Life Sciences: Leveraging Customer Data for Commercial SuccessCognizant
The document discusses how life sciences companies need to leverage customer data through master data management solutions in order to succeed commercially in an evolving healthcare landscape. It describes how the healthcare buying process has become more complex with new stakeholders influencing decisions. An effective customer data strategy is critical for life sciences companies to maintain a 360-degree view of customers and address the changing dynamics. This requires solutions that consolidate data from multiple sources to provide insights that can optimize commercial activities like marketing and sales.
How Pharma Can Fully Digitize Interactions with Healthcare ProfessionalsCognizant
This document discusses how pharmaceutical companies can fully digitize their interactions with healthcare professionals (HCPs). It notes that HCPs are increasingly using digital technologies and prefer engaging with pharmaceutical companies through digital channels. The document recommends that pharmaceutical companies build an end-to-end digital platform to facilitate various types of virtual interactions with HCPs, including web conferences, email marketing, e-detailing apps, social media management, and more. It emphasizes the importance of collecting and analyzing HCP interaction data across channels to develop a unified, customer-centric view of each HCP in order to better understand and serve their needs and preferences for digital engagement over time.
Serialization: Driving Business Value Beyond ComplianceCognizant
Serialization and track-and-trace capabilities are not just useful for meeting regulatory compliance mandates; pharmaceutical companies can also explore their use to improve supply chain planning and operations, elevate patient engagement, and increase sales and marketing effectiveness.
In recent years, medical device manufacturers have embarked on an acquisition binge. We’ve seen a series of blockbuster deals as well as numerous smaller transactions. This M&A bonanza has been sparked in part by the belief that absolute scale creates competitive advantage.
But does it? In many other industries, we find a clear correlation between overall scale and profitability. Classic strategy has long focused on building scale because larger companies tend to wield more influence with customers and have a greater ability to maintain pricing discipline. They also benefit from the most accumulated experience with driving down costs and can spread costs over the widest base of business.
Yet in medtech, the correlation between industry scale and profitability is quite weak. Instead, Bain research shows that profitability is more a function of category leadership than overall scale.
Pharmaceutical Mergs Acquisitions in the USCapgemini
The document analyzes trends in pharmaceutical mergers and acquisitions (M&A) in the US from 2007-2015. It finds that M&A deal value and count increased dramatically in 2014, driven primarily by a few "megadeals" over $5 billion. However, over 90% of deals were smaller acquisitions under $5 billion. These smaller acquisitions typically aimed to acquire companies with recent drug approvals, promising pipelines, or expertise in specific technologies. The document also finds a correlation between small biotech companies being acquired within a few months of receiving a new drug approval.
Historically, the medical device industry has been highly attractive and relatively stable. As a consequence, established players have been able to compete successfully across the device spectrum, applying common business models and processes without much need for differentiation.
The future, however, is very different as disruptive change is underway. Companies will need to look at new segments and offer end-to-end solutions to secure additional revenue and maintain their profit margins.
Life Sciences: Leveraging Customer Data for Commercial SuccessCognizant
The document discusses how life sciences companies need to leverage customer data through master data management solutions in order to succeed commercially in an evolving healthcare landscape. It describes how the healthcare buying process has become more complex with new stakeholders influencing decisions. An effective customer data strategy is critical for life sciences companies to maintain a 360-degree view of customers and address the changing dynamics. This requires solutions that consolidate data from multiple sources to provide insights that can optimize commercial activities like marketing and sales.
How Pharma Can Fully Digitize Interactions with Healthcare ProfessionalsCognizant
This document discusses how pharmaceutical companies can fully digitize their interactions with healthcare professionals (HCPs). It notes that HCPs are increasingly using digital technologies and prefer engaging with pharmaceutical companies through digital channels. The document recommends that pharmaceutical companies build an end-to-end digital platform to facilitate various types of virtual interactions with HCPs, including web conferences, email marketing, e-detailing apps, social media management, and more. It emphasizes the importance of collecting and analyzing HCP interaction data across channels to develop a unified, customer-centric view of each HCP in order to better understand and serve their needs and preferences for digital engagement over time.
Serialization: Driving Business Value Beyond ComplianceCognizant
Serialization and track-and-trace capabilities are not just useful for meeting regulatory compliance mandates; pharmaceutical companies can also explore their use to improve supply chain planning and operations, elevate patient engagement, and increase sales and marketing effectiveness.
In recent years, medical device manufacturers have embarked on an acquisition binge. We’ve seen a series of blockbuster deals as well as numerous smaller transactions. This M&A bonanza has been sparked in part by the belief that absolute scale creates competitive advantage.
But does it? In many other industries, we find a clear correlation between overall scale and profitability. Classic strategy has long focused on building scale because larger companies tend to wield more influence with customers and have a greater ability to maintain pricing discipline. They also benefit from the most accumulated experience with driving down costs and can spread costs over the widest base of business.
Yet in medtech, the correlation between industry scale and profitability is quite weak. Instead, Bain research shows that profitability is more a function of category leadership than overall scale.
Pharmaceutical Mergs Acquisitions in the USCapgemini
The document analyzes trends in pharmaceutical mergers and acquisitions (M&A) in the US from 2007-2015. It finds that M&A deal value and count increased dramatically in 2014, driven primarily by a few "megadeals" over $5 billion. However, over 90% of deals were smaller acquisitions under $5 billion. These smaller acquisitions typically aimed to acquire companies with recent drug approvals, promising pipelines, or expertise in specific technologies. The document also finds a correlation between small biotech companies being acquired within a few months of receiving a new drug approval.
Historically, the medical device industry has been highly attractive and relatively stable. As a consequence, established players have been able to compete successfully across the device spectrum, applying common business models and processes without much need for differentiation.
The future, however, is very different as disruptive change is underway. Companies will need to look at new segments and offer end-to-end solutions to secure additional revenue and maintain their profit margins.
