Big Data/Real World Analytics can be the catalyst for dramatic change in U.S. healthcare. Big Data informs many commercial, medical and HEOR decisions. On an average, Pharma Companies use 35-50% of analytics techniques to support commercial, medical and HEOR decisions. Data acquisition and infrastructure represent a majority of spending for Big Data. Data management cost-sharing across functions could drive savings & boost effectiveness. Howwever, the pharmaceutical industry is still in the early stages of utilizing large data sets from different sources to inform critical aspects of medical, commercial and HEOR operations. Best Practices, LLC published this study by engaging 22 leaders from 18 pharmaceutical companies through a benchmarking survey. This study aims to produce reliable industry metrics on current and future trends for Big Data utilization across medical, commercial and HEOR groups. A majority of study participants think partnerships with health plans/payers and data aggregators have a high impact on Big Data projects and programs. The respondents said about 20% of data is sourced from partnerships. Download Full Report: http://bit.ly/2cTW4wR

1. Big Data in Pharma:
Current & Future Trends for Big Data Utilization
Across Medical, Commercial and HEOR Functions
Best Practices, LLC
Strategic Benchmarking Research Study with Segmented
Responses by Medical, Commercial and HEOR Functions

2. 2
Table of Contents
I. Executive Summary pp. 4-12
 Research Overview pp. 4
 Universe of Learning pp. 5-6
 Big Data Team Overview and Key Study Insights pp. 7-8
 Quantitative Key Findings pp. 9-12
II. Defining Big Data pp. 13-20
III. Data Types / Sources by Medical, Commercial and HEOR Segments pp. 21-36
IV. Data Producers, Dissemination & Requestors by Medical, Commercial
and HEOR Segments pp. 37-49
V. Centralization pp. 50-56
VI. Governance and Leadership pp. 57-87

3. Best Practices, LLC, conducted a customized study – with responses segmented by medical,
commercial and HEOR functions - to better understand the growing influence of Big Data in the
biopharmaceutical sector and how it impacts medical, HEOR, and commercial operations in the U.S.
 Best Practices, LLC engaged 22 leaders
from 18 pharmaceutical companies
through a benchmarking survey. There
were multiple responses from 3
companies but they each represent a
different functional area (medical,
commercial, or HEOR).
 Research analysts also conducted
seven deep-dive executive interviews
with selected benchmark participants.
Research
Goal
Research
Methodology
 Produce reliable industry metrics on
current and future trends for Big Data
utilization across medical, commercial
and HEOR groups.
Topics Covered
 Types of Big Data Projects Used to Support
Medical, Commercial and HEOR Decisions
 Big Data Capabilities and Governance
 Types and Value of Data Used for Big Data
Projects
 Big Data Staffing and Budget Levels
 Value Rating of Partnerships on Big Data
Projects
 Policies and Procedures Governing Big
Data Activities
 Investigate data types, data partnerships,
and staffing/budget levels companies
are using as they move to a more
analytically based approach to
commercial, HEOR & medical decisions.
Research
Overview
Research Project Objectives & Methodology

4. Benchmark Class:
Eighteen Companies Participated in the Benchmark Study
22 analytics, marketing and HEOR leaders from 18 different companies participated in this study.
Participants were recruited because of their presumed investment in Big Data analytics. Three companies
had multiple responses - each representing a different functional area (medical, commercial, or HEOR).

5. Copyright © Best Practices , LLC
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Directors Make Up Most Participants; 81% Based in U.S.
Director
57%
Lead
9%
VP
19%
Manager
10%
Statistician
5%
Titles:
Associate Director Global Market Research
Director (5)
Associate Director
Executive Director
Senior Scientific Analyst
Vice President
Global Forecasting Director
Director, HEOR
Associate Manager, clinical data
Therapeutic Area Lead
Vice President, HEOR (2)
Global Brand Manager
Associate Director, Forecasting
Executive Director, Outcomes Research
Statistician
UK
5%
U.S.
81%
France
9%
Spain
5%
The benchmark class draws heavily on top-level personnel in analytics and HEOR programs. Though
participants responsibilities sometimes covered broad geographic areas, 81% were personally located
in the U.S.

