pmrg 2009 anc linkage analysis
TRANSCRIPT
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The way a company makes the most of existingknowledge within the business is a determining forceto its overall financial and operational success . . .
(Peter Nicol, VP, OutStart EMEA,
a learning and knowledge sharing solution company)
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Era of Information Overload
988
161
(forecasted)
Digital data generated worldwide, in exabytes
Exa
byt
es
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Source: USA Today, March 6, 2007
Worldwide:
• 161 exabytes of digital data were generated in 2006, says researcher IDC
Putting 161 exabytes in perspective, that's roughly the equivalent of:
− 36 billion digital movies
− 43 trillion digital songs
− 1 million digital copies of every book in the Library of Congress
Per Person in North America:
• About 213 gigabytes of information were generated for each person inNorth America in 2006 , roughly the equivalent of 100K digital books
Sources: IDC, UC Berkley, CIA World Factbook, USA TODAY research
Why The Drive to Amass Information?
Critical decisions need to be made . . .
• Information is needed to build knowledge
• Knowledge will guide “correct” decision-making
• Correct decision-making will be rewarded
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Let’s look at how this manifest in thePharmaceutical Industry . . .
• Multiple factors are acting to constrain brand potential
– Increasing number of new products (particularly “me-too’s”)
– Increasing number of generic options
– Greater access restrictions to branded products
– Greater restrictions on marketing to physicians
– Decreasing impact of personal detailing
Brand Teams are Charged w/ Maximizing Brand Potentialin an Increasingly Challenging Marketplace
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• Within this market, Brand Teams are required to make
critical decisions for maximizing share, revenue and/or
margins for their assigned brands
MR’s Role: Provide Decision-MakingSupport to Brand Teams
• Brand Teams rely on MR to provide information that
supports decision-making around strategy/tactics
End Goals:
– Maximize share capture
– Increase revenue/margins
• To that end, MRDs acquire information intended to support• To that end, MRDs acquire information intended to support
the Brand Team’s decision-making needs
7 MRDs: Market Research Departments
Information Typically Available to SupportKnowledge-Building
PharmaceuticalIndustry
Secondary Syndicated / Internal Custom / Primary
IMS NationalPrescription Audit(NPA) / Xponent or WoltersKluwers
Brokerage Firms’Industry Reports
Forecastingsupport
Versipan’s VONA(RetailDispensing)/IMS NationalSales Perspectives (NSP)
Manufacturing/ “ProductShipped” Data
ATU / A&U
Verispan’s Meetings& EventsAudit (PMEA)
Physician CommunicationsResearch
Patient Tracker Data/Report MARS/Simmons/MRI Patient CommunicationsResearch
Product / Marketing Support
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Research
IMS NationalDisease andTherapeutic Index (IMS NDTI)
Therapeutic Category Reports
IMS PlanTrak Health Strategies / HIRC MC Communications Research
MMIT FormularyCompass/Fingertip Data
MC “Status” andupcoming contracts
Formulary AcceptanceInfluencers
IMS Integrated PromotionalServices (IPS)
Call Reporting Data
Territory Alignment and SalesForce Deployment
Impact RX – Sales RepInteractions
Sales Force Structures&Strategies Reports
Sales Rep PerformanceEvaluationResearch
Rep-Msg RecallResearch
Managed Care Support
Sales Force Support
MRs Collect Information, But Information Does NotNecessarily Translate Into Knowledge
Barriers to Knowledge
• MRD’s information sources are often legacy acquisitions,
ad hoc projects, and/or “silo-ed”
“Knowledge" accrues when information is understood incontext and relative to the existing patterns of relationshipwith other information
ad hoc projects, and/or “silo-ed”
• Sources are seldom linked to provide a comprehensive view
of the market and what drives Rxing
• Rarely is information collected to provide ongoing and
“linked” reconnaissance on market factors that might,
or are known to, impact the brand’s “bottom-line”
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“Silo-ed” Information
Sales ForceOptimization
Managed CareAccess
ProductMarketing
