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Optimize the Role of Predictive Analytics For Rep Effectiveness Using Patient Longitudinal Data

Amp Idea, Inc.Amplify your idea

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Historical Pipeline - New Product Launches

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Drug-1Drug-2 :Drug-N

High Revenue

$$$

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Current Pipeline - New Product Launches

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Drug-1Drug-2

LowRevenue

$

Drastic Reduction in New Drugs Approval

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Problem

Reduced revenue and margin due to shrinking drug pipeline.

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Historical

Current

Marketing and sales budgets are shrinking while the pressure is mounting

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Traditional Call Allocations

Sales Practices Losing Effectiveness

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List of “No See” doctors is increasing,

Average length of sales calls has been reduced by physicians.

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Traditional Call Allocations

Improved Call Plans Using Patient Data

Optimal Call Allocations

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Result

Millions of dollars of wasted sales resources in sub optimal sales territories

Research shows that over 80% of sales territories have significant design flaws and targeting issues.

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Traditional Marketing Analytics

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PromotionData

Resource Allocation Analytics

SalesData

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Traditional Marketing Analytics

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PromotionData

Resource Allocation Analytics

SalesData

“90% reps finds Call Plans to be inadequate”.

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Filling Blind Spot

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PromotionData

Resource Allocation Analytics

SalesData

PayerData

PatientData

“90% reps finds Call Plans to be inadequate”.

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Patient/Payer Data

Conventional resource optimization solutions are silo-based, and often ignore other local market dynamics, including:

Patient and disease indication composition

Formulary tier and co-pay differential

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Why does Brand A have low share among Physician Cluster V-L?

Formulary Status

Disease Indication

Brand A Increases Marketing Budget - No Sales Impact

Physician Cluster

DoctorsMarket('000)

Specialty DecileBrand A (Share

Segment)

Brand AShare

Brand BShare

V-L 800 $80,000 Primary Care Very High Low 25% 75%V-H 1,200 $120,000 Primary Care Very High High 60% 40%

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Prescription - Marketing Efforts Physician Focused

Physician

Patient PharmacyManaged Care

Plan

Medicine Dispensed

Claim Sent

E-prescription

Prescription

Co-pay

PhysicianApproval

Claim

Y/N

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Physician

Patient PharmacyManaged Care

Plan

Medicine Dispensed

Claim Sent

E-prescription

Prescription

Co-pay

PhysicianApproval

Claim

Y/N

Prescription – Pharmacy Makes Switch

Alternate DrugIf High Co-pay

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360 Degree View Of Data

Prescribers

Patients/Caregivers

Payers and Plans

Brand Promotion

Market Events

Historical Data, Market Research, Analytic Results

Brand Performance

Traditional Optimization

Not Utilized in Optimization

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Integration of Payer Data with Physicians Sales Data

Able to more effectively target the right physicians, with the right message, at the right time.

The time needed to communicate formulary updates to physicians can be shortened, thus increasing revenues.

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Patient Segmentation

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Age Gender RaceDisease

IndicationDiseaseSeverity

Physician Segmentation

Region Specialty Volume ShareProduct

DominanceManaged

Care

360 Degree View Of Data – Patient Longitudinal Data

PatientSegment

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Traditional Forecasting Framework

Historical Class Volume

(Brand-A)

Rx (Brand-A) Rx (Brand-B)

Market Definition

Rx (Brand-C)

Class Volume = Retail Sales of all the Competing Brands,Brand Forecast = Projected Market Growth and Brand Share By Region/Segment

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Traditional Segmentation Framework

SpecialtyClass Volume

(Brand-A)Product Group

DominanceShared Trend

Rx (Brand-A) Rx (Brand-B)

Traditionally Class Volume is Calculated by Adding TRx of all the Brands Defined in the Class.

