Accenture 2013 Technology VisionEvery Life Sciences Business is a Digital Business

Accenture Life Sciences

Rethink Reshape Restructure...for better patient outcomes

The theme of Accenture Technology Vision 2013 is “Every Business is a Digital Business.” What does this mean for the Life Sciences industry, which is adapting to life in the “new normal” after the peak of the patent cliff1, where governments and private payers must control costs while scientific advances create opportunities to improve patient outcomes. The future high-performing Life Sciences companies (including Pharmaceutical, Biotech, Medical Technology, Consumer aealth and Generics Companies and their regulators) are facing up to this challenging environment by making radical changes in a number of crucial areas:

Business Models: To manage increasing health care costs, Life Sciences companies must provide evidence of outcomes and economic benefits to support specialized therapies.

Specialized Product Portfolios: Thanks to advances in genomics and real-world patient data, Life Sciences companies are developing more personalized medicines.

Shifting Global Markets: To meet patient needs in developing markets, Life Sciences companies must collaborate seamlessly with new partners and adapt to new markets.

New Services: With new opportunities to engage patients, Life Sciences companies can shift their mindsets from products to services, especially with new medical devices and diagnostics providing information to Health Care Practitioners (HCPs) about their patients’ treatment.

Life Science companies are focusing on more intelligent customer engagement. This includes developing new ways of understanding and supporting customers globally and across the healthcare value chain (including payers, providers, regulators, pharmacies as well as HCPs and

Introduction

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Relationships at Scale: Moving beyond transactions to digital relationships

Seamless Collaboration: Right channel, right worker, right job

Design for Analytics: Formulate the questions and design for the answers

Beyond the cloud: The value lies in putting the cloud to work

Data Velocity: Matching the speed of decisions to the speed of action

Software Defined Networking: Virtualization’s last mile

Active Defense: Adapting cyber defenses to the threat

patients) and developing more collaborative and targeted R&D to help improve productivity. It also includes optimizing the end-to-end value chain to reach new markets, drive efficiency and maintain secure supply. Companies will address these digital imperatives through future developments in digital technologies, such as social media, cloud, mobile and analytics. Life Sciences companies that take a lead in understanding the potential of these technologies will thrive in the oncoming era of increasingly specialized medicine and increasingly global markets. As Boston Scientific CIO Rich Adduci has said, “Our industry faces an enormous amount of fundamental change in a compressed time frame. We need to be able to reduce friction, and drive greater collaboration across the entire value chain. And that is what digital businesses can do.”

Understanding technology change is therefore no longer just the realm of IT. It is time for every C-suite executive to grasp its importance and use it to pursue a path to better patient outcomes. Organizations that adopt a higher order of thinking—a digital mindset—will separate themselves from their rivals. Such a mindset is necessary to anticipate and respond to ongoing technology-driven disruptions. Executives can start developing this digital mindset by considering these seven key technology trends:

1. Relationships at Scale Technology has finally evolved to help

Life Sciences companies understand the specific needs of payers, providers, regulators, pharmacies, Healthcare Professionals and patients. It’s time to rethink how Life Sciences companies deliver more personalized service to these customers.

It is time for every Life Science C-suite executive to grasp the importance of technology and use it to pursue a path to better patient outcomes.

2. Design for Analytics Life Sciences companies have potential

access to vast quantities of research and commercial data. It’s not the volume of data per se that is important, but the ability to formulate questions and derive insights from the data that can lead to better products and services.

3. Data Velocity As important as collecting the right

data is the ability to match the speed of decision to speed of action, and to quickly absorb and act on data.

4. Seamless Collaboration Fostering the right environments

between colleagues and partners to allow creativity, productivity and networking across geographical and company boundaries supports innovation and operational excellence. Companies would derive improvements in collaboration by embedding social collaboration into business processes.

5. Beyond the Cloud Cloud computing is already bringing

efficiencies to the health care industry. Life Sciences companies that approach business challenges with a “cloud first” mentality, that weave cloud capabilities into the fabric of their business processes, will increase their operational efficiency.

