Heather Avery Manager, Business Analytics Avery Manager, Business Analytics. 2 ... SAS, Analysis...

Heather Avery

Manager, Business Analytics

2

40% of executives use “good ole’ gut” for major corporate decisions

Why?Data not available

Workforce challenges (i.e. “insufficient quantitative skills in employees” and “shortage of analytical talent”)

72% of executives “striving to increase their organization’s business analytics and BI use.”Source: July 2008 Accenture Survey of 250+ Executives

http://advice.cio.com/thomas_wailgum/to_hell_with_business_intelligence_40_percent_of_execs_trust_gut

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Review key steps for establishing and executing a customer retention analytics solution

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Assessing People Resources

Assessing Data & Technology

Defining Key Metrics

Gauging Performance

Identifying Sources of Impact

Using Predictive Modeling

Challenges and Lessons Learned

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Soft Skills: • Action Oriented • Adaptability• Customer Focus• Ethics/Values• Integrity & Trust• Listening• Communication • Decision Making• Planning/

Organizing

Hard Skills: • Data Mining• Data Analysis &

Interpretation• Database

Development• Research &

Benchmarking• Cognitive

Reasoning• Math Fundamentals• Math Problem

Solving

Software: • MS Suite (Access,

Excel, PowerPoint, Word)

• Business Intelligence Tools (i.e. Business Objects, Cognos)

• Statistics Packages (i.e. Excel Analysis ToolPak, Minitab, SPSS, SAS)

Education:• Mathematics• Statistics• Computer Science• Business

Administration

Experience: • Lead Analyst:

Minimum 2-3 Years• Support Analyst:

Minimum 0-2 Years (Lead Analyst Guidance Required)

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• MS Office Software (Word, PowerPoint, Excel, Access)

• Math Fundamentals

• Math Problem Solving

• Cognitive Reasoning

Assessments

• Tailored to probe for desired skill sets

• Step-by-step description of how desired skills are applied

• Being mindful of positive and negative themes

Behavioral Based Interview

Guides

• Reporting and/or executive summaries with insights demonstrating analytical capability

Prompting for Samples of

Work

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• DB2, Oracle, SQL Server, Access 2007Collect & Store Data

• Business Intelligence Tools (i.e. Business Objects, Cognos), Access, Excel, Crystal Reports Summarize/Report Data

• Access, Excel, SPSS, Minitab, SAS, Analysis ToolPak (Excel Add-In)Data Mining and

Analysis

• Communicated results should include a combination of reporting overall results with additional insights gleaned from data mining and analysisCommunicate Results

• Does the logic for your success metric(s) remain sound?

• What are the latest techniques used for data mining and analysis?

Regularly Evaluate Approach

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Establish Intent of Measure

• What % of customers do we retain over time?

Develop Prototype Metric

• Customer Retention Rate

Define Metric

• The percent of active customers that exist at the beginning of a given time period AND remain active at the end of a given time period.

Establish Calculation

• 1 – (net # of customers lost / ( ending balance of active customers + net # of customers lost) ) * 12

• Reported monthly, YTD, and QTD – all figures are annualized

Document Source(s)

• Business Intelligence Tools used to extract data from customer tracking system

Seek Input from Stakeholders

• Business Areas

• Financial department

• Information Technology department

• Actuarial department

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• DB2, Oracle, SQL Server, Access 2007Collect & Store Data

• Business Intelligence Tools (i.e. Business Objects, Cognos), Access, Excel, Crystal Reports Summarize/Report Data

• Access, Excel, SPSS, Minitab, SAS, Analysis ToolPak (Excel Add-In)Data Mining and

Analysis

• Communicated results should include a combination of reporting overall results with additional insights gleaned from data mining and analysisCommunicate Results

• Does the logic for your success metric(s) remain sound?

• What are the latest techniques used for data mining and analysis?

Regularly Evaluate Approach

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• DB2, Oracle, SQL Server, Access 2007Collect & Store Data

• Business Intelligence Tools (i.e. Business Objects, Cognos), Access, Excel, Crystal Reports Summarize/Report Data

• Access, Excel, SPSS, Minitab, SAS, Analysis ToolPak (Excel Add-In)Data Mining and

Analysis

• Communicated results should include a combination of reporting overall results with additional insights gleaned from data mining and analysisCommunicate Results

• Does the logic for your success metric(s) remain sound?

• What are the latest techniques used for data mining and analysis?

Regularly Evaluate Approach

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Economic Factors• Disposable income• Consumer share of wallet• Consumer confidence• Conditions by industry sector

Competitive Landscape• New entrants• Competitor offerings and value

proposition• Competitor messaging and sales tactics• Third party relationships (i.e. brokers)

Industry Factors• Healthcare reform• Federal/state mandates• Category perceptions

Product / Service Offering• Products/benefits offered• Price structure and value perception• Value added services

Brand / Corporate• Image• Reputation• Financial stability

Service – Internal Operations• Service levels/standards• Service tools and capabilities• Internal initiatives

Sales / Marketing• Distribution channels• Advertisement and messaging• Bids and proposals• Mix of business (i.e. new sales,

product mix, demographics)• Field skills/turnover/incentives

Service – Field Force• Service tools and information• Service levels/standards

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Industry

• Auto

• Banking Institutions

• Construction

Geography

• North

• South

• East

• West

Products

• Widget A

• Widget B

• Widget C

Tenure

• <13 months

• 13–24 months

• 25–36 months

• >36 months

Revenue

• Top 80%

• Next 15%

• All other

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Which Widget more negatively impacts the overall figure?

Overall Widget A Widget B Widget C

86,5%

91,6%

87,1%

83,0%84,4%

90,3%

85,2%

79,5%

2008 2009

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Overall Widget A Widget B Widget C

86,5%

91,6%

87,1%

83,0%84,4%

90,3%

85,2%

79,5%

2008 2009

The distribution of active business by product line

must be consideredWhich Widget more negatively

impacts the overall figure?

29,7%

56,1%

14,2%

Widget A

Widget B

Widget C

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29,7%

56,1%

14,2%

Widget A

Widget B

Widget C

Overall Widget A Widget B Widget C

86,5%

91,6%

87,1%

83,0%84,4%

90,3%

85,2%

79,5%

2008 2009

The distribution of active business by product line

must be consideredWhich Widget more negatively

impacts the overall figure?

Impact (1 Retention Rate) Product Distribution % Total Volume

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Modeling ConsiderationsAbility to project future performance assuming the current trends continueAbility to project future performance if distinctive shifts in mix of business are expected/planned

Building a Predictive ModelIdentify primary attributes affecting customer retention metrics (i.e. attributes like industry, products, tenure of customer)Conduct regression analysis using several years of historical data to quantify the relationships that existUtilize regression equation to forecast customer retention trends and allow for scenario modeling – user input should be allowed

– Marketing of a new product will change the distribution of your total active business

– As long as the retention rate of the new product is not equal to the overall retention rate, it WILL impact the overall retention rate as the proportion of the new product increases; assuming everything else remains the same

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• Establish a buddy system

• Distribute workload

Having only one assigned resource can cause “burn-out”

• Institute a validation process

• Confirm cyclicality of results

• Research system issues/glitches

• Determine if process changes occurred

Opportunity exists to make snap decisions with one month’s worth of unusual results

• Establish appropriate timelines and channels for communicating initial results and detailed findings

Data mining & synthesizing takes T I M E

Thank you