As pharmaceutical manufacturers look for ways to build
stronger relationships with their Integrated Delivery Network
(IDN) clients, RWE is emerging as a desired infrastructure
capability, presenting a window of opportunity to support and
collaborate on IDN efforts. If done well, these RWE-related
partnerships should provide value for both parties involved
but require pharma to expand its mindset beyond
product-specific approaches.
Businesses face a multitude of challenges in today’s environment. The overall speed of business is constantly increasing. Decisions are made within minutes and channels are diversifying rapidly. Perhaps most importantly, face-to-face interaction has started to become a luxury, rather than a necessity or consequence of everyday behavior.
Today’s consumer and how contact data affects relationships - An Experian QAS...Steven Duque
This document discusses a study on how data quality affects customer experience. Some key findings:
1) Businesses are motivated to improve data quality to increase efficiency, enhance customer satisfaction, and enable better decisions. However, many still struggle with inaccurate contact data.
2) On average, businesses believe 17% of their customer data may be inaccurate, most commonly due to incomplete, outdated, or duplicate records. Inaccuracies waste an estimated 12% of departmental budgets.
3) Improving data quality can positively impact the customer experience across channels by preventing errors, consolidating duplicate records, and enabling personalized outreach. But accuracy must be established before leveraging data analytics.
From Complexity and Frustration to Simplicity and Effectiveness it is the most viable foundation for discovering new opportunities that build momentum and inspire growth.
Business model approaches to survive and thrive ncpdp - finalGeorge Van Antwerp
My presentation for an NCPDP educational event on 11/2/10 regarding the future of pharmacy. I focus on how technology is creating challenges and opportunities for the pharmacy business model.
This document summarizes a meeting between representatives from Microsoft, Sonoma Partners, and Resurrection Health Care to discuss customer relationship management (CRM) software. The key topics discussed include interactions with customers, processes for consistent operations, and collaboration across teams. Sonoma Partners described their experience implementing Microsoft Dynamics CRM for physician relationship management at Resurrection Health Care's multiple hospital facilities.
Silverlink_SolvingCommChallenge_research_brief_FINALJeff Romano
This document discusses the common challenges health plans face in managing communications with members. It can be difficult to coordinate interactions across marketing, clinical, and customer experience teams due to competing priorities. The document also summarizes the results of a survey of healthcare executives which found that the top technology-related priorities to improve engagement include preferences management, multichannel coordination, analysis and scoring of members, and reducing overlap and intensity of communications. The document concludes by describing how Silverlink's EngageME software aims to address these challenges through a centralized member engagement platform.
Data Granularity and Business Decisions by VCare Insurance CompanyDILIP KUMAR
VCare Case Study shows how data can be analysed based on providing two solutions, one based on aggregate data and other based on granular level of data.
This document discusses the rise of predictive analytics and its value in enterprise decision making. It begins by explaining how predictive analytics has expanded from niche uses to a widely adopted competitive technique, fueled by big data, improved analytics tools, and demonstrated successes. A classic example given is credit scoring, which uses predictive models to assess credit risk. The document then provides examples of other areas where predictive models generate value, such as marketing, customer retention, pricing, and fraud prevention. It discusses how effective predictive models are built by using statistical techniques on data that describes predictive factors and outcomes. The document argues that predictive models provide the most value when applied to processes involving large volumes of similar decisions that have significant financial or other impacts, and where relevant electronic
Financial Stability, a Critical Factor For Choosing a Business Partner, Is E...Dana Gardner
Transcript of a discussion on new ways companies gain improved visibility, analytics, and predictive indicators to assess financial viability of partners across global supply chains.
Importance of High Availability for B2B e-CommerceSteve Keifer
This white paper explains how B2B e-Commerce technologies have become so critical to manufacturing and retail companies that further investment is required in high availability architectures.
The document discusses key trends in digital marketing and lessons learned from 2012. It analyzes data from marketing surveys to compare the practices of "Top Performers" to "Everyone Else". Top Performers are more likely to invest in marketing automation and focus on personalization. While adoption of automation grew in 2012, many organizations still rely on outdated batch email campaigns. The document recommends simplifying automation implementation and focusing on people, process and strategy in addition to technology.
White Paper - Digital strategy and the shift to value based careTerence Maytin
Summary: The U.S. healthcare system is rapidly transitioning from fee-for-service to value- based care as part of massive and ongoing industry-wide transformation. Digital strategy is evolving to meet new challenges, help drive disruptive innovation, and better engage a large, growing audience of connected health consumers.
Whitepaper developed with Pharma Exec magazine on how EIM- Enterprise Information Management- can provide efficiency and kick start innovation by ensuring information flows correctly inside- and outside- the company
- Poor data quality costs the US economy $600 billion annually or 5% of GDP, so it significantly impacts business bottom lines. It also hinders effective customer segmentation and strategic decision making.
- Data quality is defined by how accurate, complete, timely, and consistent the information is. It matters because it affects profits and an executive's ability to make good strategic decisions.
- To ensure good data quality, companies need to build quality processes into gathering, integrating, and leveraging data from multiple sources on an ongoing basis. Outsourcing some of these functions to specialized data partners can complement internal efforts.
The document discusses vendor credentialing in healthcare from multiple perspectives. It explores the two main schools of thought around credentialing - controlling access to hospitals for pricing negotiations versus ensuring safety and security. Experts from hospitals, suppliers, and credentialing companies provide opinions on which school is more prevalent and important. They also discuss efforts over the past year to develop universal standards and best practices for credentialing, but note more work still needs to be done. Opinions are given on how an ideal credentialing system could work to satisfy both providers and suppliers.
1) Hospitals are shifting from mass marketing to targeted direct marketing using customer databases to improve patient acquisition, retention, and win-back.
2) Healthcare marketing goals are similar to consumer companies, focusing on getting more patients, retaining current patients, and regaining lost patients.
3) CRM testing for hospitals showed database marketing can cut marketing costs by over 75% while increasing profitability for existing patients and driving more prospects to their facilities.