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Prescribing Data(IMS Xponent/ Wolter Kluwer’s)
Physician Preference or StatedIntentions
Product MarketingSales Force
Optimization
“Silo-ed” Information
XXXX
Managed CareAccess
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Linked Analysis to SupportBusiness Goals
XX
XX
XX
MR Recommendations Typically Limited
• MR agendas can be reactive and static, rarely including
comprehensive surveillance of a dynamic marketplace
• Projects tend to focus on one aspect of the marketing mix,
in isolation, not accounting for the inter-related influence of
Lack of “Big Picture” knowledge limits MR’s ability to “sitat the table” during brand strategy planning
in isolation, not accounting for the inter-related influence of
each component of the “whole”
• Rarely based on ROI; based more on respondent feedback
or the “statistical” finding
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Model misspecification leads to “wrong answers”
This leads to brand strategy/tactics that may not ultimatelyadvance the “bottom-line”(Worse: may have negative ROI)
MR’s Decision-Making Support Gains Value andCredibility Through Brand Knowledge Building
• Foundation for knowledge building is “Linkage Analysis”
• “Linkage Analysis” is a knowledge management system that
allows MRDs to:
– Know What Matters
– Avoid Wrong Answers– Avoid Wrong Answers
– Make Recommendations That Enhance the “Bottom-Line”
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Knowing What Matters
Create a Business Blueprint Example ONLY
BrandEvaluation
Business Impact Measures Business Results
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Gross Revenue
Market Share
Overall PhysicianLoyalty/Satisfaction
Detailing/Sampling
Sales RepService &Support
Managed CareAccess
Must involve key stake-holders from business supporting functions
Knowing What Matters
BrandEvaluation
Business Impact Measures Business Results
Source the Business Blueprint Example ONLY
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Gross Revenue
Market Share
Overall PhysicianLoyalty/Satisfaction
Detailing/Sampling
Sales RepService &Support
Managed CareAccess
Not accounting for the impact of animportant component of theBusiness Blueprint results in ModelMisspecification
Avoiding Wrong Answers
• The Phantom Menace: Model Misspecification
– Our theories are always a simplification of “Truth” and all ourmeasures are imperfect reflections of the “Truth”; thus allmodels are misspecified to some degree
– HOWEVER, our task is to seek models that are sufficientlyspecified, to minimize our chances of a “wrong answer”
• There are four basic types of model misspecification:• There are four basic types of model misspecification:
– measurement error
– erroneous functional form for the relationship
– inclusion of an irrelevant variable
– exclusion of a relevant variable (omitted variable bias)
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– exclusion of a relevant variable (omitted variable bias)
Avoiding Wrong Answers
$$
HomeSellingPrice
Square Footage$86,000 per 1000
MisspecifiedModel
Goal: Maximize the SellingPrice of My Home
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PriceNumber of Baths$32,000 per bathsover one
Results suggest:A. Adding an office (500 sq ft)
increases selling price by $43KB. Adding a bath will increase
selling price by $32K
Given similar cost, choose A
Omitted Variable
Not Included inMisspecified
Model
New/Used
Avoiding Wrong Answers
$$
HomeSelling
Square Footage
Number of Baths
$42,000 per 1000
$44,000 per
$86,000 per 1000
$32,000 per baths
MisspecifiedModel
True Model
Goal: Maximize the SellingPrice of My Home
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$$ SellingPrice
Number of Baths
New/Used
$44,000 perbaths over one
$56,000 for newvs used
$32,000 per bathsover one
“True Model” suggests adding a bath will better achieve goalA. Adding an office (500 sq ft) increases selling price by $21KB. Adding a bath will increase selling price by $44K
Avoiding Wrong Answers
$42,000 per 1000
$44,000 per
$86,000 per 1000
$32,000 per baths
MisspecifiedModel
True Model
$$HomeSelling
Square Footage
Number of Baths
Goal: Maximize the SellingPrice of My Home
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$44,000 perbaths over one
$56,000 for newover used
