Enhancing Decision Making



Similar documents
Chapter 10 Improving Decision Making and Managing Knowledge

Introduction to Management Information Systems

CHAPTER 12. Business Intelligence

Chapter Managing Knowledge in the Digital Firm

Cis330. Mostafa Z. Ali

QAD Business Intelligence

Business Intelligence, Analytics & Reporting: Glossary of Terms

INFO What are business processes? How are they related to information systems?

CHAPTER 12. Business Intelligence

CHAPTER OUTLINE LEARNING OBJECTIVES 8/14/2012. Business Intelligence

Intelligent Government From Data to Decision. Robert Lindsley Oracle, Public Sector Technology Group

Chapter 1 DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE

E-Business: How Businesses Use Information Systems

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers

Chapter 6 - Enhancing Business Intelligence Using Information Systems

HROUG. The future of Business Intelligence & Enterprise Performance Management. Rovinj October 18, 2007

Global E-business and Collaboration

Top 5 Transformative Analytics Applications in Retail

Information systems for management ดร. สล ล บ ญพราหมณ 2558

Evolution of Information System

Enterprise Information Systems

FINANCIAL REPORTING WITH BUSINESS ANALYTICS

Vendor briefing Business Intelligence and Analytics Platforms Gartner 15 capabilities

<Insert Picture Here> Oracle Business Intelligence

Picturing Performance: IBM Cognos dashboards and scorecards for retail

Business Intelligence Solutions for Gaming and Hospitality

Decision Support and Business Intelligence Systems. Chapter 1: Decision Support Systems and Business Intelligence

Business Intelligence and Decision Support Systems

Data Management Practices for Intelligent Asset Management in a Public Water Utility

Improving Decision Making and Managing Knowledge

Course DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Implementing Data Models and Reports with Microsoft SQL Server

Introduction to Business Intelligence

Data Analytics: Exploiting the Data Warehouse

III JORNADAS DE DATA MINING

Business Intelligence Solutions. Cognos BI 8. by Adis Terzić

Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

MANAGEMENT INFORMATION. Prepared By: Hardeep Singh

Implementing Data Models and Reports with Microsoft SQL Server 20466C; 5 Days

ProClarity Analytics Family

Class 2. Learning Objectives

SalesLogix Advanced Analytics

Retail Analytics The perfect business enhancement. Gain profit, control margin abrasion & grow customer loyalty

Chapter 5. Warehousing, Data Acquisition, Data. Visualization

Chapter 9. Video Cases. 6.1 Copyright 2014 Pearson Education, Inc. publishing as Prentice Hall

Sales Performance Management SALES DEMAND PLANNING SALES SALES & OPERATIONS ACCOUNT ANALYSIS & MANAGEMENT PLANNING PLANNING MANAGEMENT

Global E-Business: How Businesses Use Information Systems

PRODUCT INFORMATION. Know Your Business Better.

CHAPTER 12: INFORMATION SYSTEMS IN BUSINESS

W H I T E P A P E R B u s i n e s s I n t e l l i g e n c e S o lutions from the Microsoft and Teradata Partnership

Dashboard Reporting Business Intelligence

Making confident decisions with the full spectrum of analysis capabilities

BUS 516 Computer Information Systems. Global E-business and Collaboration

A Look at Self Service BI with SAP Lumira Natasha Kishinevsky Dunn Solutions Group SESSION CODE: 1405

The Right BI Tool for the Job in a non- SAP Applica9on Environment

Using Business Intelligence to Achieve Sustainable Performance

SAP Customer Success Story UniCredit Bulbank. UniCredit Bulbank: 360-degree view

Microsoft Business Intelligence

Management Accountants and IT Professionals providing Better Information = BI = Business Intelligence. Peter Simons peter.simons@cimaglobal.

Analytics with Excel and ARQUERY for Oracle OLAP

Turnkey Hardware, Software and Cash Flow / Operational Analytics Framework

1. Global E Business and Collaboration. Lecture 2 TIM 50 Autumn 2012

Alexander Nikov. 2. Information systems and business processes. Learning objectives

Cincom Business Intelligence Solutions

Digging for Gold: Business Usage for Data Mining Kim Foster, CoreTech Consulting Group, Inc., King of Prussia, PA

INFORMATION SYSTEMS FORMATION 2 EXAMINATION - AUGUST 2015

BUSINESS INTELLIGENCE TOOLS FOR DATA ANALYSIS AND DECISION MAKING

Business Intelligence

Business Intelligence

{Businesss. Intelligence. Overview. Dashboard Manager

Executive Summary...2. Introduction...3. Definitions...3. Why Operational Performance Optimization...4