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Managed Care(Co-pay By Plan)

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Data Quality Management using Managed Care Plan Data

Physician Cluster

DoctorsMarket('000)

Specialty DecileBrand A (Share

Segment)

Brand AShare

Brand BShare

V-L 800 $80,000 Primary Care Very High Low 25% 75%V-H 1,200 $120,000 Primary Care Very High High 60% 40%

Physician Cluster

DoctorsMarket('000)

Specialty DecileBrand A (Share

Segment)

Brand AShare

Brand BShare

L-L 800 $24,000 Primary Care Low Low 25% 75%V-H 1,200 $96,000 Primary Care Very High High 60% 40%

Data Pre-ProcessingAnd Staging

(Business Rule)Payer Data

Market Potential

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Market Potential By Access

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Focus on Disease Indications

Physician Cluster Indication - 1 Indication - 2 Indication - 3 Indication - 4 Doctors DecileShare

SegmentV-L 5% 5% 50% 40% 800 Very High LowV-H 40% 60% 0% 0% 1,200 Very High High

Market Rx By Disease Indication

Conclusion: Based on Patient’s Disease Indication, Brand-A should receive significantly less Details for Physician Cluster V-L

Indication - 1 Indication - 2 Indication - 3 Indication - 4Brand-A Yes Yes

Brand-B Yes Yes Yes Yes

Brands - Disease Indications

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Data Quality Management using Drug Indication

Physician Cluster

DoctorsMarket('000)

Specialty DecileBrand A (Share

Segment)

Brand AShare

Brand BShare

V-L 800 $80,000 Primary Care Very High Low 25% 75%V-H 1,200 $120,000 Primary Care Very High High 60% 40%

Physician Cluster

DoctorsMarket('000)

Specialty DecileBrand A (Share

Segment)

Brand AShare

Brand BShare

L-L 800 $8,000 Primary Care Low Low 25% 75%V-H 1,200 $120,000 Primary Care Very High High 60% 40%

Data Pre-ProcessingAnd Staging

(Business Rule)Patient Data Drug Indication

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Market Potential

Market Potential By Indication

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Market Definition : Traditional Approach – Treated Market

Calcium ChannelBlocker

HypertensionMarket

ACE InhibitorAngiotensin II

Receptor Antagonists

Beta Blocker

AzorTribenzorCardizemExforgeLotrelNorvascTarka

AzorBenicarBenicar HCTDiovanLasixMicardisEdarbi

LopressorToporol - XLBystolicCoregInderalMetoprolol

LotensinCapotenZestrilPrinivilAccuprilAltaceTarka

Traditional approach defines the market based on treatment option.

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Market Definition: By Disease Indication – Market Potential

Calcium ChannelBlocker

HypertensionMarket

ACE InhibitorAngiotensin II

Receptor Antagonists

Beta Blocker

AzorTribenzorCardizemExforgeLotrelNorvascTarka

AzorBenicarBenicar HCTDiovanLasixMicardisEdarbi

High Blood PressureAbnormal Heart RhythmHeart FailureAnginaTremorPheochromocytomaMigraines.

High Blood PressureHeart Failure

High Blood PressureAbnormal Heart RhythmAngina

High Blood Pressure Heart FailureRenal Disease StrokeDiabetic NephropathyLeft-Ventricular Hypertrophy

LopressorToporol - XLBystolicCoregInderalMetoprolol

LotensinCapotenZestrilPrinivilAccuprilAltaceTarka

Identify product attributes that will maximize actual prescribing

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Realistic Physician Decile

Very High High Medium Low

Benicar 4,000 8,000 12,000 80,000

Number of Physicians By Segment (Traditional Approach)

Very High 1,600High 1,100

Medium 800Low 500

2003,0002,2002,600

1001,0008,0002,900

100900

5,00074,000

Total

2,0006,00016,00080,000

After applying access and disease indication filter, 1,600 very high, 3,000 high and 8,000 medium volume

prescribers retained their respective decile segmentation.

200 high volume, 100 medium and 100 low volume prescribers moved to very high segment.

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Number of Physicians By Segment (Disease Indication and Access)

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Better Targeting, Call Allocations & Territory Alignments Compared to Traditional Call Allocation Methodology

Prioritizes Targets Based on Sales Data AND Local Market Demographics of the Patients, Plans and Physicians: “No See” doctors Based On:

Communication Preferences Formulary Status Disease Indication

Traditional Call Allocations

The Net Result: Improved Call Plan

Optimal Call Allocations

Remove “No See” Doctors New Called On Doctors

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In this example, dropping lower-value doctors from the customer target list and adding higher In this example, dropping lower-value doctors from the customer target list and adding higher potential doctors would significantly improve market coverage and incremental sales.potential doctors would significantly improve market coverage and incremental sales.

