Turning Big Data into a competitive advantage? Challenges and opportunities

Transcription

1 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

2 Increasing market complexity 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 2

3 Unsustainable operational costs 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

4 Twin pressures cannot be solved with piecemeal solutions Databases Spreadsheets Custom applications Increasing complexity Unsustainable costs Many life sciences companies lack a cohesive, end-to-end technology solution for their information, applications and infrastructure 4

5 Key trends driving change in the pharma marketing model Brand-centric to customer-centric The customer has more control Create customer-focused content and engagement opportunities Changing channel mix Must orchestrate all channels Manage and utilize all points of the customer lifecycle Performance accountability Expectation of demonstrable ROI Measure and report results of multiple tactics Exploding data sources Must convert to insight and action Collect and analyze real-time data and choose when to act 5

6 The changing environment combined with emerging data sources are driving the explosion in data types and volumes Big data spans 4 dimensions: Volume, Velocity, Variety, Volume Volume Every day, new data sources are being created across multiple channels which is rapidly turning terabytes into petabytes of information Velocity The speed at which information is made available is accelerating, shifting from monthly to weekly to near real time Variety What makes the future of data BIG is that is not just syndicated data, but all data; structured and unstructured Value 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 6

7 New sources of information that define Healthcare Big Data are emerging and generating unprecedented data volumes Social Media Rise of social media as an influencer Consumer-directed healthcare Electronic Medical Records Data providing a detailed clinical picture within the site of care and contribute to an overall picture of a patient s treatment pathway Real-World Evidence Privately-funded-sourced and government sponsored longitudinal studies (increasingly required by payers) Personalised medicine Genome data bringing exponential value to medicine 7

8 Papal history as witnessed at the Vatican 8

9 The new customer engagement model New capabilities are required to engage with customers in today s technology rich environment, need for intelligence over information has never been so great Website visits and registrations Social networking Remote speaker education and programs and survey responses Sales rep detail with ipad Direct mail responses Text messages Non-personal interactions Customer Personal interactions Telesales detail Customer service call Medical apps and portal visits KOL/ Thought leader Mobile apps Devices/ search engines Conventions 9

10 New questions will need new answers - what do you want to know and how can it help you achieve better results? Big Data analytics: better insights with better profiling.. Basics Numbers Opinions Behavior Influence 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? 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? 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? 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? 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? 10

11 Big data = big opportunities and big challenges With the new and emerging sources of information new (IT) capabilities are required to optimize commercial operations = 3,8, and it is good enough * Consuming BIG Data and getting it to those who need it, in a timely and cost effective way Inexactitude / Go for Big and know more Cloud-technology and Master Data Management (MDM) (*) Forrester Report: The Forrester Wave : Master Data Management Solutions, Q

12 Current State Identified needs 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 How to bridge the gap? 12

13 Prescriber preference Integrated cloud platform for Big Data and analytics Prescription and sales, client data Channel profiles, behavior Integrated marketing automation: golden customer record, campaign management Sales force effectiveness: planning, (mobile) CRM and bonus and incentives calculation Social Media listening: understanding brand reputation impact, adverse events Performance management: brand, launch, SF, executive reporting Cloud point-solutions 13

14 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