measure) could be analyzed by product or time (dimensions)

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 OLAP Cubes 8-25 OLAP cube: data structure allowing for analysis of multiple dimensions  Data can be analyzed by more than three dimensions

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Data Slicing and Dicing 8-26 Slicing and dicing of data allows for analyzing subsets of the dimensions  E.g., sales by product type and region only for the second quarter of 2009, or desktop sales in the western region

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Data Mining 8-27 Used for discovering “hidden” predictive relationships in the data  Patterns, trends, or rules  E.g, identification of profitable customer segments or fraud detection  Any predictive models should be tested against “fresh” data Data-mining algorithms are run against large data warehouses  Data reduction helps to reduce the complexity 0f data and speed up analysis

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Association Discovery 8-28 Technique used to find associations or correlations among sets of items  Support and confidence indicate if findings are meaningful Sequence Discovery  Association discovery over time

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Clustering and Classification 8-29 Clustering  Grouping of related records based on similar values for attributes  Groups are not known beforehand  E.g., clustering frequent fliers based on segments flown Classification  Groups (classes) are known beforehand  Records are segmented into the different groups  Often using decision trees

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Text Mining 8-30 Extracting information from textual documents Can be applied to a variety of documents:  Web sites  Transcripts  Phone calls  Interviews  Student college applications

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Web Mining 8-31 Web usage mining  Determine patterns in customers’ usage data  Clickstream data—recording of the users’ paths through a Web site  Analyze “stickiness”—ability to attract and keep visitors Web content mining  Extract textual information from Web documents using Web crawlers  Analyze using text mining systems

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Presenting Results 8-32

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Business Analytics 8-33 BI applications to support human and automated decision making  Information systems to support human decision making  Intelligent systems  Tools for enhancing organizational collaboration

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Management Information Systems 8-34 Managerial level Purpose:  Produce reports  Support of midlevel managers’ decisions Examples:  Sales forecasting  Financial management and forecasting  Manufacturing, planning and scheduling  Inventory management and planning  Advertising and product pricing

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of an MIS 8-35

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Summary of MIS Characteristics 8-36

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Executive Information Systems 8-37 Aka Executive support system Executive level Purpose:  Aid in executive decision making  Provide information in highly aggregated form Examples:  Executive-level decision making  Long-range and strategic planning  Monitoring of internal and external events and resources  Crisis management  Staffing and labor relations

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Hard vs. Soft Data 8-38 EIS can provide both hard and soft data  Hard data  Facts and numbers  Generated by TPS & MIS  Soft data  Nonanalytical information E.g., latest news stories  Web-based news portals Customizable Delivery to different media

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Yahoo Finance Provides Soft Data 8- 39

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of an EIS 8-40

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Summary of EIS Characteristics 8-41

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Decision Support Systems (DSS) 8-42 Decision-making support for recurring problems Used mostly by managerial level employees (can be used at any level) Interactive decision aid What-if analyses  Analyze results for hypothetical changes  Example: Microsoft Excel

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of a DSS 8-43

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Common DSS Models 8-44

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Summary of DSS Characteristics 8-45

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Functional Area Information Systems 8-46 Cross-organizational-level IS Support specific functional area Focus on specific set of activities

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Business Processes Supported by Functional Area Information Systems 8-47

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Organizational Functions and Representative Information Systems 8-48

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Collaboration Systems 8-49 Increased need for flexible teams Virtual teams—dynamic task forces  Forming and disbanding as needed  Fluctuating team size  Easy, flexible access to other team members Need for new collaboration technologies

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Groupware 8-50 Used to enable more effective team work  Distinguished along two dimensions  Time (synchronous vs. asynchronous)  Place (face to face vs. distributed)

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Benefits of Groupware 8-51

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Asynchronous Groupware 8-52 Various tools are commonplace in organizations  , newsgroups, and mailing lists, work flow automation systems, intranets, group calendars, and collaborative writing tools. Lotus Notes (released in 1989) still considered industry leader

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Synchronous Groupware 8-53 Shared whiteboards, online chat, videoconferencing Electronic meeting systems  Help groups have better meetings Uses of EMS  Strategic planning sessions  Marketing focus groups  Brainstorming sessions  Business process management  Quality improvement Web-based implementations

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Example: Electronic Meeting System 8-54

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Videoconferencing 8-55 Used to replace traditional meetings Dedicated videoconferencing  Highly realistic but very expensive Desktop videoconferencing: Low-cost alternative  Web cam  Enablers  Increase in processing power  Internet connection speed

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Intelligent Systems 8-56 Artificial intelligence Simulation of human intelligence Reasoning and learning, as well as gaining sensing capabilities, such as seeing, hearing, walking, talking, and feeling

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Example: Artificial Intelligence 8-57 Source:

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Intelligent Systems 8-58 Intelligent system  Sensors, software and computers  Emulate and enhance human capabilities Three types  Expert systems  Neural networks  Intelligent agents

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Expert Systems 8-59 Use reasoning methods Manipulate knowledge rather than information System asks series of questions Inferencing/pattern matching  Matching user responses with predefined rules  If-then format Fuzzy logic  Represent rules using approximations

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Example: Expert System 8-60 WebMD.com’s expert system to make a medical recommendation

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Architecture of an Expert System 8-61