White Paper Par Data Quality Managementparabgoteborg
The document discusses achieving and maintaining quality in business-to-business customer data. It notes that 15-40% of the average company's customer data is inaccurate, which can negatively impact business decisions. It recommends regularly auditing customer data against an accurate master database to identify gaps, duplicates, and outdated or inactive customer records. Maintaining accurate and up-to-date customer data through ongoing monitoring and automatic updates is important for effective marketing, reducing waste, and maintaining credibility with customers.
Pharma Analytics provides an overview of analytics in the pharmaceutical industry. The document aims to provide insights into analytics for the pharma sector but details are not yet available as the content is still forthcoming. The author is Pralay Hazra.
This document provides information about the "Big Data & Analytics for Pharma Summit" event taking place on November 3-4, 2016 in Philadelphia. The event will focus on challenges in pharmaceutical R&D, drug development, and safety monitoring, and how analytics can help address these challenges in an evolving market focused on patient-centricity. Key themes include real-world data usage, marketing, business models, decision making, and drug research. The agenda includes keynote speakers from major pharmaceutical companies discussing various analytics applications and case studies.
As pharmaceutical manufacturers look for ways to build
stronger relationships with their Integrated Delivery Network
(IDN) clients, RWE is emerging as a desired infrastructure
capability, presenting a window of opportunity to support and
collaborate on IDN efforts. If done well, these RWE-related
partnerships should provide value for both parties involved
but require pharma to expand its mindset beyond
product-specific approaches.
Businesses face a multitude of challenges in today’s environment. The overall speed of business is constantly increasing. Decisions are made within minutes and channels are diversifying rapidly. Perhaps most importantly, face-to-face interaction has started to become a luxury, rather than a necessity or consequence of everyday behavior.
Today’s consumer and how contact data affects relationships - An Experian QAS...Steven Duque
This document discusses a study on how data quality affects customer experience. Some key findings:
1) Businesses are motivated to improve data quality to increase efficiency, enhance customer satisfaction, and enable better decisions. However, many still struggle with inaccurate contact data.
2) On average, businesses believe 17% of their customer data may be inaccurate, most commonly due to incomplete, outdated, or duplicate records. Inaccuracies waste an estimated 12% of departmental budgets.
3) Improving data quality can positively impact the customer experience across channels by preventing errors, consolidating duplicate records, and enabling personalized outreach. But accuracy must be established before leveraging data analytics.
From Complexity and Frustration to Simplicity and Effectiveness it is the most viable foundation for discovering new opportunities that build momentum and inspire growth.
Business model approaches to survive and thrive ncpdp - finalGeorge Van Antwerp
My presentation for an NCPDP educational event on 11/2/10 regarding the future of pharmacy. I focus on how technology is creating challenges and opportunities for the pharmacy business model.
This document summarizes a meeting between representatives from Microsoft, Sonoma Partners, and Resurrection Health Care to discuss customer relationship management (CRM) software. The key topics discussed include interactions with customers, processes for consistent operations, and collaboration across teams. Sonoma Partners described their experience implementing Microsoft Dynamics CRM for physician relationship management at Resurrection Health Care's multiple hospital facilities.
Silverlink_SolvingCommChallenge_research_brief_FINALJeff Romano
This document discusses the common challenges health plans face in managing communications with members. It can be difficult to coordinate interactions across marketing, clinical, and customer experience teams due to competing priorities. The document also summarizes the results of a survey of healthcare executives which found that the top technology-related priorities to improve engagement include preferences management, multichannel coordination, analysis and scoring of members, and reducing overlap and intensity of communications. The document concludes by describing how Silverlink's EngageME software aims to address these challenges through a centralized member engagement platform.
Data Granularity and Business Decisions by VCare Insurance CompanyDILIP KUMAR
VCare Case Study shows how data can be analysed based on providing two solutions, one based on aggregate data and other based on granular level of data.
This document discusses the rise of predictive analytics and its value in enterprise decision making. It begins by explaining how predictive analytics has expanded from niche uses to a widely adopted competitive technique, fueled by big data, improved analytics tools, and demonstrated successes. A classic example given is credit scoring, which uses predictive models to assess credit risk. The document then provides examples of other areas where predictive models generate value, such as marketing, customer retention, pricing, and fraud prevention. It discusses how effective predictive models are built by using statistical techniques on data that describes predictive factors and outcomes. The document argues that predictive models provide the most value when applied to processes involving large volumes of similar decisions that have significant financial or other impacts, and where relevant electronic
Financial Stability, a Critical Factor For Choosing a Business Partner, Is E...Dana Gardner
Transcript of a discussion on new ways companies gain improved visibility, analytics, and predictive indicators to assess financial viability of partners across global supply chains.
Importance of High Availability for B2B e-CommerceSteve Keifer
This white paper explains how B2B e-Commerce technologies have become so critical to manufacturing and retail companies that further investment is required in high availability architectures.
The document discusses key trends in digital marketing and lessons learned from 2012. It analyzes data from marketing surveys to compare the practices of "Top Performers" to "Everyone Else". Top Performers are more likely to invest in marketing automation and focus on personalization. While adoption of automation grew in 2012, many organizations still rely on outdated batch email campaigns. The document recommends simplifying automation implementation and focusing on people, process and strategy in addition to technology.
White Paper - Digital strategy and the shift to value based careTerence Maytin
Summary: The U.S. healthcare system is rapidly transitioning from fee-for-service to value- based care as part of massive and ongoing industry-wide transformation. Digital strategy is evolving to meet new challenges, help drive disruptive innovation, and better engage a large, growing audience of connected health consumers.
Whitepaper developed with Pharma Exec magazine on how EIM- Enterprise Information Management- can provide efficiency and kick start innovation by ensuring information flows correctly inside- and outside- the company
- Poor data quality costs the US economy $600 billion annually or 5% of GDP, so it significantly impacts business bottom lines. It also hinders effective customer segmentation and strategic decision making.