QlikView for Telecommunications. Delivering Unprecedented Customer Intelligence

Implementing a Customer Lifetime Value Predictive Model: Use Case

An Enterprise Framework for Business Intelligence

Methodology Framework for Analysis and Design of Business Intelligence Systems

Selecting the Right SAP BusinessObjects BI Client Product based on your business requirements for SAP BW Customers

Microsoft Implementing Data Models and Reports with Microsoft SQL Server

Day 7 Business Information Systems-- the portfolio. Today s Learning Objectives

Making Business Intelligence Relevant for Mid-sized Companies. Improving Business Results through Performance Management

How To Turn Big Data Into An Insight

Microsoft Services Exceed your business with Microsoft SharePoint Server 2010

Information Systems Roles in the Value Chain Customer Relationship Management (CRM) Systems 09/11/2015. ACS 3907 E-Commerce

ACS 3907 E-Commerce. Instructor: Kerry Augustine November 10 th Bowen Hui, Beyond the Cube Consulting Services Ltd.

Better Business Analytics with Powerful Business Intelligence Tools

How To Use Microsoft Dynamics Gpa

E-Business: Use of Information Systems

SMB Intelligence. Reporting

ACS 3907 E-Commerce. Instructor: Kerry Augustine March 3 rd Bowen Hui, Beyond the Cube Consulting Services Ltd.

How To Understand Business Intelligence

White Paper February IBM Cognos Supply Chain Analytics

OBIEE 11g Pre-Built Dashboards from Oracle Courtesy: Oracle OBIEE 11g Deployment on Vision Demo Data FINANCIALS

Is Business Intelligence an Oxymoron?

Business Analytics and Data Visualization. Decision Support Systems Chattrakul Sombattheera

Business Intelligence

SIGNIFICANCE OF BUSINESS INTELLIGENCE APPLICATIONS FOR BETTER DECISION MAKING & BUSINESS PERFORMANCE

DISCOVER MERCHANT PREDICTOR MODEL

DATA VISUALIZATION: When Data Speaks Business PRODUCT ANALYSIS REPORT IBM COGNOS BUSINESS INTELLIGENCE. Technology Evaluation Centers

ENTERPRISE BI AND DATA DISCOVERY, FINALLY

Big Data & Analytics for Semiconductor Manufacturing

Oracle BI Application: Demonstrating the Functionality & Ease of use. Geoffrey Francis Naailah Gora

Transcription:

Enhancing Decision Making

Content Describe the different types of decisions and how the decision-making process works. Explain how information systems support the activities of managers and management decision making. Explain how business intelligence and business analytics support decision making. Explain how different decision-making constituencies in an organization use business intelligence. Describe the role of information systems in helping people working in a group make decisions more efficiently. 2

Types of decisions Business value of improved decision making Improving hundreds of thousands of small decisions adds up to large annual value for the business Types of decisions: Unstructured: Decision maker must provide judgment, evaluation, and insight to solve problem Structured: Repetitive and routine; involve definite procedure for handling so they do not have to be treated each time as new Semistructured: Only part of problem has clear-cut answer provided by accepted procedure 3

Decision making at the different levels Senior managers: Make many unstructured decisions For example: Should we enter a new market? Middle managers: Make more structured decisions but these may include unstructured components For example: Why is order fulfillment report showing decline in Minneapolis? Operational managers, rank and file employees Make more structured decisions For example: Does customer meet criteria for credit? 4

INFORMATION REQUIREMENTS OF KEY DECISION MAKING GROUPS IN A FIRM FIGURE 12-1 Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements. 5

Decision-making process The four stages of the decision-making process 1. Intelligence Discovering, identifying, and understanding the problems occurring in the organization 2. Design Identifying and exploring solutions to the problem 3. Choice Choosing among solution alternatives 4. Implementation Making chosen alternative work and continuing to monitor how well solution is working 6

STAGES IN DECISION MAKING FIGURE 12-2 7

Roles of Information Systems Information systems can only assist in some of the roles played by managers Classical model of management: five functions Planning, organizing, coordinating, deciding, and controlling More contemporary behavioral models Actual behavior of managers appears to be less systematic, more informal, less reflective, more reactive, and less well organized than in classical model 8

Mintzberg s behavioral model of managers Mintzberg s 10 managerial roles Interpersonal roles 1. Figurehead 2. Leader 3. Liaison Informational roles 4. Nerve center 5. Disseminator 6. Spokesperson Decisional roles 7. Entrepreneur 8. Disturbance handler 9. Resource allocator 10. Negotiator 9

Reasons why investments in IS do not always produce positive results Three main reasons why investments in information technology do not always produce positive results 1. Information quality High-quality decisions require high-quality information 2. Management filters Managers have selective attention and have variety of biases that reject information that does not conform to prior conceptions 3. Organizational inertia and politics Strong forces within organizations resist making decisions calling for major change 10

