CHAPTER 4 Decisions and decision support 1 Find or recognize the problem need or opportunity 2 Consider ways of solving the problem 3 Examine the merits of each solution and choose the best one 4 Carry out the chosen solution and monitor the results Types of decisions you face the right answer right answer 1 Structured decision processing a certain information a specific way so you always get 2 Non structured decision may be several right answers without a sure way to get the 3 Recurring decision happens repeatedly 4 Nonrecurring decision ad hoc one you make infrequently Decision support system DSS A highly flexible and interactive system that is designed to support decision making when the problem is not structured results of the analysis DSS helps you analyze but you know how to solve the problem and how to use the Components of DSS management syste DSS to use 1 Model management component consists of both the DSS models and the model 2 Data management component stores and maintains the information that you want your 3 User interface management component allows you to communicate with the DSS Geographic information system GIS Designed specifically to analyze spatial information Spatial information is any information in map form Businesses use GIS software to analyze information generate business intelligence and make decisions Data mining tools and models Business need IT based analytic tools 1 Database and DBMS 2 Query and reporting tools 3 Multidimensional analysis tools 4 Digital dashboards 5 Statistical tools 6 GISs 7 Specialized analytics 8 Artificial intelligence Data mining tools and models support effectiveness Association dependence modeling cross selling opportunities recommendation engine Clustering groups of entities that are similar Classification use historical data to derive future inferences Regression find corollary and often casual relationships between data sets Summarization basic but powerful Predictive analytics highly computational data mining technology that uses information and business intelligence to build a predictive model for a given business application Insurance retail healthcare Prediction goal The question you want addressed by the predictive analytics model Prediction indicator Specific measurable value based on an attribute of the entity under consideration Predictive analytics example Prediction foal what customers are most likely to respond to a social media campaign within 30 days by purchasing at least 2 products in the advertised product line Prediction indicators 1 Frequency of purchases 2 Proximity of date of last purchase 3 Presence on FB and twitter 4 Number of multiple product purchases Text analytics use statistical AI and linguistic technologies to convert textual information into structured information Gaylord hotels use text analytics to make sense of customer satisfaction surveys Text analytics support 1 Lecical analysis word frequency distributions 2 Named entity recognition identifying peoples places and things 3 Disambiguation meaning of a named entity recognition 4 Conference handling of different noun phrases that refer to the same object 5 Sentiment analyss discerning subjective business intelligence such as mood opinion and emotion Endless analytics 1 Web analytics understanding and optimizing web page usage Search engine optimization SEO improving the visibility of a web site using tags and key terms 2 HR analytics analysis of human resource and talent management data 3 Marketing analytics analysis of marketing related data to improve product placement marketing mix 4 RM analytics analysis of CRM data to improve sales force automation customer service and support 5 Social media analytics Analysis of social media data to better understand customer organization interaction dynamics 6 Mobile analytics analysis of data related to the use of mobile devices to support mobile computing and m commerce Artificial intelligence the science of making machines imitate human thinking and behavior can replace human decision making in some instances Expert systems an artificial intelligence system that applies reasoning capabilities to reach a conclusion used for 1 Expert systems 2 Genetic algorithms 3 Neural networks 4 Agent based technologies 1 Diagnostics problems 2 Prescriptive problems What expert systems can and cant do Can 1 Reduce errors 2 3 Cant improve customer service reduce costs 1 Use common sense 2 Automate all processes Neural networks ANN an artificial intelligence system that is capable of finding and differentiating patterns Neural networks can 1 Learn to adjust to new circumstances on their own 2 Take part in massive parallel processing 3 Function without complete information 4 Cope with huge volumes of information 5 Analyze nonlinear relationships Fuzzy logic a mathematical method of handling imprecise or subjective information Used to make ambiguous information such as short usable in computer systems Applications 1 Google search engine 2 Anti block brakes 3 Washing machines Genetic algorithms an artificial intelligence systems that mimics the evolutionary survival of the fittest process to generate increasingly better solutions to a problem Genetic Algorithms examples 1 Staples determine optimal package design characteristics 2 Boeing design aircraft parts such as fan blades 3 Many retailers better manage inventory and optimizing display areas Genetic algorithms can until it finds optimal solution 1 Take thousands or even millions of possible solutions and combine or recombine them 2 Works in environments where no model of how to find the right solutions exist Agent based technology Piece of software that acts on your behalf performing tasks assigned to it Types of agent based technologies 1 Autonomous agent can adapt and alter the manner in which it works 2 distribute agent works on multiple distinct computer systems 3 mobile agent can relocate itself onto different computer systems 4 cc 5 Multi agent systems group of intelligent agents that can work independently and also together to perform a task Types of intelligent agents Information agents search for information and bring it back 1 2 Monitoring and surveillance agents constantly observe and report on some entity of interest a network or manufacturing equipment 3 User agents take action on your behalf 4 Data mining agents operate in a data warehouse discovering info Multi agent systems and biomimicry organizational situations biomimicry learning from