6. Software Defined Networking (SDN)

Extending virtualization concepts to networks promises to lower IT costs and improve agility of Life Sciences companies. It will simplify collaboration with partners, expansion into new markets, integration of acquisitions and spin-outs of divisions.

7. Active Defense Securing intellectual property and

maintaining control of critical regulated components is a battle as hackers target Life Science companies. Taking an active defense approach moves a company from reactively monitoring to proactively understanding patterns and adapting responses.

It is incumbent upon the executive leadership team to be stewards of this new mindset. They must recognize that it’s no longer possible to separate “the technology” from “the business”; the two are inextricably intertwined. An organization cannot be its best unless it excels at understanding and using technology. This is the essence of the digital business.

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The Life Sciences industry has entered an era in which, in order to grow, it must develop specialized products for specific patient populations and reach customers in rapidly developing markets. This new era requires that companies rethink how they interact with patients, payers, providers and governments in both mature and emerging markets—with speed, with the right information, and scaling their efforts to each target audience. This is a significant change from the focused “feet on the street” model that worked well in mature health care markets. Becoming a digital business represents a shift in the approach to health care practitioners (HCP) and patient engagement. Digital not only affords an opportunity to understand patients better and to deliver customized patient experience, but also to elevate HCP engagement, personalizing it to meet their needs.

Life Sciences companies are also relying on digital services to address requirements of both regulatory agencies and payers and create a differentiated patient experience. The Life Sciences Technology Vision 2012 highlighted Sanofi as a social media leader, thanks to its efforts building communities for diabetes patients on Facebook. Sanofi continues to innovate in providing patient services and connecting with the diabetes community. Its GoMeals® app, for example, engages patients across all aspects of treatment. The app monitors and records both activity levels and blood glucose levels (through integration with the iBGStar blood glucose meter), as well as providing information on diet and lifestyle choices that impact patient outcomes. Its initial efforts with Facebook and apps provide a digital patient platform from which Sanofi can create fuller and richer patient services programs. It will be able to work with its patient community to help identify how further digital efforts can help solve challenges to patient outcomes, such as patient adherence to the prescribed treatment regimen.

Digital applications and social media represent an under-utilized opportunity to listen and provide services to patients and improve patient outcomes. Life Sciences companies benefit from a dual payoff: better patient relationships and a more-differentiated brand.

Elevating Health Care Practitioner EngagementFar-sighted organizations will use digital platforms to complement their traditional selling models with an integrated multichannel strategy that makes information available when, where, and how the health care practitioner wants it. As companies expand in developing markets, such as China and India, the multichannel approach allows companies

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Relationships at Scale: Moving beyond transactions to digital relationships

Delivering Customized Patient ExperiencesLife Sciences companies have been slow to engage patients through social sites and twitter feeds, but patients are already using online and digital media to learn about their conditions, and discuss their stories in online communities like PatientsLikeMe.com. At a minimum, Life Sciences companies now have new ways to understand patients based on increasingly digital interactions, whether through e-mail, social media, targeted web pages, online chat, mobile apps, or tweets. Garnering patient insights from such interactions can allow companies to create more compelling experiences. GSK, for example, used social listening to understand parent’s fears on vaccine usage, which informed their campaigns to dispel myths and fears around vaccinating children.2 In another case, UCB partnered with PatientsLikeMe to establish a free online community for people living with epilepsy.3 The insights gained from listening to patient concerns in this community helps UCB improve its product design, which in turn, will result in better patient experience.

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to broaden their reach to more physicians, responding to their needs for education and information on diseases and the possible products available to help patients.

Companies will increasingly use technology to build relationships at scale for these physicians; that is, interact with them in a personalized and yet cost-effective way. Reaching HCPs outside the major cities in developing markets such as China and India, for example, is a challenge. Arun Gupta, CIO of Cipla believes technology will increasingly play a key role: “Life Science companies face a challenge in engaging with customers on their terms. There are fundamental differences between a doctor working in a metro or city center hospital when compared to smaller practices in smaller cities, towns and semi-urban areas. There is also a digital divide to consider; younger physicians are more likely to accept digital technologies that help with their practice. We need to address these differences across all our markets without increasing the complexity of our business“.

