Date post: | 15-Jun-2015 |
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Data and Analytics Science (a ResOps shared service)
COMPANY CONFIDENTIAL2
Agenda
1. DAS Intro
A. History & Expansion
B. Mandate & Goals
C. People
2. Past Projects Review
3. Next Steps
COMPANY CONFIDENTIAL3
DAS Intro
COMPANY CONFIDENTIAL4
History & Expansion
• 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.
COMPANY CONFIDENTIAL5
Mandate & Goals
DAS mandate is twofold:
• Execute
• 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:
• Immediate:
• Continue to execute on a set of active projects (Dynamic Model upgrade, CMS upgrade, ad hoc work).
• Short term:
• 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:
• Choose a subset of these activities and execute!
COMPANY CONFIDENTIAL6
Meet the Team!
Currently, DAS consists of existing MRG PDI – highly talented, strong technical focus, demonstrated capability to apply specialized knowledge generally
• Samuli Heilala
• MSc Computer Science
• Fundamental role in migration to CMS.
• Robert Huneault
• MMath Applied Mathematics
• Currently leading development of Dynamic Model application; developed statistical/algorithmic foundations.
• Christian Filion
• MASc Management Sciences
• Focus on data integration and analysis for Custom group; primary owner of confidential MRG datasets.
• Omnya Elmassad
• MSc Statistics
• Focus on developing procedure extrapolation algorithms and production support, new product development.
COMPANY CONFIDENTIAL7
Past Projects Review
02
COMPANY CONFIDENTIAL8
MT360 Transition to CMS
• 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
“How do I standardize, consolidate, and manage 200+ (and growing) sets of data for a single product line?”
Excel models
Word
Word
Word
Excel models
DB
Tech-enabled process improvement and advanced data management (operational)
COMPANY CONFIDENTIAL9
Covidien Consulting Project
• Largest consulting project ever performed by MRG
• 15+ countries and 3 markets of significant depth researched, modelled, extrapolated, and forecasted
• To facilitate data consolidation and management:
• 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
“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?”
Advanced data management (ad hoc)
COMPANY CONFIDENTIAL10
Teva Consulting Project
• 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!
“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?”
Advanced data analysis and visualization (ad hoc)
COMPANY CONFIDENTIAL11
Single Metric (new product development)
• 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
“How do payer restrictions in the US affect my drug’s market access opportunities?”
Advanced data/statistical analysis (ad hoc)
COMPANY CONFIDENTIAL12
Marketrack – Uploader
• Designed a program to upload Excel surveys directly into database for one of Marketrack’s largest set of projects
• Since late 2011, over 90% of surveys entered without DE support, completely DE-error free
• Removed DE bottleneck, facilitating faster analysis and production times
• DE in weeks DE in minutes
“How do I remove the need for data entry?”
DM Curves
• Developed easily parametrizable forecasting curves for use in market modelling and forecasting
• Currently used in (nearly) all MT360 models, standard in many other MRG models
“How do I standardize forecasting?
MedTech Process Improvements
Tech-enabled process improvement (operational)
COMPANY CONFIDENTIAL13
Next Steps
03
COMPANY CONFIDENTIAL14
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• In the meantime, the DAS team is available for support on existing problems and
questions.
• Reach out to me ([email protected]) with questions!