High-velocity automated decision making High-velocity automated decision making Made possible through computer algorithms precisely defining steps for a highly structured decision Humans taken out of decision For example: High-speed computer trading programs Trades executed in 30 milliseconds Responsible for Flash Crash of 2010 Require safeguards to ensure proper operation and regulation 11

Concept of Business Intelligence and Analytics Business intelligence Infrastructure for collecting, storing, analyzing data produced by business Databases, data warehouses, data marts Business analytics Tools and techniques for analyzing data OLAP, statistics, models, data mining Business intelligence vendors Create business intelligence and analytics purchased by firms 12

BUSINESS INTELLIGENCE AND ANALYTICS FOR DECISION SUPPORT 13

Elements in the business intelligence environment Six elements in the business intelligence environment 1. Data from the business environment 2. Business intelligence infrastructure 3. Business analytics toolset 4. Managerial users and methods 5. Delivery platform MIS, DSS, ESS 6. User interface 14

Functionalities of BI systems Business intelligence and analytics capabilities Goal is to deliver accurate real-time information to decision makers Main functionalities of BI systems 1. Production reports 2. Parameterized reports 3. Dashboards/scorecards 4. Ad hoc query/search/report creation 5. Drill down 6. Forecasts, scenarios, models 15

How business intelligence is used Business intelligence users 80% are casual users relying on production reports Senior executives Use monitoring functionalities Middle managers and analysts Ad-hoc analysis Operational employees Prepackaged reports For example: sales forecasts, customer satisfaction, loyalty and attrition, supply chain backlog, employee productivity 16

BUSINESS INTELLIGENCE USERS 17

Functionalities of BI systems Production reports Most widely used output of BI suites Common predefined, prepackaged reports Sales: Forecast sales; sales team performance Service/call center: Customer satisfaction; service cost Marketing: Campaign effectiveness; loyalty and attrition Procurement and support: Supplier performance Supply chain: Backlog; fulfillment status Financials: General ledger; cash flow Human resources: Employee productivity; compensation 18

Functionalities of BI systems Predictive analytics Use variety of data, techniques to predict future trends and behavior patterns Statistical analysis Data mining Historical data Assumptions Incorporated into numerous BI applications for sales, marketing, finance, fraud detection, health care Credit scoring Predicting responses to direct marketing campaigns 19

Big data analytics Big data analytics Big data: Massive datasets collected from social media, online and in-store customer data, and so on Help create real-time, personalized shopping experiences for major online retailers Hunch.com, used by ebay Customized recommendations Database includes purchase data, social networks Taste graphs map users with product affinities 20

BI applications Additional BI applications Data visualization and visual analytics tools Help users see patterns and relationships that would be difficult to see in text lists Rich graphs, charts Dashboards Maps Geographic information systems (GIS) Ties location-related data to maps Example: For helping local governments calculate response times to disasters 21

Strategies for developing BI and BA capabilities Two main management strategies for developing BI and BA capabilities 1. One-stop integrated solution Hardware firms sell software that run optimally on their hardware Makes firm dependent on single vendor switching costs 2. Multiple best-of-breed solution Greater flexibility and independence Potential difficulties in integration Must deal with multiple vendors 22

Decision systems for different levels Operational and middle managers Use MIS (running data from TPS) for: Routine production reports Exception reports Super user and business analysts Use DSS for: More sophisticated analysis and custom reports Semistructured decisions 23

Decision support systems Decision support systems Use mathematical or analytical models Allow varied types of analysis What-if analysis Sensitivity analysis Backward sensitivity analysis Multidimensional analysis / OLAP For example: pivot tables 24

SENSITIVITY ANALYSIS 25

A PIVOT TABLE THAT EXAMINES CUSTOMER REGIONAL DISTRIBUTION AND ADVERTISING SOURCE 26

Executive Support Systems ESS: decision support for senior management Help executives focus on important performance information Balanced scorecard method: Measures outcomes on four dimensions: 1. Financial 2. Business process 3. Customer 4. Learning and growth Key performance indicators (KPIs) measure each dimension 27

THE BALANCED SCORECARD FRAMEWORK 28

Decision support for senior management (cont.) Decision support for senior management (cont.) Business performance management (BPM) Translates firm s strategies (e.g., differentiation, low-cost producer, scope of operation) into operational targets KPIs developed to measure progress toward targets Data for ESS Internal data from enterprise applications External data such as financial market databases Drill-down capabilities 29

Group Decision Support Systems Group decision support systems (GDSS) Interactive system to facilitate solution of unstructured problems by group Specialized hardware and software; typically used in conference rooms Overhead projectors, display screens Software to collect, rank, edit participant ideas and responses May require facilitator and staff Enables increasing meeting size and increasing productivity Promotes collaborative atmosphere, anonymity Uses structured methods to organize and evaluate ideas 30