This is a clarion call for mass personalization. Companies are already pioneering down this path through the use of digital technologies. As an example, a biotech pioneer in India, uses a text messaging service as an educational tool for diagnosis and treatment of diabetic patients. The same service allows physicians to call dedicated call centers with detailed questions. Similarly, a western multinational in China is expanding its use of a contact center in a core strategy to engage physicians in more-remote areas which are difficult to reach through in-person visits. Early data from that program suggests that more than two-thirds of HCPs support this new channel. It is no surprise then that a recent survey4 suggests that mastering multichannel marketing was a top business priority for 70 percent

of sales and marketing executives in the industry. Many are already experimenting with multi-channel approaches. The case study (see sidebar) highlights one Global Pharmacutical company’s approach to integrating all customer-facing channels—for example, contact centers, sales reps, Web sites—across the enterprise.

Just as patients have increased their online activities, so too have HCPs.

Start-ups such as Medikly and Creation Healthcare are developing tools to connect publicly available information (such as prescribing data) with what HCPs say in community forums, in order to create a better understanding about physician preferences. Life Sciences companies are also experimenting with gamification techniques to support continuing medical education (CME)5 and disease awareness

Case Study: Journey towards an Integrated Customer Engagement Model

One Global Phamaceutical company’s effort to build digital capabilities illustrates the steps required to become digitally competitive. To implement its new, digitally enabled customer strategy, the company established several coordinated transformation efforts. The first one established a way of codifying every customer interaction across channels. This foundation helped the company to build business rules that allow coordination across channels and provide a 360-degree view of interactions with HCPs, which can be used by clinical and sales functions.

In parallel, the company revamped its master customer database to collect new kinds of data on the health care environment, including how its customers were using digital technology.

The next step in its digital evolution involved integrating a digital marketing platform. It services requests for information from HCPs intelligently and consistently across a variety of formats. The format and messaging is based on the stated or observed preferences (for example, videos, webcasts, e-details) This is a powerful shift in personalizing experience for physicians, in which traditional rep-based detailing becomes one of many ways of engaging with the company.

At this time, the company is considering overlaying the platform with adaptive intelligence that can coordinate a multi-channel response. For example, in the U.S., an HCP emailing a reimbursement question would get a tailored response based on analysis of combined intelligence from past interactions across channels.

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programs. These techniques have achieved unprecedented levels of engagement, suggesting that the HCP community is eager to engage with innovative uses of digital technology.

Health markets are sufficiently diverse that practitioners will continue to make decisions based on factors that go beyond patient outcomes. Physicians within a large integrated facility will make product choices that are in line with the guidelines of their employers, while physicians with large numbers of lower-income patients may prefer to prescribe drugs whose manufacturers offer patient services programs.

The company highlighted in the case study (see sidebar) wanted to learn how health care practitioners seek information and decide which drugs to prescribe. In doing so, it developed a seven-tier HCP engagement and experience model to improve the design of its commercial applications. Every application relating to Sales and Marketing master data is being redesigned to support the new engagement model. Life Sciences companies should ensure that their digital applications collect and assimilate data around these local decision drivers in order to gain an important tactical advantage.

Life Sciences companies will also increasingly use digital technologies to facilitate provider and patient communication. Medical device companies have adopted this concept rapidly, as today’s in-home medical devices can connect to the Internet. As an example, Medtronic’s Paradigm Revel™ system not only monitors and manages insulin levels

of its diabetic patients, but also allows the doctor to remotely adjust the therapy based on the data sent by the device. An Internet-connected device from another in-home medical device manufacturer lets physicians adjust patient titrations online, and also provides them with comparative data about how other clinicians are treating their patients.

