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Turning “Big Data” into a competitive advantage? Challenges and opportunities Presentation prepared for CIB Symposium by IMS Health Kris Bruynseels, Senior Principal, Technology and Services, IMS Health 6 June 2014

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Turning “Big Data” into a competitive advantage? Challenges and opportunities

Presentation prepared for CIB Symposium by IMS Health

Kris Bruynseels, Senior Principal, Technology and Services, IMS Health

6 June 2014

Increasing market complexity

2

Shifting portfolios to include specialty, high-cost molecules targeted at narrower patient populations

More constituencies influencing prescribing decisions

Broader, more complex market engagement: more channels, bi-directional and across all channels

50% all Phase III and registered drugs are specialty/oncology

Unsustainable operational costs

3

Reduced revenue, resulting from lower market potential of NMEs,

constraints on pricing, higher discounts and rebates

Market and product complexity driving more operational support

throughout value chain

Existing cost containment measures reaching limits

or risking effectiveness

Life sciences companies need to take out $35B in costs over next 5 years to keep margins constant while also maintaining current levels of R&D activities

Source: IMS Institute for Healthcare Informatics. Advancing the Responsible Use of Medicines: Applying levers for change. 2012

Twin pressures cannot be solved with piecemeal solutions

4

Spreadsheets Databases

Custom applications

Unsustainable costs

Many life sciences companies lack a cohesive, end-to-end technology solution for their information, applications and infrastructure

Increasing complexity

Key trends driving change in the pharma marketing model

5

Must orchestrate all channels Manage and utilize all points of the customer lifecycle

Changing channel mix

Must convert to insight and action Collect and analyze real-time data and choose when to act

Exploding data sources

The customer has more control Create customer-focused content and engagement opportunities

Brand-centric to customer-centric

Expectation of demonstrable ROI Measure and report results of multiple tactics

Performance accountability

The changing environment combined with emerging data sources are driving the explosion in data types and volumes

6

Big data spans 4 dimensions: Volume, Velocity, Variety, Volume

• Every day, new data sources are being created across multiple

channels which is rapidly turning terabytes into petabytes of information

Volume

• The speed at which information is made available is accelerating, shifting from monthly to weekly to near real time

Velocity

• What makes the future of data BIG is that is not just syndicated data, but all data; structured and unstructured

Variety

• The key value driver for any data starts with what questions do we want answered and how to generate and integrate insights into key business processes

Value

New sources of information that define Healthcare “Big Data” are emerging and generating unprecedented data volumes

7

• Rise of social media as an influencer • Consumer-directed healthcare

Social Media

• Data providing a detailed clinical picture within the site of care and contribute to an overall picture of a patient’s treatment pathway

Electronic Medical Records

• Privately-funded-sourced and government sponsored longitudinal studies (increasingly required by payers)

Real-World Evidence

• Genome data bringing exponential value to medicine

Personalised medicine

Papal history as witnessed at the Vatican

8

The new customer engagement model

9

New capabilities are required to engage with customers in today’s technology rich environment, need for intelligence over information has never been so great

Text messages

Direct mail

responses

Medical apps and portal visits

Website visits and registrations

Email and survey responses

Mobile apps

Customer service call

Telesales detail

KOL/ Thought leader

Sales rep detail with iPad

Remote speaker education and programs

Conventions

Social networking

Devices/ search engines

Personal interactions

Non-personal interactions Customer

New questions will need new answers - what do you want to know and how can it help you achieve better results?

10

Big Data analytics: better insights with better profiling..

Basics

What is their State Licence #?

Where do they Practice?

Do they have more than one office?

Where are their offices?

Do they see reps?

How long is an average visit?

Do they use other channels to get information?

What channels do they use?

What percentage of the time so they use these channels?

Numbers

What do they write?

What is their TRx?

What is their NRx?

What is their competitive TRx profile?

Why do they write the way they write?

What disease areas do they treat?

What is their adoption pathway - early adopter, laggard?

Why do they sit in this Adoption pathway?

What is their Decile?

Are they a target?

What is their target rating?

How many calls do you plan on making?

How often does the company interact/contact the Physician?

Opinions

What is the theme of their practice?

Do they use compliance programs?

Are they concerned about cost of therapy?

Are they big on Generics?

Do they focus on side effect profiles?

Do they actively check efficacy?

Do they report adverse reactions?

Do they Sample?

What frequency do they sample?

Are they appropriate for Clinical Trials?

Do they like to lunch?

How do they feel about the state of healthcare reform?

How does healthcare reform affect their practice?

Do they endorse or would they speak on behalf of our company?

Influence

What specialists do they refer to?

Why do they refer to that specialist?

Where are these specialists located?

Who are their local key opinion leaders?

Who are their global key opinion leaders?

Who do they influence?

What hospitals are in there geographic area?

What buying groups are in their area?

What patient advocacy groups are in their area?

Which Payer Group covers most of their treatment areas?

Do they teach or have they ever taught?

When did they graduate?

What university did they graduate from?

Did they specialize?

Behavior

Why did they become a Physician?

What is their intention to treat?

How many patients go through their practice?

How many patients do they see themselves?

Are they technology savvy?

Do they use iPads

Do they wear glasses or contacts?

What type of glasses do they wear?

What do they drive?

What type of pen do they use?

What does their office look like?

Big data = big opportunities and big challenges

11

With the new and emerging sources of information new (IT) capabilities are required to optimize commercial operations

“2 + 2 = 3,8, and it is good enough”*

Inexactitude / Go for Big and know more

“Consuming BIG Data and getting it to those who need it, in a timely and

cost effective way”

Cloud-technology and Master Data

Management (MDM)

(*) Forrester Report: The Forrester Wave™: Master Data Management Solutions, Q1 2014

Life sciences company identified needs versus current state

• Proliferated technology systems and applications: siloed and sub-optimal

• Amount of data flowing in to life sciences companies has exceeded their ability to manage and derive value from these sources,e.g. insufficient interpretation and actionable insights

12

Id

en

tifi

ed

need

s

Cu

rren

t S

tate

How to bridge the gap?

13

“Social Media listening:

understanding brand reputation impact, adverse events”

“Performance management: brand, launch, SF, executive

reporting”

“Sales force effectiveness:

planning, (mobile) CRM and bonus and

incentives calculation”

“Integrated marketing

automation: golden customer record,

campaign management”

Prescriber preference

Prescription and sales, client data

Channel profiles, behavior

Cloud point-solutions

“Integrated cloud platform for Big Data

and analytics”

Turning “Big Data” into a competitive advantage? Challenges and opportunities

Presentation prepared for CIB Symposium by IMS Health Kris Bruynseels, Senior Principal, Technology and Services, IMS Health

6 June 2014