- Data quality is defined by how accurate, complete, timely, and consistent the information is. It matters because it affects profits and an executive's ability to make good strategic decisions.
- To ensure good data quality, companies need to build quality processes into gathering, integrating, and leveraging data from multiple sources on an ongoing basis. Outsourcing some of these functions to specialized data partners can complement internal efforts.
The document discusses vendor credentialing in healthcare from multiple perspectives. It explores the two main schools of thought around credentialing - controlling access to hospitals for pricing negotiations versus ensuring safety and security. Experts from hospitals, suppliers, and credentialing companies provide opinions on which school is more prevalent and important. They also discuss efforts over the past year to develop universal standards and best practices for credentialing, but note more work still needs to be done. Opinions are given on how an ideal credentialing system could work to satisfy both providers and suppliers.
1) Hospitals are shifting from mass marketing to targeted direct marketing using customer databases to improve patient acquisition, retention, and win-back.
2) Healthcare marketing goals are similar to consumer companies, focusing on getting more patients, retaining current patients, and regaining lost patients.
3) CRM testing for hospitals showed database marketing can cut marketing costs by over 75% while increasing profitability for existing patients and driving more prospects to their facilities.
White Paper Par Data Quality Managementparabgoteborg
The document discusses achieving and maintaining quality in business-to-business customer data. It notes that 15-40% of the average company's customer data is inaccurate, which can negatively impact business decisions. It recommends regularly auditing customer data against an accurate master database to identify gaps, duplicates, and outdated or inactive customer records. Maintaining accurate and up-to-date customer data through ongoing monitoring and automatic updates is important for effective marketing, reducing waste, and maintaining credibility with customers.
Pharma Analytics provides an overview of analytics in the pharmaceutical industry. The document aims to provide insights into analytics for the pharma sector but details are not yet available as the content is still forthcoming. The author is Pralay Hazra.
This document provides information about the "Big Data & Analytics for Pharma Summit" event taking place on November 3-4, 2016 in Philadelphia. The event will focus on challenges in pharmaceutical R&D, drug development, and safety monitoring, and how analytics can help address these challenges in an evolving market focused on patient-centricity. Key themes include real-world data usage, marketing, business models, decision making, and drug research. The agenda includes keynote speakers from major pharmaceutical companies discussing various analytics applications and case studies.
This document summarizes a webinar on analytics in pharmaceutical research and development. The webinar featured presentations from experts at GSK, Tessella Analytics, and Perkin Elmer on trends in data analytics, how big pharma is responding to analytics, and use cases for data platforms. The panelists discussed challenges like managing large and diverse data sources, the need for speed in R&D, and strategies for data management, sharing, and reuse including establishing data standards and computing models that analyze data without moving it. The webinar addressed how data science can help integrate tools to process and visualize complex biomedical data in order to generate answers and insights for research.
Pharma saleforce effectiveness & digital marketing Kvantum Inc
Digital attribution is primarily associated with paid digital media and associated online click behavior. It is assumed that digital is effective, and since it saves cost of delivery of information it would be an effective channel. Pharmaceutical companies has absolutely no insight into how the digital interaction with the physician and the patient drives the efficacy of their current sales levers. At Kvantum, we help Pharma companies in answering questions like:
Does digital affect the need to reallocate spend on detailing vs sampling
Which type of digital interaction has the most impact on physician behavior when prescribing a drug, and how much time does it take digital interaction to influence that behavior
Does this behavior change with time?
Should the pharmaceutical company invest more in sales reps who can interact with a physician over email or chat?
Should the field sales rep call or meet less often, should part of these meetings be conducted over a digital medium
….
Bottomline, the effect of digital on sales in an unknown
Sanofi Aventis Analytics Journey: Transforming Big PharmaYuri Kudryavcev
This document discusses Sanofi-Aventis' transformation of its financial performance management in Asia Pacific through the deployment of a standardized core model in IBM Cognos TM1. Key points:
- Sanofi-Aventis is a global healthcare leader with diversified medicines and vaccines in 100+ countries.
- Previously, each local operation had different non-standard planning and reporting processes, making regional visibility difficult.
- The project aimed to build an analytics platform for standardized planning/reporting across APAC, going mobile, and accelerating key finance processes.
- PMsquare partnered with Sanofi to deploy the core TM1 model to 3 countries every 6 months, balancing standardization
Savvius Vigil is the first network appliance able to intelligently store months of packet-level information to enhance security investigations. Savvius Vigil integrates with your existing SIEM platform to examine packets related to a breach weeks or months after the incident occurred. This information is often vital to a full understanding of the threat.
How SAP HANA can provide value for Pharma R&DMarc Maurer
This document discusses how SAP's in-memory database HANA could help address challenges in pharmaceutical research and development. It outlines data management challenges in pharma R&D, how HANA addresses these challenges through its real-time analytics capabilities, and potential use cases for HANA in areas like genomics, clinical trials, and drug development. The document proposes starting a discussion between pharma R&D and SAP/HPI to explore how HANA could help solve existing problems or future challenges.
MediSafe - Mobile Medication Management PlatformJon Michaeli
• MediSafe is a mobile-first medication management platform, different from a pill reminder application, because it addresses all of the major causes of non-adherence -- forgetfulness, lack of support, emotional distress, information overload, low engagement, and rising medication costs (in the form of copays).
• MediSafe engages patients in their treatment by sharing results (e.g. via lab tests and biometrics), motivates futher through connections to physicians and care teams, and offers a holistic and simplified approach to managing their health via related educational content (e.g. diet, exercise), easy access to prescription refills, and other value added services.
• MediSafe is the industry leader with over 1.3 million downloads and hundreds of thousands of weekly active users across iOS and Android smartphones and tablets.
• MediSafe apps have earned a 4.5 star rating from 50,000+ reviews across Google Play and iTunes app stores.