The next stage in this evolution is integrated telemedicine with HCPs and Life Sciences companies working closely to not only provide end-to-end care management but also to collaborate on clinical trials.

Integrating Real and Virtual ExperienceThe idea that a single subgroup—for instance, sales or marketing—within a Life Sciences company is responsible for the entire “digital” channel and the relationships it supports does not make sense anymore. These relationships begin during clinical trials and run through the lifecycle of the product. Life Sciences companies will increasingly apply apps and digital technology that enable patient-to-physician communication and remote monitoring during clinical trials, and may also be part of the monitoring regime required for reimbursement. As a result, companies must figure out how all the groups will work in concert. Each group should work toward an overarching, omnichannel relationship strategy, one that promotes collaboration and sharing among channels to manage relationships with customers in an ongoing fashion.

Where to Start?Companies are establishing a solid foundation of master data and using this to understand and address gaps in their multichannel strategies. They are building a better understanding of customer (patient, provider and payer) interactions; identifying questions to be answered to develop a holistic view of the customer and identifying how techniques such as “social listening” can support their digital efforts. To build and nurture digital relationships with customers, companies should create a cross-functional team responsible for reviewing, updating, and improving their customer-relationship strategy, one that is at once holistic and yet still targeted to specific segments within patient and practitioner communities.

Relationships at Scale: Moving beyond transactions to digital relationships

The idea that a single subgroup—for instance, sales or marketing—is responsible for the entire “digital” channel and the relationships it supports does not make sense anymore.

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Life Sciences companies have vast quantities of research and patient data, but often not the “right data” or a way to access it in order to make key strategic decisions. High-performing Life Science companies are differentiating themselves on their ability to drive insights from data. Implementing data standards and curating data to enable it to allow different analytics to be run, is key to their ability to analyze information, but in designing applications that enhance insight they must also understand the questions they want to answer. We believe that top of mind for industry executives are framing the questions which can help them improve R&D productivity and provide evidence of outcomes.

Improving R&D ProductivityIn R&D, scientists and researchers have developed knowledge in designing studies and protocols to answer questions regarding a product’s safety and efficacy. Industry groups such as the Clinical Data Interchange Standards Consortium (CDISC) have established clinical data standards to accelerate analysis of data and to help companies to aggregate it across studies and submit it to regulators for review. The Life Sciences industry has made progress, but the industry must do much more work to establish standards and improve interoperability.

For Pharmaceutical companies, these standards are especially important to provide greater transparency for clinical trials data and to improve their reputation. These standards will also enable companies to develop new insights through collaboration with academic institutions and other third parties across the industry.

But at the most fundamental level, companies must formulate the questions that will help them further develop existing products’ safety and efficacy profiles

and discover new products or uses. That thinking must be the basis for designing new interoperable platforms which aid the ability to better analyze and share data. This effort demands a new mindset among multidisciplinary data scientists who can formulate hypothesis and combine large volumes of structured and unstructured data from a variety of sources to divine insights into new products and capabilities.

With increasingly specialized products comes added pressure to improve the efficiency of the R&D process, so that scientists and R&D executives can deliver greater number of high-quality clinical studies at lower costs. To further drive R&D productivity, Pharmaceutical Companies have an opportunity to address the standardization of operational data which can be used to inform study design; identify sites such as hospitals with a track record as successful sites; identify drawbacks to the site and address patient retention and adherence during clinical studies. Companies will increasingly focus on establishing operational data standards, with companies such as Medidata building metrics into protocols that predict key operational metrics, such as cost per site. Pharmaceutical companies would benefit from building these requirements into their analytics as they move to the next generation of processes and systems for managing clinical trials.

Provide Evidence of OutcomesGathering the right information to address marketing, payer and HCP considerations in clinical trials is increasingly essential for providing evidence of outcomes, essential in getting approval and increasing the potential for reimbursement. Incyte and Novartis were able to design and collect validated patient-reported outcomes (PRO) data for Jakafi6 its treatment for myelofibrosis, a rare and life-threatening disease affecting bone marrow and organs.