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Next Gen Forecasting Framework

Historical Class Volume

(Brand-A)

Indication-1 Indication-2

Rx (Brand-A) Rx (Brand-B) Rx (Brand-A) Rx (Brand-C)

Class Volume = Retail Sales of all the Competing Brands By Disease Indication,Brand Forecast = Projected Market Growth and Brand Share By Region/Segment

+ Disease Indication + Managed Care Impact

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Next Gen Segmentation Framework

Specialty Class VolumeProduct Group

DominanceShared Trend

Managed Care(Co-pay By Plan)

PatientDiagnosis

Rx By Diagnosis

Interim Adjusted Class Volume

Business Rule(Co-pay)

Final Adjusted Class Volume

Co-Pay By Plan

Amp Idea, Inc. proposes that Class Volume should be Calculated after Filtering TRx from the Competing Brands Based On Disease Indication and Managed Care Plan.

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Resource Allocation Process – Optimal Reach and Frequency

Specialty

Rx/Sales Data

Call Data

Samples

Patient Data

Disease Indication

Payer Data

MarketSegmentation

HistoricalPromotionEvaluation

Product/PortfolioResource

Optimization

Call Planning

IncentiveCompensation

Changes in market segmentation will reflect in territory alignment/incentive compensation and territory alignment in the marketing resource optimization process.

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TerritoryAlignment

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Market Research/Analytics Results

Sales/Marketing Data(CRM)

Key PerformanceIndicators (KPIs)

Excel BasedManagementDashboard

(Data Integration &Business Intelligence)

Provider/Patient

Payer

Excel Based Analytic Information Hub - Provide Better Insights into Brand Performance

Data Warehouse(SAS, DB)

DataExtraction,

Transformation,Loading

(Excel/SAS)

Analytic Engine(SAS)

Report Generation

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Benefits

Better physician targets, less wasted marketing resources.

Appropriate adjustment in marketing resources for targeted physicians based on: No see doctors Patient diagnosis information Managed care – Formulary status and co-pay

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Approach - Pareto Principle

The Pareto principle states that, for many events, roughly 80% of the effects come from 20% of the causes.

In other words, 80% of sales come from 20% of sales reps.

Review low performing territories using sales, promotion, patient and managed care data.

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Opportunity

By deploying a more robust patient-based analytical platform, and integrating a

broader set of local market intelligence metrics, we are better positioned to: Save millions of dollars per field force in annual sales team expenditures, and

potentially increase revenue in each territory.

Provide grounded, empirically-based decisions around the ROI of patient-based

marketing initiatives.

Based on proprietary research, moving beyond conventional resource

optimization techniques and incorporating a more robust localized solution,

brand sales performance can increase.

By increasing productivity and improving customer targeting, Pharmaceutical

companies will improve the sales in non-performing territories

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Critical Business Questions To Explore?

What does the complete competitive landscape for my product look like?

How can we maximize the impact of our product launch tactics?

How effective are our sales reps in accessing, engaging, and promoting to targeted physicians?

How well does our detailing activity drive brand choice compared with competitors?

Which core messages are most effective?

Is it time to change our messaging strategy?

Are sampling volumes driving share—or supplanting written prescriptions?

Is our marketing campaign driving share from the targeted source of business?

How effective are our new sales strategies and tactics?

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Questions

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Praveen Mathur is Vice President of Business Analytics at Amp Idea. He works with clients in establishing best practices in the area of sales optimization through combination of customer and market information, advanced analytical processes and software solutions. His areas of expertise include: maximizing ROI on marketing investment; customer segmentation; promotion response modeling; field force portfolio optimization; and market mix modeling using non-linear regression techniques.

Prior to joining Amp Idea, Praveen held various positions at inVentiv Health, leading cross-functional teams of business analysts and software engineers in the development of analytical tools to evaluate the effectiveness of sales and marketing initiatives.

Ram Bala is an Assistant Professor of Operations Management & Information Systems at the Leavey School of Business, Santa Clara University. He holds a Ph.D. in Management Science from the UCLA Anderson School of Management. His main research areas are product line design, promotional effort allocation, global product development and pricing and contracting strategies for services. His specific interest is the deployment of cutting edge technologies to increase the “intelligence” of business decisions.

Prior to joining academia, he has consulted for several firms in the area of pharmaceutical marketing analytics.

Author’s Bios

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Contact

Praveen Mathur, Vice President - Analytics, Amp Idea, Inc. pmathur@ampideainc.com www. ampideainc.com 732-619-3899

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