$32,000 per bathsover one $$ Selling
Price
Number of Baths
New/Used
Action Plan flawed due to misspecified model
• A component that directly impacts the selling price was omitted
Avoiding Wrong Answers
Goal: Maximize BrandShare / Revenue
$$MarketShare /
Sales Force
Product Quality
Hypothetical Example in Pharma
$$ Share /Revenue
Product Quality
Managed CareSF Analytic Results based onmisspecified model suggests:A. Increasing sample increase share
by 1.5% shareB. Increasing category knowledge will
yield 1.2% share
Recommendations implemented, but results don’t accrue.Why? Action plan was flawed because a component known to impactbusiness result was omitted
Avoiding Wrong Answers
Avoid Model Misspecification
• Spend the requisite time needed to build a consensus
“Business Blueprint”
– Proper model building is based as much on experience andmarket knowledge as research “learnings”
• No statistical test will reveal a specification error due to anomitted variable biasomitted variable bias
• Always explore hypotheses about the relationship of
“impact” variables, as well as what might be missing
– Remember the Phantom Menace
Linkage Analysis
Number ofDetails
“Valued” Rep
Manage CareAccess
New Product - Diabetes
.38.12.32
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PhysicianPreference
ProductValue
Share ofTRxs
BLINDED CASE STUDY(Illustrates “point,” not actual findings)
Company Image/Presence
.05
.35 .56
Linkage Analysis
Mature Product – Enzyme Replacement
Number ofDetails
“Valued” Rep
Manage CareAccess
.10.18.32
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PhysicianPreference
ProductValue
Share ofTRxs
BLINDED CASE STUDY(Illustrates “point,” not actual findings)
Company Image/Presence
.35
.08 .56
The Validity of Linkage Analysis
• There is a relationship between using linkage analysis and
improved business performance
– Linkage analysis is synonymous with building causal modelslinked to business outcomes
23% of Companies: Extensive linkage and validation
Those 23%, on average, had 3% higher ROA
77% of Company: Minimal linkage and validation
Those 23%, on average, had 3% higher ROAand 5% higher ROE than companies thatdidn't use linkage (i.e., causal models)
Christopher Ittner and David Larcker, “Coming Up Short on Nonfinancial Performance Measurement”Christopher Ittner and David Larcker, “Coming Up Short on Nonfinancial Performance Measurement”
Harvard Business ReviewHarvard Business Review (November, 2003)(November, 2003)24
Making Recommendations That Enhancethe “Bottom-line”
• Avoid the temptation to provide recommendations based
on “statistics” or respondent-preference
• Focus, instead, on the “cost-benefit” or ROI of the
considered improvement initiative
Model of Impacts on Rxing Statistical Effect
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Model of Impacts on Rxing
• Product Efficacy
• MC
• Sales Force “Perceived Value”
• Detailing
Statistical Effect
.56
.32
.32
.32
Sampling
Category Knowledge.35
.25
Making Recommendations That Enhancethe “Bottom-line”
• Ongoing reconnaissance tracks:– The changing market– Progress on share building initiatives– Brand Team assumptions about what impacts the market
Listen(Obtain Feedback)
Implement Change
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(Obtain Feedback)
Analyzethe Data
Measurement
Define Action Paths
Management
Continuous Processfor Monitoring
Drivers of Rxingand Profitability
Brand Knowledge Building
• . . . through “Linkage Analysis ” – a system for managinginformation that allows MR to:
– Know What Matters
• Blueprinting , together with continuous reconnaissance of themarketplace, keeps the Team updated on factors shown to impactthe “bottom-line”
– Avoid Wrong Answers
• “Linked” analysis of all factors known/thought to impact the“bottom-line”
– Make Recommendations That Enhance the “Bottom-line”
• Recommendations, while they do not discount respondentpreference and stated intentions, are based on a cost/benefitanalysis of impact on the “bottom-line”
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For more information, please contact . . .
Linkage Analysis Help SupportsDecision-Making for Strategic Advantage
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Susan Lee SimpsonVP, Senior Account Executive
513-564-8382
Thomas MillsVP, Statistical Consultant
513-564-8381