Once Phase I/II trial results suggested a marked improvement in symptoms, Incyte worked with the FDA to develop a quality-of-life assessment tool. Eventually, Incyte was able to claim significant symptom improvement through a validated survey of patient reported outcomes. The clinical evidence supported the drug’s approval, allowing Incyte to promote the drug’s benefits using measurable results.

The availability of real comparative evidence is becoming central to products being accepted for reimbursement by payers. Increasingly Life Sciences companies are using disease data to not only justify patient programs but also to develop patient services, such as diagnostics, patient support and adherence programs. They plan to bundle such patient services closely with the product and price them accordingly. Life Sciences companies are also harnessing real world patient data to create other patient and practitioner services that can strengthen their market positions. They are not only assimilating outcomes data from clinical trials, but are also actively augmenting this data with EMR/EHR and payer claims data as well. All of this requires analysis capabilities.

One large global Pharmaceutical Company is building a cloud-based data warehouse that compiles real-world evidence of challenges in using its diabetes product. Such analysis will help identify potential gaps in care coordination across regions, and inform the design of regional patient intervention programs to close such gaps. Eventually, the company is planning to tap into the same data to drive other commercial and clinical decisions. As an example, sales and marketing teams can tailor messages and programs to HCPs based on observed treatment patterns in specific areas, while clinical operations can select sites based the profiles of patients in any given region.

Design for Analytics: Formulate the questions and design for the answers

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Creating a data supply chainWith the explosion in data, it helps to start treating data less as content in a warehouse and more as a data supply chain. Just as the various components of an automobile from multiple suppliers come together on an assembly line, a Life Sciences company’s data needs to be sourced, manipulated, integrated with other pieces of data, updated, and transformed into insight. Just as important is the ability to exchange information with partners and suppliers to incrementally improve the data coming into the supply chain.

The “supply chain” mindset is necessary to translate outcomes and properly address health economics questions from payers and integrated delivery networks. Using the supply chain approach, Life Sciences companies can continually update a product’s safety and efficacy profile, as well as design patient services to track and collect financial costs of the services, and collate similar comparative data across payers to evaluate the effectiveness of their programs.

Where to startDesigning for analytics is more than simply adding data requirements to a software or process. It is blurring the lines between the Life Sciences business processes and with IT functions. For example, the concept of value management –understanding the value of a new product on trial through design and data collection early in its development—has cross-functional impacts. Many companies are recognizing this advantage and creating a prominent new role in the organization, frequently designated as the Chief Data Officer. This role works across traditional functions and champions activities within the organization for collection, prioritization,

distribution, analysis and security of data. This is often the first step to moving towards an insight-driven business. As a way to make further progress, companies should be identifying data gaps and ways these can be filled through a data creation strategy and embedding these requirements into their future systems roadmap.

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As companies have been deluged with discussions of big data, most of the focus has been on the variety and volume of data that can be mined for precious insights. But in the scope of digitization, Life Sciences companies must also pay attention to data velocity: the need to match the speed of decision to speed of action.

Faster decision-making can help improve competitiveness and even help increase revenue in some cases. As companies make more interactions with patients and HCPs digital, velocity will follow. Sales reps can have access to accurate data compiled across internal and external sources on their mobile devices. Marketing executives can see the impact of campaigns engaging HCPs across multiple channels. In R&D, as clinical trials focus more on specialty therapies and personalized medicines, closer monitoring and a more rapid response to results helps improve outcomes for participating patients and speeding up regulatory approval. regulatory approval.

Data velocity strategies are likely to take two approaches. The first approach is to build new capabilities to rapidly absorb and digest data, matching real-time insight to real-time opportunities. The second approach is to capitalize on hybrid models which blend-in real-time data with existing data on an ongoing basis to enhance real-time insight with historic insight.

Matching Real-time Insight to Real-time Opportunities Companies increasingly recognize that the pathology of the same disease in two different individuals can be quite different and hence their response to the same treatment can be quite different. Most new therapies under development today are therefore specialty therapies directed toward treating the devastating diseases of smaller patient populations.