Data Mining and Big Data Analytics in Pharma Ankur Khanna
The document proposes software solutions for drug research, including text mining, data warehousing, data mining, database development, and big data analytics. It discusses common challenges in drug research like the high costs and low success rates. It then describes various solutions like text mining patents and research to help identify new research opportunities and reduce duplication of efforts. It provides examples of how various pharmaceutical companies use data mining and warehousing techniques. Overall, the document pitches different IT solutions that can help pharmaceutical and life sciences companies address their research challenges and make their processes more efficient.
SAP HANA Use Cases for Pharma Research & DevelopmentMarc Maurer
This document discusses how SAP's in-memory database platform called SAP HANA could benefit pharmaceutical research and development. It provides an overview of SAP HANA's technology capabilities such as massively parallel processing, large in-memory datasets, and text analytics. It then discusses proof points of SAP HANA's use in genomics to dramatically speed up DNA analysis. The document outlines potential use cases of SAP HANA in areas like secondary analysis of genome data, clinical trial data analysis, and virtual patient simulation. It concludes by recommending next steps for pharmaceutical companies to start
Ensuring Profitable ROI in Pharma Marketing (mini)Eularis
The Pharmaceutical environment is turbulent and, as a result, what used to work to create industry-wide growth of 20% no longer does. The profit generated from brands is in decline as market growth slows in the major Pharmaceutical markets and this inevitably leads to marketing budget cuts.
The only way for a brand to grow effectively - and cost-effectively - is to improve the bottom line effectiveness of each marketing spend. Pharmaceutical marketers are under even more pressure to get more ‘bang for their buck’ from their marketing spend and be able to justify it.
This in-depth report answers the questions that Pharmaceutical marketing directors are asking:
* How do we successfully measure our individual marketing activities’ bottom line return, and prove it to the CFO?
* How do we prove exactly which marketing components are really growing our bottom line
* How do we know what aspects need to be changed, and how, to grow the bottom line by a specific amount
This report explains the different methods being used such as ROI, promotional response models, econometrics and predictive algorithms and the pros and cons of the different approaches.
There are step-by-step guidelines on successfully implementing these approaches for real and measurable results and numerous case studies of actual Pharma brands who have successfully navigated these waters. Consideration is given to what they did to measure and improve - and prove - bottom line return.
There are step-by-step guidelines on successfully implementing these approaches for real and measurable results and numerous case studies of actual Pharma brands who have successfully navigated these waters. Consideration is given to what they did to measure and improve - and prove - bottom line return.
The report will help Pharmaceutical marketers navigate and understand marketing analytics and develop skills to harness competitive advantage.
This report will focus on:
* The practical skills every marketer needs for measuring the effectiveness of their marketing
* Which tools and best practices really make a difference
* The measurement principles that drive successful marketing measurement
* How to propel strategy, growth, and bottom line return
* Case studies in measurement of sales force return, eDetailing return, compliance/adherence programs, CME speaker programs, advertising campaigns, PR campaigns, CRM implementation return, and much more
* Key points of relevance in these case studies
* New ideas you can apply to your area of marketing responsibility – be it sales force, advertising, eDetailing, CME, CRM, PR or any other related field.
Pre-Launch Planning: Priming Your Pharma Brand For Profit And Success (mini)Eularis
In today’s environment, Pharmaceutical companies find themselves in a bind. Until recently, if drugs made over $500 Million in annual revenue within 3 to 5 years of launch, they were considered hugely successful. They were a support to an extensive company portfolio and a component of greater company profit.
However, things have changed. The standards for a successful drug have become much higher and much more dangerous. With so many revenue-producing drugs going off patent, companies are facing large holes in their balance sheets and sales that are increasingly slow.
Plus, with the stakes high and available funds low, pipelines are drying up. Add to this the closer scrutiny of safety issues, the rise of Generics, slower physician acceptance and adoption of new therapies, and the Pharma Industry is in trouble.
More and more, companies are expecting marketers to be instrumental at the key moment of launch, and marketers are under extreme pressure. To deliver on the high hopes of Pharmaceutical brand launch, companies must engage in comprehensive pre-launch planning.
In this report we analyze why launch is increasingly important, the issues involved in pre-launch planning, including key organizational strategies, marketing tactics, regulatory considerations, global issues, and methods for ensuring the most effective plans.
Data-driven Healthcare for the Pharmaceutical IndustryLindaWatson19
The tremendous opportunity of a data-driven strategy is apparent to the pharmaceutical industry, as all these informational assets exhibiting volume, variety, and velocity need to be ingested and analyzed for enhanced insight leading to better business decisions to address proactively the needs of patient care, while getting to market cheaper, faster, with better products.
Life Sciences: Leveraging Customer Data for Commercial SuccessCognizant
As the healthcare buying process becomes increasingly complex, master data management solutions focused on customer relationships are critical for life sciences companies to excel.
Solutions to the complexity of pharmaceutical sales data managementMohammad Qureshi
This document discusses the objectives and challenges of a pharmaceutical organization in managing large amounts of complex sales data from multiple sources. It introduces PAGE 44 as a company that provides data management solutions tailored to the pharmaceutical industry. PAGE 44 has in-depth industry knowledge and technical capabilities to extract valuable insights from sales data in order to improve strategic decision making, sales force effectiveness, and business performance.
The document discusses how analytics are being used to drive effectiveness in Medicaid programs and health plans. It notes that Medicaid spending has grown 450% in the past two decades and will cover nearly 100 million Americans by 2020. Without advanced analytics, Medicaid agencies and health plans will be unable to effectively identify, stratify, and manage the high-cost, high-risk patients in the Medicaid population. The document outlines how the most effective organizations are using predictive analytics to measure performance, identify areas for improvement, manage risks, and influence health outcomes and costs.
- The document discusses how healthcare organizations can better understand physician referral patterns by capturing and analyzing referral data across different systems and departments.
- It recommends using a standardized data collection strategy and database to pull aggregated information on physician relationships and referrals on a continuing basis.
- The Physician360 dashboard helps track the physician experience, identify where referrals are lost, and monitor key indicators to discover issues and improve patient retention. It provides a more holistic view of physician relationships beyond just referrals.
