Business Intelligence Introduction & Overview

1. Business IntelligenceIntroduction & Overview

2. Analyzing Drill down, exception reports, root-cause analysis, multidimensional analysis Reporting Detailed operational data Sharing standardized reports ? Monitoring Dashboards, scorecards and alerts Planning Create plans, models and scenarios, which are then fed back into the monitoring layer and encoded as targets and thresholds. What is Business Intelligence “A broad category of applications and technologies for gathering, storing, analyzing, sharing andproviding accessto data to help enterprise users make better business decisions”- Gartner “No matter where you start, you should be able to move up and down layers seamlessly without awkward context shifts to gather insights, take action and optimize performance” - TDWI

3. BI Defined: Information Driving Organizational Performance Business intelligence is an umbrella term for Applications Infrastructure, platforms, tools Best practices which enable the analysis of information in order to optimize decisions and manage performance. Performance Decisions Analysis Information

4. What Questions can BI answer? • Where are we? • What were our sales this month? • Where are we going? • Are our sales trending up or down? • Why is this happening? • Why are sales going down? • What is going to happen in the future? • Forecasting / What If analysis • How can I plan for the future? • Planning / Goal Setting

5. Operations ERP Reporting/Analysis KPI tracking Maximizing profits Risk Management Activity Based Costing Logistics Customer Relationships Sales forecasting Segmentation Cross-selling CRM analysis Campaign planning Customer profitability Where is BI utilized?

6. The Simple Business Intelligence Model • Collect data using a wide variety of sources and formats • Organize information (and resources) for multiple uses and users • Judge the value (of information and resources) • Assist in the analysis process by determining the pertinence, reliability, and validity of information gathered • Disseminate information, but communicate intelligence that leads to ACTION • Weigh the options; consider the alternatives

7. Business Intelligence (BI) • Time savings • Single version of truth • Improved strategies and plans • Improved tactical decisions • More efficient processes • Cost savings • Faster, more accurate reporting • Improved decision making • Improved customer service • Increased revenue • The Benefits of BI

8. Main BI Topics 8 Data warehousing – Making historical data available for analytics Data preparation – Extraction, transformation and loading Query - a collection of specifications that enables you to focus on a particular set of data. Online Analytical Processing (OLAP) - a capability of information systems that supports interactive examination of large amounts of data from many perspectives. Reporting - generates aggregated views of data to keep the management informed about the state of their business. Data mining - extraction of knowledge by utilizing software that can isolate and identify previously unknown patterns or trends in large amounts of data.

9. Business Intelligence Business Analytics • BI Applications: • Data warehousing • Data mining • BPM • OLAP • etc. Executives Managers Operators Data BI Users Business Environment Data Decisions

10. BI Product Providers Microsoft SAS IBM / SPSS Oracle SyBase Business Objects

11. The Different Users of Business Intelligence • There are many different users who can benefit from business intelligence • Executives – Those who focus on the overall business • Business Decision Makers – Usually focused on single areas of the business (finance, HR, manufacturing, and so forth) • Information Workers – Typically managers or staff working in the back office • Line Workers – Employees who might use BI without knowing it • Analysts – Employees who will perform extensive data analysis

12. Business Scorecards • This screenshot shows a couple of simple scorecards. • Scorecards can contain KPIs that can be expanded or collapsed, and they can contain different indicators to show the strength or health of a KPI. • These scorecards can also be filtered to narrow down products, regions of the world, and so forth.

13. The Purpose of a Scorecard • A scorecard should give an executive a visual representation of the health of an organization in a single glance • The scorecard is of sufficiently high level to represent major business operations and their goals • The data in a scorecard should be as recent as possible to make them more actionable

14. What is a Balanced Scorecard? A method of measuring activities and outcomes for effective performance management

15. Activity & Outcome Measures • Activity Measures • Internal Business Process Perspective • Learning and Growth Perspective • Outcome Measures • Customer Perspective • Financial Perspective

16. Customer Perspective New Hire Termination % Quality of Hire Cycle Time to Hire Voluntary Turnover % Employee Satisfaction Score Internal Business Process Perspective HR Headcount per 100 FTE Unscheduled Overtime % Deficient Punch % Lost-time injuries per 100 FTE Self-Service Participation % Scheduling Effectiveness % ACTIVITY MEASURES OUTCOME MEASURES Learning & Growth Perspective Training Hours/FTE Productivity Gain per Training Hour OSHA Events/FTE Career Path Ratio Improving Performer Ratio Position Tenure Skill Match Ratio Financial Perspective Non-productive Labor Cost % Average Cost per Claim Cost per Hire HR Expenses per 100 FTE Accrual Liability per FTE Overtime Pay Ratio Bonus Ratio % Balanced Scorecard Performance Measures