This requires a significant change to the approach companies and regulators take to clinical trials. The FDA has established procedures for licensing specialty therapies, but regulators also increasingly expect continuing detailed monitoring of patients through longitudinal post-marketing studies. These new procedures increase the potential for “in-life” clinical trials, monitoring patients outside clinical settings.

These trials require Life Sciences companies to capture feedback from patients about potential adverse events and outcomes. Companies are developing robust industry platforms to gather and compile this kind of information rapidly. For example, to address requirements for capturing spontaneous adverse events, Accenture teamed with a large global pharmaceutical company to develop a validated patient safety information (PSI) platform (see sidebar for details). Bioelectronics companies are also developing wearable, Wi-Fi-enabled sensors that detect vital information and can relay it to a physician in real time.7

With this type of technology quickly becoming commercially available, in-life post-marketing data collection will become more efficient at generating data that can be used at the right time to make adjustments. Fujitsu8 is developing a phone that is capable of calculating vital signs based on a person’s facial image, a non-invasive way of monitoring patients. Pharmaceutical Companies are also experimenting with embedding sensors in tablets (Proteus Digital Medicines9) or with smart pill boxes like Vitality GloCaps®10 that can collect data on timely pill usage. With the FDA recently approving its first remote monitoring drug trial11, the ability to generate more real time insight through digital technology will both improve patient safety and reduce costs of running clinical trials.

Enhancing Real-time Insight with Historic InsightIn practice, most companies will need to blend real-time data with historic data to identify patterns and gain insights. Life Sciences companies already have access to extensive stores of rich contextual historical data. Most companies receive prescription information from industry sources such as IMS. The UK National Health Service (NHS) recently announced it was making its data available to the Open Data Institute, including prescription data.12 Companies will still want to analyze such data, but blending it with near real-time data will provide cost-effective solutions to ongoing business challenges. For example, companies may tailor the interaction for a physician, identified as prescribing less of a medication, whom the company may lose as a customer.

Furthermore, the gradual shift towards outcome-based reimbursement means that companies can’t afford to distinguish clinical data from real-world evidence. In fact, managing outcomes using both controlled trials and real-world evidence throughout the lifecycle of the product will become an essential feature of future Life Sciences development. Thus R&D leaders and brand managers of tomorrow need to be able to assimilate all available information and correlate it to measured or reported outcomes, and actively identify ways to improve usage through newer indications or by re-designing trials currently underway.

The same shift in the reimbursement environment is resulting in medical devices being designed to collect “in-life” data about the patient that can be used for outcomes discussion with the payers, as well as for improving services provided to the patient. For example, a pacemaker can

Data Velocity: Matching the speed of decisions to the speed of action

improve patient care if an internal chip can detect dangerous arrhythmia patterns and transmit data to alert the physician.

The story is similar in dynamic supply chains. Responding to changes in the supply chain with a combination of historical data and brand new intelligence allows companies to create more responsive and resilient supply chains. Life Sciences companies will establish what we call “control towers,” a person or group responsible for coordinating and integrating multiple efforts. This involves integrating data across multiple sources and performing analytics to drive decision-making in planning and fulfillment, transportation, direct materials supply and external supply.

As the challenges of accelerating data become more sophisticated, the trick will be to apply “hybrid insight” as often as possible. This calls not only for changes in how companies architect their data but also in changes in skills as well. It requires that companies seek out and reward architects and developers who understand the importance of combining data for fast analysis. Those who show an aptitude for blending real-time insight with batch insight—and knowing when to use each—will be extremely valuable.

Where to startLife Sciences companies should create a strategy that matches speed of insight to the window of opportunity to act on them. This means identifying the critical decision-making bottlenecks, and identifying which are data-dependent.