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Summary of ES Characteristics 8-62

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Neural Networks 8-63 Approximation of human brain functioning Training to establish common patterns  Based on past information New data compared to patterns Example: loan processing

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Example: Neural Network System 8-64

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Intelligent Agent Systems 8-65 Program working in the background Bot (software robot) Provides service when a specific event occurs

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Types of Intelligent Agent Systems 8-66 User agents  Performs a task for the user Buyer agents (shopping bots)  Search for the best price Monitoring and sensing agents  Keep track of information and notifies users when it changes Data-mining agents  Continuously browse data warehouses to detect changes Web crawlers (aka Web spiders)  Continuously browses the Web Destructive agents  Designed to farm addresses or deposit spyware

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Knowledge Management Systems 8-67 Generating value from knowledge assets Collection of technology-based systems Knowledge assets  Skills, routines, practices, principles, formulas, methods, heuristics, and intuitions  Used to improve efficiency, effectiveness, and profitability  Documents storing both facts and procedures  Examples: Databases, manuals, diagrams, books, and so on

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Knowledge Asset Categories 8-68 Explicit knowledge assets  Can be documented Tacit knowledge assets  Located in one’s mind  Often reflect an organization’s best practices

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Benefits and Challenges of Knowledge-Based Systems 8-69

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Utilizing Knowledge Management Systems Challenge:  People using the system are spread across organization  Problems people face may have been solved by someone else within the same organization Goal:  Facilitate exchange of needed knowledge between separate “islands”  Social network analysis  Knowledge portals

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Web-Based Knowledge Portals 8-71 Knowledge repository

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Information Visualization 8-72 Display of complex data relationships using a graphical methods  Enables managers to quickly grasp results of analyses  Visual analytics  Dashboards  Geographic information systems

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Visual Analytics Interpreting complex output from BI systems is challenging Visual analytics combines various analysis techniques and interactive visualization  Combination of  Human intelligence and reasoning capabilities  Technology’s retrieval and analysis capabilities  Helps to make sense of “noisy” data or unexpected patterns 8-73

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Digital Dashboards 8-74

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Geographic Information System (GIS) 8-75 Use of geographically referenced information  Finding optimal location for a new store  Identification of areas too wet to fertilize (see figure)  Locating target customers  Infrastructure design

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Geographic Information System Uses 8-76 Customer dot mapping Trade area analysis Thematic mapping

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 End of Chapter Content 8-77

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Opening Case —Managing in the Digital World: Providing Business Intelligence to eBay.com 8-78 Founded in million users Sales of $30 billion (2007) Problems  Shill bidding  Sellers who don’t send  etc. How to determine patterns of fraudulent behavior?

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Bad Intelligence—Anonymous Hackers Punish the Wrong Person 8-79 In 2008, The Church of Scientology was attacked by the hacker group “Anonymous” The attack was due to retribution for the church removing Tom Cruise interviews on the Web A hacker war with pro-Scientology hackers started  An innocent couple in California was accidentally targeted as pro-Scientology hackers  Phone number posted online  Social security number posted online  Threatening phone calls

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 The Demise of Broadcast TV % of aren’t watching TV on TV Online recording and DVR are the media of choice The broadcast industry needs to respond

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Too Much Intelligence? RFID and Privacy 8-81 RFID tags  Latest in technological tracking devices  Information imprinted on a tag  Tag generates signature signal  Special RFID reader interprets signal E.g., used by pharmaceutical industry to prevent counterfeits Privacy concerns  Someone with an RFID reader could see where you bought a product and what you paid for it  Devices needed to erase tracking information

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Instant Messaging at Work 8-82 Using public IM has disadvantages for organizations:  Security cannot be assumed  Data resides on the provider’s server  Access to the network cannot be blocked Alternatives:  Internal IM network  Secure message transfer  Ability to handle thousands of employee accounts  Platform compatibility  Access from outside of the WAN  Proper access rights  IM hosting service  Data resides on provider’s server  Privacy concerns

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Very Smart Phones 8-83 Turning the Mobile Phone into a personal assistant  Magitti  Developed by Palo Alto Research Center (PARC)  Combines time of day, location, past behaviors, and text messages to suggest activities  MIT Media Lab has similar projects to predict behavior from GPS locators, call logs, etc.  iPhone has various sensors built in  All it needs is applications being developed to utilize hardware capabilities

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Adobe’s John Warnock and Chuck Geschke Warnock and Geschke worked together at Xerox’ Palo Alto Research Center (PARC) Developed PostScript  Technology that simplifies printing documents directly from computers Warnock and Geschke left Xerox in 1982 to found Adobe Systems, Inc. Geschke was kidnapped in 1992 Adobe is one of the biggest software companies in the world Products include:  Acrobat, ColdFusion, Dreamweaver, Flash, Photoshop, and many others 8-84

IS Today (Valacich & Schneider) Copyright © 2010 Pearson Education, Inc. Published as Prentice Hall 11/28/2015 Healthcare 8-85 Healthcare increasingly reliant on information technology  Many doctors carry PDAs/laptops to access patient records or drug information Electronic patient records moving towards the Web  Google health and Microsoft HealthVault Other applications  Diagnosis and monitoring  EEG, EKG, computer tomography  Digital x-rays  Tele-medicine  Remote diagnosis and surgery