1. Data and Analytics Science (a ResOps shared service)

2. Agenda
1.
DAS Intro
A.
History & Expansion
B.
Mandate & Goals
C.
People
2.
Past Projects Review
3.
Next Steps
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3. DAS Intro
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4. History & Expansion
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For 2+ years, MRG has maintained a team called PDI (Product Development and
Improvement).
•
Team consists of (currently) four people, each with long histories at MRG,
technically focused education, and exposure to a broad array of MRG products.
•
The mandate of this team has been to solve problems that:
•
Are properly and efficiently solved with highly specialized techniques (computer science,
mathematics, statistics);
•
May be specific to a project (e.g. data integration, specialized analysis);
•
May be related to improving a process (e.g. migration to CMS, Dynamic Model)
•
The team has functioned as internal consultants for ad hoc problems, as and when
they arise.
•
Broadly: the team brings a high level of sophistication and efficiency to data,
analysis, and programming.
•
In the new organizational setup, this group’s reach is expanded across DRG.
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5. Mandate & Goals
DAS mandate is twofold:
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Execute
•
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To use technical, statistical, and other specialist expertise to support and execute on advanced analytics
activities across DRG.
Improve
•
•
To make DRG activities effective and efficient through the use of data and analytics.
To provide consultative support, tool and methodology development, and ownership over centralized DAS
services.
DAS goals for 2014:
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Immediate:
•
•
Short term:
•
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Reach out to DRG senior leaders to systematically determine opportunities to execute and improve.
• Where do we already carry out advanced analytics work?
• Where could DAS assist existing functions or generate new solutions for customers?
• Where is data-intensive work being spread too thinly to gain any efficiencies?
• Where do we lack technical expertise to properly conduct analytics?
Medium term:
•
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Continue to execute on a set of active projects (Dynamic Model upgrade, CMS upgrade, ad hoc work).
Choose a subset of these activities and execute!
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6. Meet the Team!
Currently, DAS consists of existing MRG PDI – highly talented, strong technical
focus, demonstrated capability to apply specialized knowledge generally
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Samuli Heilala
•
•
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MSc Computer Science
Fundamental role in migration to CMS.
Robert Huneault
•
•
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MMath Applied Mathematics
Currently leading development of Dynamic Model application; developed statistical/algorithmic
foundations.
Christian Filion
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•
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MASc Management Sciences
Focus on data integration and analysis for Custom group; primary owner of confidential MRG
datasets.
Omnya Elmassad
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•
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MSc Statistics
Focus on developing procedure extrapolation algorithms and production support, new product
development.
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7. Past Projects Review
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8. MT360 Transition to CMS
“How do I standardize, consolidate, and manage 200+ (and growing) sets of
data for a single product line?”
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Developed the data structure (taxonomy, aggregation rules), processes, database, and designed the
content management system language to streamline production
•
Streamlined certain production tasks, facilitating content reuse and improving staffing flexibility by
allowing concurrent content access
Word
Word
Excel
models
Excel
models
DB
Word
Tech-enabled process improvement and advanced data management (operational)
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9. Covidien Consulting Project
“My project has tens of millions of data points. How do I store, manage, use, and
view them in a sensible way and deliver them in a reasonable way?”
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Largest consulting project ever performed by
MRG
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15+ countries and 3 markets of significant depth
researched, modelled, extrapolated, and
forecasted
•
To facilitate data consolidation and
management:
•
•
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Designed a taxonomy for the project
Built a program to consolidate many
models’ worth of data into a standardized
output
Built a viewer to visualize data
Advanced data management (ad hoc)
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10. Teva Consulting Project
“How many, and which, US hospitals do we target if we want to reach a target diseased
population that is within a certain distance of the hospitals, given that each hospital has a
limited capability to perform the treatment?”
•
Applied linear optimization techniques,
used a variety of datasets (epidemiology,
hospital procedure volumes, census data,
geo-location data) to generate a map of
hospitals to target to maximize patient
reach
•
Analysis was repeated for a second client!
Advanced data analysis and visualization (ad hoc)
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11. Single Metric (new product development)
“How do payer restrictions in the US affect my drug’s market access opportunities?”
•
Currently developing a method to use
formulary and prescription-volume data
to measure pharmaceutical market
access
•
Using statistical modelling and data
analysis to assess impact of each payer
restriction on prescription volumes
Advanced data/statistical analysis (ad
hoc)
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12. MedTech Process Improvements
Marketrack – Uploader
DM Curves
“How do I remove the need for
data entry?”
“How do I standardize forecasting?
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Designed a program to upload
Excel surveys directly into
database for one of Marketrack’s
largest set of projects
•
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Currently used in (nearly) all
MT360 models, standard in many
other MRG models
Removed DE bottleneck, facilitating
faster analysis and production
times
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Developed easily parametrizable
forecasting curves for use in
market modelling and forecasting
Since late 2011, over 90% of
surveys entered without DE
support, completely DE-error free
•
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DE in weeks  DE in minutes
Tech-enabled process improvement (operational)
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13. Next Steps
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14. Next Steps
• Evaluate
•
We will be meeting with ResOps groups to understand where this group can be
leveraged.
• Expect meeting requests by EOW. Goals:
• To get management and core-user input on existing activities for which DAS can
execute or improve.
• To determine what unanswered, or un-asked, questions might be solved using
data and analytics.
• Support
•
•
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In the meantime, the DAS team is available for support on existing problems and
questions.
Reach out to me (sandrews@mrg.net) with questions!
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