Case Study: An Industry Platform for “In-life” Adverse Event Reporting and Real-time Patient Reported Outcomes

New European Commission regulations have empowered patients, not just health care practitioners, to report spontaneous adverse events. Traditionally, patients under-report medication side effects and companies suffer from missing or poor quality data. Accenture worked with a global Pharmaceutical Company to develop a pioneering Patient Safety Information (PSI) solution that captures spontaneous adverse event data from patients, sales reps and health care practitioners via a website and iPad app, and integrates the data with other sources.

The long-term intent is to develop a data collection platform that—while still addressing security and data privacy requirements—can be repurposed for a number of applications during the post-marketing phase. For example, patient-reported outcomes, non-intervention studies, phase IV studies, and ongoing pharmacovigilance all must collect data, at least in part, directly from patients in an in-life setting. Current technologies designed for these purposes are expensive and complex to use. But by deploying mobile devices with a simple interface, companies can go a long way to realizing this capability.

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To achieve success in a digital world, Life Sciences companies must bring together a wide pool of talent across both geographies and partners. They must enable creativity, productivity and networking in order to help achieve innovation and operational excellence.

Research scientists must work even more closely with those in commercial functions, so that they can identify patient populations and design trials that will not only garner the support of payers and providers, but also deliver distinct value to patients. To ensure availability of products across global markets, companies must also work closely with their network of supply chain partners. Scientists and knowledge

Figure 1: Achieving Seamless Collaboration in Stages

workers, often working in different locations and different organizations, must be able to collaborate seamlessly.

Enterprise collaboration tools (including web conferencing, messaging and social networking) and knowledge management tools (including document databases, and shared intranet/extranet repositories) foster environments that enable innovation and problem-solving. Further productivity gains will come from moving from document-centric approaches to process-centric approaches (see diagram). By embedding social collaboration tools into business processes and the software that supports them, companies will be able to drive adoption. They must think through the

best ways to improve user experience and change culture and behaviors, in order to encourage collaboration.

In short, Life Sciences companies need to think of how they can support collaboration through integration into Life Sciences processes, and apply this across the extended enterprise.

Social Collaboration is ready for integration into Life Sciences ProcessesEnterprise collaboration tools are maturing and can now be integrated into processes. SAP’s Jam tool (incorporating elements of its StreamWork collaboration platform), and Oracle’s Social Relationship Management

Seamless Collaboration: Right channel, right worker, right job

Process Centric

Collaboration Inside and Outside the EnterpriseProcess

CentricWorkflow Engines;

CRM Process Management

Document Centric

Information and Knowledge Management

People Centric

Social networking

Mat

urity

Lev

el

• Publishing finished products the enterprise intranet.

• Sharing works-in-progress with teammates as you co-create them.

• Sharing status

• Discussing issues

• Discovering and building relationships

• Executing structured distributed processes

• Managing structured hand-offs and approvals

• Executing loosely-structured, distributed activities

• Managing unstructured hand-offs, reviews

Fully Networked, Process Driven Collaboration

Internal Collaboration

Basic Enterprise Social Collaboration

Information and Knowledge Management

1

2

Information and Knowledge Management

Social Networking

3

Information and Knowledge Management

Social Networking

Workflow Engines, etc

4

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platform now allow companies to tie collaboration tools into their ERP and CRM packages. In addition, Salesforce.com has integrated its Chatter collaboration tool into its PaaS and SaaS applications, while Microsoft’s SharePoint continues to integrate collaboration capabilities, including its Yammer social collaboration software.

Life Sciences companies may have been reluctant to implement social collaboration in their highly regulated divisions, for fear that the release of unguarded comments might result in unintended consequences. But as productivity and efficiency become more important, companies must figure out how to address privacy and security while still providing capabilities for knowledge-sharing and collaboration.

As an example, one major global Life Sciences company began using Chatter as a mechanism for communicating with its sales force, replacing weekly bulletins and an intranet landing page. It evolved this effort into a wider collaboration tool, encouraging participation of compliance, legal and regulatory staff into conversations. The mobile sales reps also use Chatter to submit service requests. Because the company understands that sales reps’ time on the road is valuable, it set up the system so that the rep only has to type key words such as “email Issue” or “car needs fixing”, and the help desk automatically logs and begins addressing problems without the rep having to call in.