How to Leverage Increased Data Granularity in the ICD-10 Code SetPerficient, Inc.
A webinar designed for healthcare professionals. We explore how to leverage the increased data granularity in the ICD-10 code set. While there are risks, a properly executed ICD-10 implementation will deliver plentiful rewards.
The Physician Value Index: A Framework for Optimizing Marketing Performance ...Medikly
There have never been more ways to reach HCPs, yet it’s never been so challenging to effectively engage them. HCPs now choose when, where, how, and if they interact with pharmaceutical companies.
This white paper proposes a new model, the Physician Value IndexTM, which integrates four key aspects of how a physician interacts with a pharmaceutical brand—presence, participation, influence, and sentiment.
Reading this white paper will show you how to:
Incorporate this new capability model
Better measure marketing performance
Drive business value
Justify spend through real-time, data-based insights
This document discusses data mining applications in healthcare. It describes how data mining can be used by payers to detect fraud, by physicians to identify effective treatments, and by hospitals to predict patient readmissions. It outlines the standard CRISP-DM process for data mining and discusses challenges like data accuracy and interoperability. Examples of data mining techniques discussed include classification, regression, clustering, and association rule mining. The document recommends using SAS software for its advanced analytics capabilities and applicability to use cases like fraud detection and predicting patient risks and treatment effectiveness.
The document discusses how healthcare analytics can be used by hospitals and health systems to reduce costs and improve patient care and outcomes. Specifically, it outlines how analytics can help cut administrative costs, support clinical decision making, reduce fraud and abuse, improve care coordination, promote patient wellness, and manage large volumes of healthcare data. The top 10 healthcare data analytics companies are also listed, including IBM, OptumHealth, Oracle, Verisk Analytics, Medai's Health, MedeAnalytics, McKesson, Truven Health Analytics, Allscripts Healthcare Solutions, and Cerner.
This document outlines a vision for next-generation commercial capabilities within the pharmaceutical industry. It discusses the paradigm shift occurring as healthcare markets evolve more rapidly, driving the need for pharmaceutical companies to innovate their commercial models to navigate increasing complexity and costs. It proposes a collaborative model where companies leverage external partners' expertise in analytics, technology, and skills alongside internal assets to build commercial centers of excellence. These centers of excellence would standardize processes while clustering subject matter expertise to develop capabilities as a strategic differentiator and recognize efficiencies over time. The goal is to provide faster access to insights from vast and diverse healthcare data sources to implement locally relevant solutions on a global scale.
Scenario A specialty memory chip manufacturer is located in South.docxkenjordan97598
Here are three strategic goals that align with the vision and mission statements:
1. Improve quality of care by investing in advanced medical technology and equipment. This supports the mission of providing quality services and the vision of becoming the leading healthcare provider in the region.
2. Expand patient services to include primary care, dental, behavioral health and community outreach programs. This will help achieve the mission of educating the public and the vision of growing the facility over time.
3. Develop strategic partnerships with insurance companies and government organizations to increase patient volume and ensure financial sustainability. This supports both the mission of serving the local community and the vision of a larger, more profitable facility in the long run.
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Using Advanced Analytics, Drug Makers Reach Decision-Makers More Effectively
1. Using Advanced Analytics, Drug Makers
Reach Decision-Makers More Effectively
By analyzing digital footprints, pharma companies can better identify key
influencers throughout their integrated delivery networks.
Executive Summary
Integrated delivery networks (IDN) are meant to
reduce the cost of healthcare while improving the
quality of care. But each IDN has its own unique
organizational structure, and the same physi-
cian may have a different level of influence over
medication choices in multiple IDNs. This new
landscape makes it harder than ever for pharma-
ceuticals providers to cost-effectively target the
decision-makers that have the greatest say in
choosing which medications each IDN provides to
patients.
In some IDNs, a central corporate group main-
tains firm control over its formulary of preferred
medications. In others, local sites or individual
physicians are given more autonomy. To make
the challenge more complex, physicians who are
closely affiliated with one IDN may face restric-
tions in what they may prescribe while working
in an IDN facility. Physicians may, however, have
more freedom to prescribe from another clinic
with which they are affiliated that is not part of
that IDN.
Finally, each IDN has its own policies detailing
which of its employees are authorized to speak to
sales reps. That makes it essential to understand
each IDN in order to reduce wasted sales effort
and avoid inconveniencing or annoying a physi-
cian who might otherwise become a champion for
a medication at another IDN.
By combining and analyzing data — such as Web
sites listing physician affiliations with IDNs, CRM
records of past interactions with physicians and
online prescription data — pharmaceuticals com-
panies can create more detailed and accurate
maps of each IDN and the role of formulary deci-
sion-makers within them. Using these maps, they
can execute more efficient sales campaigns and
conduct a strategic analysis of how their brands
are performing in regional or national markets.
Such digital data, which accumulates around
people, organizations and processes — or a Code
Halo™ — is fast becoming the competitive linchpin
for organizations in far-ranging industries, includ-
ing healthcare, retail, manufacturing, financial
services and media/entertainment.1
For instance,
our research shows that through the use of analyt-
ics mapping, a leading pharmaceuticals company
could increase sales by more than $22 million to
just six IDNs, and by $750,000 to $1 million for
each of another 50 IDNs.
This white paper describes how our unique data
analysis and modeling techniques deliver Code
Halo-based IDN organizational maps that reduce
our clients’ cost of sales while expanding their
market reach amid fundamental changes in the
U.S. healthcare delivery system.
cognizant 20-20 insights | december 2014
• Cognizant 20-20 Insights
2. cognizant 20-20 insights 2
Figure 1
IDNs in Transition
Recent reforms are designed to reduce uncoordinated care. However, the new integrated
delivery networks make it more difficult to identify medical decision-makers.
The IDN Landscape
Historically, physicians have operated in what
some have called a cottage industry of small or
solo practices.
