1. Introduction
Outline BI and Enterprise-wide decisions BI in different Business Areas BI Strategy, Architecture, and Perspectives 2
Case study: Netflix and House of Cards Source: Andrew Stephen 3
Case study: Netflix and House of Cards First Netflix Original Series Season 1 13 episodes released on Netflix on Feb. 1 2013 Stars Kevin Spacey Political drama/thriller Netflix initially ordered 26 episodes (2 seasons) Minimum $4.5 million per episode ~ Over $117m invested In 2012 Netflix s net income was $17.2m Biggest cost lies in licensing fees for streamed content This makes sense if subscribers watch it and it helps attract new subscribers Could they predict success in advance? Source: Andrew Stephen 4
Case study: Netflix and House of Cards Yes, they could predict success in advance they know a lot about subscribers What they watch (TV series vs. movies; genre preferences) What you like (star ratings) How they watch (episode binging) Where they watch (devices) First two weeks after release most watched on Netflix Source: Andrew Stephen 5
Case study: Netflix and House of Cards Looked at subscribers viewing habits Saw that the original version was popular on Netflix (from the UK, 1990 BBC miniseries) The subscribers who watched the original and rated it highly were also likely to watch movies starring Kevin Spacey or directed by David Fincher Also found a segment of subscribers who liked political dramas, thrillers This enabled Netflix to place a safe bet on their investment in this series without seeing a pilot episode Could reliably estimate the audience size, predict liking Could use their algorithms to recommend it instead of having a large marketing budget Source: Andrew Stephen 6
Case study: Netflix and House of Cards They didn t do audience testing, market research, focus groups, etc. They just let the data tell them what people should like based on past behaviors 33 million subscribers, and everything is tracked. That equates to rich data that can be mined to generate actionable insights KEY TAKEAWAY: Data can be used to identify new opportunities based on past customer behavior Source: Andrew Stephen 7
Need for Enterprise-Wide Decisions Goals/Strategy Pricing Promotion Loyalty Marketing Demand Consumers Capacity Labor Production Quantity Suppliers Materials Cash flow Debt/Equity Finance Revenues Investors Investments 8
IS in the Extended Enterprise Suppliers Customers Strategic Apps. Materials/Components Tactical Apps. Consumers SCM Applications ERP Applications CRM Applications Business Intelligence 9
What is Business Intelligence? Business Intelligence enables the business to make intelligent, fact-based decisions Aggregate Data Present Data Enrich Data Inform a Decision Database, Data Mart, Data Warehouse, ETL Tools, Integration Tools Reporting Tools, Dashboards, Static Reports, Mobile Reporting, OLAP Cubes Add Context to Create Information, Descriptive Statistics, Benchmarks, Variance to Plan or LY Decisions are Fact-based and Data-driven 10
Why is BI So Important? Time Data Making Business Decisions is a Balance Opinion (aka Best Professional Judgment) In the absence of data, business decisions are often made by the HiPPO. With Business Intelligence, we can get data to you in a timely manner. 11
Why is BI So Important? Corporate data is doubling every 2-3 years Barriers of entry (costs/technology) are being removed Continued pressure on businesses to find efficiencies and new market opportunities, client expectations More different data sources than ever before CRM Call Center Marketing Campaign Mgmt Internet Financial/ Accounting Inventory Procurement HR 12
Outline BI and Enterprise-wide decisions BI in different Business Areas BI Strategy, Architecture, and Perspectives 13
BI Business Areas The Data Warehousing Institute (TDWI) 14
BI Business Areas (examples) Marketing: Helps in analyzing campaign returns, promotional yields and fine tune spending to get better ROI, tracking social media marketing Sales: Finding best path and best practices, customer acquisition cost and length, process improvement, year-on-year turnover and sales analysis Inventory: Monitoring and adjusting inventory levels. Human Resource: Track and manage things like employee turnover, attrition rate, managing recruitment process etc. 15
BI for Marketing Unlocks information hidden in systems across the enterprise financial management, third-party demographic sources, and CRM Data analytics provide insights specify objectives evaluate performance against objectives identify opportunities and targets make decisions about future actions complement (not a substitute) to intuition 16
Marketing Intelligence Get a complete picture of customer needs and buying patterns Understand customer value Identify customers likely to churn Monitor effectiveness of marketing campaigns Understand the impact on overall marketing plans and budgets, thus enabling users to identify cost saving and revenue-increasing opportunities 17