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Analytics
Team
Big Data
Function
Understanding Big Data Use in Medical, HEOR & Commercial Decision-Making
Big Data Questions
• Medical
• Commercial
• HEOR
Big Data Info Types
• Electronic Health Records
• Government Cost Data
• Health Outcomes
Big Data Projects
• Value Proposition Development
• Post-Launch Performance
• Real World Studies
Big Data Decisions
• Go/No Clinical Decisions
• ID Market Opportunities
• Developing Economic
Models/Assessments

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Quantitative Findings: Big Data Teams and Data Producers
For the medical, commercial and HEOR segments, the following key Big Data team presence, data
producers and analysis targets were observed in this study.
Half of the study participants for both the medical and HEOR segments said
they have a centralized/dedicated group (Big Data team or function) to support
Big Data projects. For the commercial segment, 40% said they have a
centralized/dedicated Big Data group.
Only 5 of 36 types of Transactional, Reported, Online, Scientific and Machine-
Generated data were rated highly valuable by a majority of study participants in
each of the three segments (medical, commercial and HEOR). They were:
Claims; EHR (Electronic Health Records); Health Outcomes (provider/payer
reported); Real World Studies; and Registries. No types of Online or Machine-
Generated data were rated highly valuable by a majority of any segment
Internal Commercial, Medical and Development functions were rated by a
majority of medical, commercial and HEOR respondents as the most impactful
targets for data analysis presentations. A majority of each segment also said
these internal groups were also the most frequent requestors of presentations.
Only 5 of 36 Types of Data
Rated as Highly Valuable
Across all 3 Segments
Majority of Each Segment
Rate Internal Groups as
Most Impactful Targets for
Data Analysis
Most Have Centralized or
Dedicated Big Data Team
or Function

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Big Data cuts across different functional groups – IT, Commercial, Medical – and each group has its
own issues with how to utilize the potential inherent in large data sets from disparate sources.
“The term Big Data is nebulous.
Anyone you talk to, it means different
things…are you coming from an IT
perspective? Are you coming from a
patient level data perspective? Are
you coming from a digital
perspective? I can get more tangible
when I come from those angles
because I have all these
conversations internally and we're
honestly on different pages what it
means to them. “
- Director, Customer Data
Big Data Means Different Things to Different People/Functions

9. 9
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Point of Sale (POS) Claims Electronic Health
Records (EHR) /
Electronic Medical
Records (EMR) /
HIE (Health
Information
Exchanges)
ePrescription /
pharmacy fulfillment
Wholesalers /
Group Purchasing
Organizations
(GPOs)
Government (e.g.,
cost data)
Credit card
Impact of Transactional Data (Commercial)
Highly impactful Somewhat impactful Not impactful Not used
While a majority of commercial participants rated claims and Electronic Medical Records (EMR) as
the most valuable types of transactional data for Big Data studies, 50 % also cited point of sale as
highly impactful or valuable.
N=12
Q: How impactful (or valuable) has each of the following types of transactional data sources proven to be?
Transactional Data: Commercial Rates Claims, EMR Most Valuable

10. 10
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Impact of Online Data (HEOR)
Highly impactful Somewhat impactful Not impactful Not used
Online Data: HEOR Finds Online Information of Limited Impact
Participants in HEOR roles – like their peers in Medical – didn’t give online data high impact ratings
for using in Big Data studies.
N=15
Q: How impactful (or valuable) has each of the following types of online data sources proven to be?

11. 11
Medical Leaders Describe Analytics As Centralized
Medical leaders were the most likely to describe their analytics efforts as having centralized or
dedicated personnel.
N=12
Q: Do you have a centralized/ dedicated group of individuals to support Big Data projects?
Yes
58%
No
42%
Dedicated Big Data Team (Medical)

12. 12
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Partnership Value (Medical)
Highly impactful Somewhat impactful Not impactful Not used
Medical: Health Plans/Payers, Aggregators and Health
Systems Seen as Highly Impactful Partners
Medical leaders were most likely to rate partnerships as highly valuable across all varieties of
collaborations. Most popular were collaborations with payers and data aggregators.
N=12
Q: Which of the following partners are most impactful/ valuable on Big Data programs and projects?

13. 13
No Obvious Trends Between Functions
Certain functions do not clearly outpace the others.
Q: Types of Big Data projects currently used to support these medical decisions:
N=10,9,12
0%
10%
20%
30%
40%
50%
60%
70%
Targets for Drug Development Other Drug Development Decisions
% of Surveyed Techniques Employed in Decisions
Medical Commercial HEOR

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Best Practices, LLC is a research and consulting firm that conducts work
based on the simple yet profound principle that organizations can chart a
course to superior economic performance by studying the best business
practices, operating tactics, and winning strategies of world-class companies.
Best Practices, LLC
6350 Quadrangle Drive, Suite 200
Chapel Hill, NC 27517
www.best-in-class.com
About Best Practices, LLC