IDNs arose in the late 1980s to mid-1990s with the
aim of reducing waste by integrating caregivers
(see Figure 1). Since then, IDN adoption has been
driven by managed care and other risk-sharing
models that require reviews to take place before
procedures are conducted. Other drivers include
patient-centered medical homes that aim to coor-
dinate all patient care through a primary care
physician and an accountable care organization
(ACO).
Each of these trends underscores the move away
from a comparatively simple model in which phar-
maceuticals companies could easily identify and
contact individual physicians with prescription
decision-making authority. In the IDN world, the
drug that any given physician might prescribe for
a specific disease state may be defined by cor-
porate headquarters, a regional business unit or
multiple physicians with varying levels of discre-
tion over which medications they may prescribe.
Furthermore, each IDN may comprise different
types of healthcare facilities that share different
relationships with the corporate director, making
it still more difficult to determine who has what
degree of influence in defining formularies.
Tracing the accounts and physicians within an IDN
structure — and the relationships among them — is
a complex but necessary process for pharmaceu-
ticals companies to optimize sales force efficien-
cy. However, past efforts to understand IDNs have
been undermined by:
• A lack of coordination among brand teams
within pharmaceuticals providers, resulting
in sub-optimal targeting of decision-makers
and inadequate representation in a provider’s
formulary.
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Physician
Treatment
Plan 3
Treatment
Plan 1
Treatment
Plan 2
Healthcare
Plan 1
(Makes formulary
decisions) (Makes formulary
decisions)
(Makes formulary
decisions)
(Makes formulary
decisions)
member
of
Covers
treatment
at the IDN
Physician sits in
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Healthcare
Plan 1
member
of
PhPhysiciaiannnPhh
rerecocommmmendsrr s
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Consnsulu ting
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hca
iciaanni i
3. cognizant 20-20 insights 3
• A lack of information about the structure
and decision-making processes within young,
fast-changing IDNs.
• The lack of a single data source for various
IDNs, as well as an effective method of merging
multiple sources of data about them.
We address these challenges with an iterative
analytics methodology that works from the top of
the IDN organizational structure down, and easily
adapts to the structure of each IDN and the needs
of each pharmaceuticals company. This meth-
odology, which has been used successfully to
analyze multiple IDN networks, is more accurate
than earlier approaches because it includes more
complete and detailed information about physi-
cians’ relationships to IDNs.
Our methodology can be used for any product in
the pharmaceuticals space with minimal tweaking.
By streamlining the process, we have reduced the
time to map an IDN network from one week, to
two to three days. The range of data that can be
analyzed and the depth of analysis allows us to
more accurately describe even the most complex
networks, and enables our clients to more effec-
tively predict the number of sales representatives
required to meet their revenue forecasts.
The resulting insights into IDN models and
decision-making have the potential to generate
tens of millions of dollars in revenue for a phar-
maceuticals provider. For instance, tracing the
IDN network helped a top-five pharmaceuticals
company increase the effectiveness of its sales
force by focusing the right resources at the
appropriate levels of the IDN, thereby increasing
mind share and market share for its brands. The
analysis identified the facilities with the greatest
decline in sales, as well as the corresponding
physicians and affiliation network. It also helped
quantify the level of autonomy that physicians
had in each IDN, and reduced costs by focusing
the sales force on the IDNs where doctors had
the most freedom to prescribe their drugs, while
using specialized reps to sell to corporate direc-
tors.
IDN Analytics Solution
Our analytics IDN modeling process creates an
initial model of each IDN using third-party data
that the pharmaceuticals company already owns.
We then combine that data with the client’s own
sales and marketing data and with publicly avail-
able data, using custom algorithms to map and
verify the data. By combining and analyzing a
larger volume of more detailed data from Code
Halos, we help pharmaceuticals clients more
accurately target decision-makers.
Past attempts to trace IDN networks and their
affiliate physician circles have failed largely
because they used physicians as the starting
point. This resulted in multiple complex networks
that were not always complete or accurate. This
model, while valuable, lacks the level of detail and
accuracy required to most cost-effectively target
sales efforts.
Our approach works in the opposite direction,
from the IDN to the physicians. The model draws
on data about the basic structure of each IDN,
including the names and addresses of the facili-
ties in the network. Other data includes lists of
affiliated physicians and the nature of that affili-
ation, such as whether they are a consulting or
attending physician or an employee. Including
this data helps identify consulting physicians
who may have more freedom than an employee
to decide which drugs to prescribe, and who have
influence at other IDNs where they consult. Both
factors could make these physicians a high-value
target for a sales rep.
Combining these various data sources is what we
call a Code Halo “collision,” which occurs when
data from one Code Halo combines with another
to provide a more accurate and detailed under-
standing of customer needs, and a more custom-
ized experience for them. This is a key advantage
of our approach to modeling IDNs and the deci-
sion-makers within them.
As shown in Figure 2 (next page), we build on
the initial model by adding information from the
client’s internal account database and applying
our analytics tools to the combined dataset. We
use complex name- and address-matching algo-
Tracing the IDN network helped
a top-five pharmaceuticals
company increase the
effectiveness of its sales force
by focusing the right resources
at the appropriate levels of the
IDN, thereby increasing mind
share and market share
for its brands.
4. cognizant 20-20 insights 4
rithms to identify previously unknown accounts
and additional physicians who are affiliated with
the IDNs but not captured in the initial data. Our
algorithms and techniques allow us to combine
and analyze third-party affiliation data and the
client’s own account data to deliver deeper, more
accurate insights in less time than our clients
have historically been able to.
A final and vital step is the use of sophisticated
Web research to scan public information sources
to verify our IDN model and resolve questions,
such as whether a specific physician is affiliated
with a specific IDN and the nature of that affilia-
tion. Our streamlined processes ensure this veri-
fication process delivers the most accurate model
as quickly as possible and at the lowest cost.