17. What are the Challenges? • Identifying which performance measures are relevant for each scorecard recipient • Balancing the weight applied to each measure in proportion to overall performance • Compiling and staging the source data • Designing a dynamic architecture to minimize maintenance efforts and maximize flexibility and performance • Securely deploying the scorecards in a large enterprise environment

18. Balanced Scorecard Data Model Balanced Scorecard Data Model Extract, Transform & Load Base Measure Sourcing and Aggregation Extract, Transform & Load Performance Measure Calculation at all Levels of Aggregation Note: This model is a simplified conceptual model only. Extract, Transform & Load Performance Measure Allocation and Distribution Business Intelligence Software

19. Deployment Considerations • Easy to navigate web-based interface • Drill down, through or across the data • Restrict data access by user • Facilitate minimal report maintenance (data driven) • Alerting – when thresholds are crossed • Indicators – performance ‘at a glance’ • Must be able to explore subordinate’s performance level

20. The Contents of a Scorecard • Scorecards usually contain some or all of the following elements: • Key Performance Indicators (KPIs) • KPI actual values compared to historical values (for trend analysis) • KPI actual values compared to a forecast or budget amount • Rankings of different departments, locations, products, and so forth

21. BI Successes • Continental Airlines consolidated several customer databases into a single, strategic data warehouse and BI initiative that helped it become first in its industry for customer service. Its example demonstrates how companies can achieve competitive advantage. • UniCredit took a leading role in a new credit portfolio management market, thanks to a BI solution. This included an integrated data warehouse, risk modeling, rule-based warnings and an interactive reporting portal. • The Richmond Police Department in Virginia deployed a variety of analytical and predictive tools to determine likely areas of criminal activity so that officers could be proactively deployed to deter crime, rather than reactively respond to criminal activity.

22. Other BI applications: To Store & Analyze Data • Data Mining, Framing & Warehousing • (DSS) and Forecasting • Document Warehouse & Management • Knowledge Management • Mapping, • Information Visualisation and Dashboarding; • Management Information System (MIS); • Geographic Information System (GIS); • Trend Analysis; • Software As A Service (SaaS) • Business Intelligence offerings (On Demand) • Online Analytical Processing (OLAP) and • Multidimensional analysis • sometimes called "Analytics“ (based on the "hypercube" or "cube"); • Real Time Business Intelligence • Statistics and Technical Data Analysis • Web Mining, Text Mining and • Systems Intelligence

23. Other BI applications are used to analyze or manage the "human" side of businesses, Customer Relationship Management (CRM) Marketing Tools Human Resources applications. Web Personalisatiuon

24. Conclusion: Business Intelligence Today and Tomorrow • Today’s organizations are deriving more value from BI by extending actionable information to many types of employees, maximizing the use of existing data assets • Visualization tools including dashboards are used by producers, retailers, governments, and special agencies • More and more industry-specific analytical tools will flood the market to perform almost any kind of analysis and to facilitate informed decision making from the top level to the user level • A potential trend involving BI is its possible merger with artificial intelligence (AI)

25. BI Applications • Fraud detection • Clickstream Mining • Market Segmentation • Retail • Telecommunication • Banking& Finance • CRM

26. BI system at Hero MotoCorp • Analytics • Dashboards • Decision support systems • Online analytical processing • Querying and reporting • What-if analysis • Top management • Finance and accounts • Human resources • Manufacturing / production • Customer support • Marketing • Sales • Information technology

27. Benefits • Aligned analysis with business objectives: • Centralized information generation • Real time data analysis: BI has facilitated real time updates about critical business factors like sales for two wheelers, production, inventory analysis, etc.  • One version of the truth: • What-if analysis:

28. M&M Product Mix • Analytics, Dashboards, Decision support systems, Querying and reporting • With BI, accurate and timely information has become available to Mahindra & Mahindra helping it reduce reconciliations and better manage the billing process. This has led to quicker payments and a reduction in account receivables. • Analysis of data from sales, production and inventory data using BO Explorer has helped it improve its product mix. • BI has also enabled Mahindra & Mahindra to fulfill orders on time, thus increase its sales. • Improved visibility across locations has led to reduction in inventory and inventory carrying cost.

29. Shoppers Stop • With BI, Shoppers Stop is able to target micro-segments to ensure incremental business through promotions and messages sent to its customers. This has also helped the retailer to reduce inventory and still offer the customer what he wants by optimizing the merchandise mix. • The company analyzes the profiles of its stores located in the cities with similar demographic spread to create new stores at new locations. This analysis ensures that stories opened in the new cities have a higher probability of success. • Monitoring sales patterns across stores helps the operations teams to tactically change store layouts or of the displayed merchandise to attract customers.  The same feedback helps the back office planners in adjusting flow of merchandise to the stores. • BI has also helped Shoppers Stop to grow its online retail and improve the flow of referrals.