BA_Intro.ppt

7/27/2019 BA_Intro.ppt

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TOP: BUSINESS ANALYTICS

MGT 2206 001

Welcome!

Matthew J. Liberatore

Fall 2009


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Introduction

Many firms are awash in data Enterprise Resource Planning (ERP) Systems

provide voluminous business data

The internet offers customer and market dataand the opportunity to experiment withdifferent product, promotion, and pricing plans

RFID devices will be placed on virtually everypallet or carton generating vast amounts ofnew data


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Introduction

These trends are leading firms to use andanalyze data to improve businessperformance and make better decisions

Competing on Analyticsby Davenport andHarris: somefirms use analytics as a

competitive weapon

Consider some examples, many from ourresearch


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Analytics Competitor: Netflix

Movie recommendation engine

throttling: infrequent-use customers

(most profitable) given priority in shipping

Paying for distribution rights of DVDs (lookat success of related movies)


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Analytics Competitors in Sports

Moneyballby Michael Lewis As consistently make the playoffs despite a low

overall payroll

New metrics for player selection: on-basepercentage and on-base plus slugging percentage

Boston Red Sox Example: Martinez easier for opposing batters after 7

innings or 105 pitches (ALCS 2003)

New England Patriots: analytics both on and offthe field


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Analytics Competitor:

Harrahs Entertainment Customer loyalty card data used in near-

real time to optimize yield, set prices forslots and rooms, and design trafficthrough the casinos Predict the pain point and pull you away

from the slot machine

Which marketing initiatives to movethrough which channels HR analytics used in recruiting process


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Vanguard

Dashboards have non-financial metricsand line of sight that roll up to a corporate

dashboard to drive outcomes Customer analytics is a major focus where

data mining is used to score clients andtrack problems

Six sigma and analytics combined toimprove business processes


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Wyeth

metrics feed strategy and strategy feedsmetrics

Ten high level enterprise metrics areintegrated and reviewed by the CEO andtop management

Analytics and six sigma help to manageand improve all of their global processes:innovation, sales and marketing, supplychain, management, support


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KPMG

Metrics are key and help to understandhow strategy is being executed

Focusing on electronic data discovery how to build associations across data

Examples: bad debt chasing, payroll

process, SOX audit controls in vendorsourcing and pricing, fraud discovery


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Rohm and Haas

Implementing an executive dashboard

Providing business managers with

operational metrics

Focusing analytics in supply chain,customer relationships, working capital

reduction


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FTI Consulting

Analytics used in corporate finance,economic consulting, forensic and

litigation consulting, as well as brandmanagement and strategiccommunications in general

Focus on leading and predictive metrics


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Nordstrom

Analytics used at store level for merchandising(ID trends/styles), and by upper management totrack customer interactions

Heavy use in determining who should receiveemails and catalogs in their multi-channeloperation

Lots of test versus control uses in the Direct

Marketing aspects of their business Scorecards used to measure performance of

new predictive models against current ones


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Air Products

Extracts value from a single instance SAP systemenabling their supply chains via dashboards,

data accessibility via business warehouse cubes Analytics integrates with their lean/six sigma and

other initiatives to drive customer andshareholder value

Make visible data that is strategic such ascustomer metrics like Perfect Order Fulfillment


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Colgate

Use data (financial, sales now R&D, sharedservices coming) generated from global ERP

system to run the company Most managers can drill down into data to

answer questions like what did we buy today

Measure the back end of sophisticatedmarketing promotions to see what part worked


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Marriott

Marriott Rewards used analytics to predictcustomer acquisition and retention

Realized, expected, and potentialcustomer value is measured

Predict each customers likelihood of

visiting a location on a weekday orweekend in the next year


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APQC Study

on Process Measures and Analytics Five participating companies: Wyeth, ING,

Marriott International, General Electric,Caterpillar

Key findings: Analytics are applied within processes as early

warning indicators Value of analytics greatly enhanced when integrated

into day to day processes Integrating process analytics with continuous

improvement techniques such as Six Sigma and Leandrives action and bottom line results


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What Companies Are Telling Us

About Analytics We are helping clients harness their vast amounts of

customer and operational data

We cannot find enough new grads with the right

quantitative skills We compete on the basis of better knowledge of their

customers, using analytics

The riskier our business problems the more we rely on

analytics After implementing our ERP system we are mining that

data, and using data better in different ways


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What Business Leaders Are

SayingIn God we trust, all others bring data

Do you think that, or do you know that?

Those who succeed with six sigma, andthen advance in our company, have thebetter quantitative skills

We are basing our strategy on analytics,especially customer analytics


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What is Business Analytics?

Analyticshas been defined as the extensiveuse of data, statistical and quantitative

analysis, explanatory and predictivemodels, and fact-based management todrive decisions and actions (Davenport

and Harris, Competing on Analytics, 2007)


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Some authors view analytics as a subsetofbusiness intelligence(BI): a set of

technologies and processes that use datato understand and analyze businessperformance and includes both data

access and reporting, and analytics(Davenport and Harris, Competing onAnalytics, 2007)


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For the purposes of this course, we willnot make any distinctions between

business analytics and BI We consider business analyticsto include

the access, reporting, and analysis of data

supported by software to drive businessperformance and decision making


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Introduction to Business Analytics:

Course Topics Overview of Business Analytics

Data Warehousing

Business Analytics and Data Visualization

Performance Management

Introduction to Data, Text, and WebMining

Data Mining Methods and Applications

BA_Intro.ppt

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