This model captures accounts and decision-
makers at all levels of the IDN hierarchy. These
include:
• Direct accounts, which are usually hospitals,
outpatient centers, medical groups, clinics
and rehabilitation centers that are owned or
directly managed by the IDN.
• Indirect accounts, consisting of institutions such
as medical schools and pharmacies that are
affiliated with the IDN through nursing homes,
academic relationships or co-ownership.
• Affiliates, which are group practices in which
physicians serving in the IDN are also members
and thus can potentially be influenced by
the IDN.
Figure 2
Distilling Meaning from Code Halo Collisions
Combining and analyzing data from multiple sources helps identify key
pharmaceuticals decision-makers.
1
2
3
4
Network
information Public data
In-house
client sales and
marketing data
Standardized
physician
affiliation data
IDN
Creation
Algorithm
Linkage
Verification
Analysis
IDN + physician
sphere
Insight
into IDN
Insight
into IDN
Standardized
network
data
Data
Cleaning and
Standardization
5. 5cognizant 20-20 insights
Figure 3
Fine-tuning the IDN Sales Effort
Our detailed IDN maps help pharmaceuticals clients target their sales forces.
Distribution
Buying Group
GPO
IDN
Site
Owned
Owned
Corporate Parent
Pharmacy
ClinicHospital
Hospice
Pharma Provider
IDN/ Corporate
Physicians Sit Here
Supplier-Distributor — Corporate Headquarters
Pharma Distribution
Owned Subsidiary
Owned/Affiliated Practices
Owned/
Affiliated/
Leased/
Managed
Practices
Medical Group Nursing Home
Group Practice
Managed Care
Key Decision-Makers Sit Here
MedSurg Distribution/Purchasing
Client Benefits
Strategy teams within our pharmaceuticals clients
use detailed IDN maps (see Figure 3) to help
determine how their products are performing in
the market, where to invest in more sales staff,
and what type of staff to deploy — and where —
to improve the performance of specific products
in specific IDNs. On a more tactical level, these
models (when combined with other data such
as prescription patterns) can help identify when
to target individual physicians instead of, or in
addition to, corporate offices, and which physi-
cians to target on behalf of which products. These
IDN maps can even be used to craft detailed call
plans, including how many times to contact each
physician and the best locations for such meetings.
The data produced by our Code Halo analysis can
also be used to identify key factors that influence
account decisions, as well as individual physi-
cians’ prescribing patterns. Understanding these
factors can help pharmaceuticals companies
implement change in everything from marketing
communications to sales materials, with the goal
of helping to overcome negative perceptions and
reinforce positive messages.
Pharmaceuticals companies can also “individual-
ize” customer interactions to ensure that physi-
cians are contacted only in a manner that is appro-
priate to them, and only about medications they
have the authority to prescribe or recommend
to others. For the pharmaceuticals company, the
benefits include reduced cost of sales, increased
sales force effectiveness and increased sales and
market share for the products that contribute
most to the bottom line.
Looking Forward: Putting IDN
Maps to Use
Pharmaceuticals companies can begin the
journey to a better understanding of their IDN
customers by:
• Identifying specific IDNs in which the
company’s products are not selling well, and
where sales efforts are uncoordinated and
wasteful (to build a business case for better
IDN analysis).
• Identifying existing sources of information
about physicians and influencers in the IDN,
missing information and areas where analysis
could help target sales efforts (to build a
business case for better IDN analysis).
6. cognizant 20-20 insights 6
• Evaluating their current internal big data
capabilities to identify what other sources of
data and skills in data aggregation, cleansing or
analysis they might need to better understand
IDNs (to help them scope an RFP).
• Asking sales reps to identify specific pain
points, such as their inability to reach specific
influencers In specific IDNs to discuss specific
products.
The transition from individual medical practic-
es to IDNs renders the traditional “bottom-up”
method of educating physicians about medica-
tions obsolete. The new IDN world is one in which
the same physician may be a decision-maker in
one IDN and an influencer in another, while having
no latitude in their prescription choices in a third.
Given the need to reduce their cost of sales while
increasing their market share, pharmaceuticals
makers cannot afford to wander without guidance
in this new marketing landscape. Our unique
blend of data and analytics tools provides the
fastest, most accurate IDN maps to ensure phar-
maceuticals companies get the most benefit from
their IDN marketing investments.
Quick Take
Our analytics capabilities helped increase sales
ROI for a major pharmaceuticals provider by
mapping influencers in specific geographies of
interest.
We began by combining our client’s internal
data of approximately 400 accounts, as well as
third-party information that contained roughly
100 accounts, to identify a list of 4,000 potential
influencers. From this data, we used a complex
text-matching algorithm and a hierarchical
structure of the IDN to identify accounts with
direct and indirect affiliation with the IDN, as well
as group practices of affiliated physicians. From
this, we identified 170 accounts, with about 2,000
physicians who would be most useful for our
client to focus on.
Next, we used information from external
customer databases to identify gaps in our rating
of accounts, as well as Web research to verify
accounts whose relationship with the IDN was
unclear. This narrowed the list of key influencers
with strong links to the IDN to 130 accounts, or
about 1,900 physicians.
This list was shared with the field sales force, and
a basic disruption-level analysis was performed to
assess its accuracy. Finally, we developed an IDN
organizational map for the field force to use for
the following activities:
• Identify key influencers based on historical
sales data, their prescription patterns
and the affinity to the clients’ products.
Using further analytics, we advised the client
to segment the customers who were most
relevant in terms of their influence and their
contribution to the number of prescriptions
written.
• Refine the targeting strategy. Doing so
reduced redundant sales efforts by allowing
specialized reps to focus on building relation-
ships across different therapeutic areas within
an IDN.
• Achieve lower costs and better results. Our
analysis helped the pharmaceuticals company
improve the ROI of its sales reps by identify-
ing more influencers in more IDNs in a given
geography. The reps can thus see more influ-
encers — as well as those with the highest value
— (including new customers) in a given area.
Analytics at Work: Boosting Sales ROI