The bio-pharmaceutical industry has been rather slow in embracing Big Data Analytics due to its inherent costs, difficulty in measuring ROI of Big Data, uneven senior management buy-in and other challenges associated with harnessing large sets of information in varied formats. As the industry moves towards recognizing the huge potential that BIG DATA holds for important HEOR decisions, rapid steps are being taken to develop greater BIG DATA capabilities. Best Practices, LLC undertook this study to probe current & future trends, winning strategies and best practices for Big Data utilization across the HEOR function. The study lprobes the most useful data types and sources for key HEOR decisions; governance policies and leadership and the most meaningful data producers, dissemination channels and targets. Download Full Report: http://bit.ly/2byZH9g

1. Big Data in Pharma:
Current & Future Trends for Big Data Utilization
Across the Health Outcomes Research Function
Best Practices, LLC
Strategic Benchmarking Research Study with HEOR Functions

2. 2
Table of Contents
I. Executive Summary pp. 3-8
 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 and Sources pp. 21-26
IV. Data Producers, Dissemination & Requestors pp. 27-31
V. Centralization pp. 32-34
VI. Governance and Leadership pp. 35-51
VII. About Best Practices, LLC pp. 52

3. Best Practices, LLC, conducted a customized study – with responses segmented by medical,
commercial and Health Outcomes Research (from now on called either Health Outcomes or HEOR)
functions - to better understand the growing influence of Big Data in the biopharmaceutical sector and
how it impacts HEOR.
 Best Practices, LLC engaged 15 leaders
from 13 pharmaceutical companies
through a benchmarking survey.
 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:
Thirteen Companies Participated in the Benchmark Study
Best Practices, LLC engaged 15 leaders from 13 pharmaceutical companies through a benchmarking
survey to discuss how their companies approach Big Data utilization within HEOR. Executive
interviews were also conducted with function leaders and others from Medical Affairs and Commercial.

5. Copyright © Best Practices, LLC
5
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

6. Copyright © Best Practices, LLC
6
Quantitative Findings
The following key Big Data findings were observed in this study:
Only 5 of 36 types of Transactional, Reported, Online, Scientific and Machine-
Generated data were rated highly valuable by a majority of study participants.
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.
Six out of ten benchmark participants used post-launch studies around health
outcomes. The second most highly rated reported data type is patient reported
outcomes data.
Half of the study participants said they have a centralized/dedicated group (Big
Data team or function) to support Big Data projects.
Post-Launch and
Customer Segmentation
Studies Most Common
Big Data Projects
Most Have Centralized or
Dedicated Big Data Team
or Function
Only 5 of 36 Types of Data
Rated as Highly Valuable

7. 7
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Health outcomes
(provider/ payer
reported)
Patient reported
outcomes (PRO)
Government
surveys (e.g.,
NHANES)
Internally-driven
market research
surveys
Reported adverse
events
Call center &
customer care
Focus groups
Impact of Reported/Survey Data (HEOR)
Highly impactful Somewhat impactful Not impactful Not used
Reported Data: HEOR Highly Values Health Outcomes Data
Sixty percent of the study participants in HEOR roles said for Big Data studies they highly value
health outcomes data from providers and payers. Patient reported outcomes data was the second
highest rated reported data type.
N=15
Q: How impactful (or valuable) has each of the following types of reported/survey data sources proven to be?

8. 8
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Impact of Data Producers (HEOR)
Highly impactful Somewhat impactful Not impactful Not used
HEOR: Commercial Payers Seen as Most Valuable Data Producers
HEOR leaders found commercial payers to be most impactful. HIEs may constitute a larger share of
data in the future because of federal payments for participation in data sharing programs.
N=15
Q: How impactful (valuable) is each of the following types of data producers?

9. 9
Division On Centralization Persists for HEOR
HEOR leaders split evenly on the question of whether analytics was centralized. Across functions,
the industry is still figuring out what Big Data is, who executes it, and where it lives.
N=15
Q: Do you have a centralized/ dedicated group of individuals to support Big Data projects?
Yes
50%
No
50%
Dedicated Big Data Team
(HEOR)

10. 10
0%
10%
20%
30%
40%
50%
60%
70%
80%
North America EU Europe (nonEU) Asia
Big Data Capabilities and Governance by Region (HEOR)
Regions with Big Data capabilities Region where governance resides
HEOR Reports A 40% Governance Gap in North America
HEOR leaders say their Big Data governance is more likely to be based in the EU than North
America, but their capabilities are more often in western hemisphere.
N=15
Q: Please indicate the regions below where your organization has Big Data capabilities, and where Big Data
governance resides.

11. 11
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Rules about what analysis commercial functions can perform using Big
Data
Rules about what analysis medical functions can perform with Big Data
Rules on Big Data insights-sharing between commercial and medical
Rules governing disclosure of findings to public
Rules on proactive vs. reactive use of insights from Big Data
Rules on disclosure from regulatory perspective
Rules on publishing
Policies establishing clear ownership for various data types across the
company’s information silos
Policies and procedures for accessing data (e.g., who can see what)
Policies governing protecting identification/ de-identification of patient
level data
Policies governing clear ownership of IP generated through a
partnership
Policies regarding review/ approval of research protocols
Prevalence of Data Governance Policies (HEOR)
HEOR: Majority have Range of Data Governance Policies
HEOR leaders reported relatively similar policy frequencies to those reported by medical leaders.
N=15
Q: Which of the following policies and procedures are in place at your company to govern Big Data activities?

12. Copyright © Best Practices, LLC
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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.
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