BI for Marketing Retain Valuable Customers Marketing manager Receives alerts for customers at risk of churn Drills and looks at deeper information about those customers number of other products they own, current and predicted lifetime, customer satisfaction levels, and a snapshot of recent transaction history Creates a segment of high-value and at-risk customers, creates retention program, submits a budget to marketing executive 18
BI for Marketing Retain Valuable Customers (cont.) Marketing executive Consults analytics dashboard (budget information and ROI of marketing approves the budget request) Marketing manager Executes call-center campaign to promote retention offer Tracks campaign progress in real time number of customers contacted, offer acceptance and reject rate, and performance by call center agent. Marketing executive tracks the effectiveness of the retention marketing plan across the division for the quarter Actual versus budgeted expense, response rate, and overall campaign ROI based on customers that were retained. 19
BI for Marketing Generate Quality Demand at Lower Cost Measuring effectiveness of demand generation identify bottlenecks, improve campaign efficiency Monitoring the success of campaigns number of emails delivered, open rate, bounce-backs, and offer effectiveness number of calls made, average days to follow-up, crosssell and up-sell effectiveness, and total order revenue Adapt marketing approach in real time and swap out offers not eliciting high response rates 20
BI for Marketing Customer Profitability Which products customers will buy? Which products may make effective bundles (as one combined product)? Correlate customer lifetime value and churn risk with customer behavioral attributes Insight into customer clusters and better inform treatment strategies Aggregate information from various data sources and calculate, monitor, and build critical metrics such as customer profitability 21
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BI for Services Better Customer Service Experience Service manager identifies increase in call volume and customer complaints over the past several hours Drilling-in identifies increased call volumes about lost, missing, or late deliveries Identifies which product supplier has been late on many deliveries Take action: adds a late order option to the service center s Interactive Voice Response informing about problems related to orders from this supplier lower-cost options (IVR) address simple inquiries freeing customer service representatives (CSRs) 23
Social Marketing Intelligence Customers are increasingly moving to social media Digital footprints: New marketing opportunities for directing advertising targeted advertisements, matching lifestyle and interests 24
Social Marketing Intelligence Source: Andrew Stephen 25
Trend: Social Marketing Intelligence (cont.) Listen to the voice of the market topic and sentiment extraction from online discussions to assess the opinions toward a given company 26
Outline BI and Enterprise-wide decisions BI in different Business Areas BI Strategy, Architecture, and Perspectives 27
Business Intelligence A broad category of applications and technologies for gathering, storing, analyzing, sharing and providing access to data to help enterprise users make better business decisions Gartner 28
Information Pyramid 29
BI Strategy Improving organizations by providing business insights to all employees leading to better, faster, more relevant decisions Allow business users the ability to query and write reports To simplify reporting across multiple transaction systems To store historical data longer than you can/would in transaction system 30
Why do companies need BI? Optimization What s the best that can happen? Competitive Advantage Predictive Modeling Forecasting/extrapolation Statistical analysis Alerts Query/drill down Ad hoc reports Standard reports What will happen next? What if these trends continue? Why is this happening? What actions are needed? Where exactly is the problem? How many, how often, where? What happened? Tactical / Strategic BI Operational BI Sophistication of Intelligence 31
BI Types (our focus) Reporting and Analysis Analyze information with familiar tools Enabling end-users with ad hoc reporting capabilities Share reports and analysis over the web Data Warehousing Integrate information from disparate sources Store and manage vast amounts of detail data Analyze information with an integrated view of your business Performance Management Improve corporate performance Accelerate management decision making Enable collaborative analysis 32
BI Architecture 33
BI Architecture (MS) DELIVERY SharePoint Server Reports Dashboards Excel Workbooks Analytic Views Scorecards Plans END USER TOOLS AND PERFORMANCE MANAGEMENT APPS Excel PerformancePoint Server SQL Server Reporting Services BI PLATFORM SQL Server DBMS SQL Server Integration Services SQL Server Analysis Services Heterogeneous data sources 34
Gartner for BI (2015) 35