The company has already deployed a mobile infrastructure incorporating Veeva CRM software to improve collaboration, and is now extending those tools so that sales reps can confer with other experts within the organization, with the objective of improving collaboration and working

more closely with HCPs. It is also now looking for ways to extend the use of Salesforce.com products, sourced from the AppExchange, to improve sales team productivity in a variety of ways, from tracking marketing budgets to tracking payments to physicians.

Companies in other industries are using social networking and collaboration applications (such as Chatter, Yammer and Lync) to provide global teams with an improved user experience for collaboration. For example Unilever, working with Accenture13, has implemented a platform, based on Salesforce Chatter, to help connect marketers, brand managers and partners across 190 countries. The digital social platform enhances collaboration by allowing colleagues to collaborate and share knowledge, best practices and creative assets across the business and partners, such as advertising agencies.

The Extended EnterpriseLife Sciences Companies realize that to drive R&D productivity and take advantage of opportunities in new markets, they must work closely with partners. The industry is focusing on new and innovative ways to embed collaboration into business processes and enable seamless communication with business partners. The combination of digital technologies and applications built around collaboration is critical to helping Life Sciences companies to bring new products to market quickly and meet demand in new markets.

For many years companies have individually tried to improve processes in R&D. Point-to-point collaboration solutions were developed with contract research organizations (CROs), investigators and others to drive efficiency and speed

up clinical trials. As R&D has become an increasingly collaborative process, Pharmaceutical Companies are partnering among themselves, academic institutions, and even payers and HCPs, to develop innovative new treatments. The integration of collaboration as part of the process is even more critical in this industry because of a need to manage quality and secure intellectual property and commercially sensitive information.

There are signs that the industry is coming together to address some of its biggest collaboration challenges. The non-profit TransCelerate BioPharma14, established in 2012, focuses on advancing innovation in research and development (R&D) by identifying and solving common R&D challenges for all participants in the Pharmaceutical industry. TransCelerate’s initial areas of focus include development of site monitoring approach and standards, development of a common interface for investigator site portals, industry recognition of study site qualifications and training methods, development of clinical data standards, and establishment of a comparator drug supply. The main technology component—the shared, cross-industry investigator portal—is designed to streamline investigator and site access through harmonized delivery of content and services. It will offer a central point of access and single sign-on for investigators and site staff. The portal has three primary target outcomes: the design and implementation plan for a common investigator portal; harmonized security policy with single sign-on; and common taxonomy and technology.

Cross-company collaboration is also critical in a Life Sciences company’s supply chain. Life Sciences companies are evolving from manufacturers to business integrators.

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Many young biotech companies have already established highly virtual supply chains, while established companies are also outsourcing parts of their supply chains to benefit from operational efficiencies partners can bring. Expansion into new markets increases the challenges, as Life Sciences companies work with new suppliers, contract manufacturers and logistics service providers.

Collaboration within this expanding network is essential for the extended enterprise to operate securely, reliably and efficiently. This is especially important when it comes to supply planning and fulfillment, coordinating a myriad of logistics providers, material suppliers, and contract manufacturers.

Supply chain collaboration relies on aggregating information from multiple partners. In recent years, software companies have begun developing tools addressing these specific needs (for example, SAP’s Supply Network Collaboration, Tracelink, and GT Nexus are examples of cloud-based supply planning and fulfillment platforms). Pfizer’s15 implementation of a cloud-based information exchange framework across 500 supply chain partners has provided it with flexibility to bring in new providers, provide full traceability of components and ingredients, and more efficiently comply with industry regulations. Working with Vodafone in Mozambique, GSK

has developed a simpler but potentially lifesaving use of digital technology to enable supply chain collaboration The use of Technology has boosted vaccination rates by an additional 10%, by allowing clinics to report available supply and anticipated demand in rural areas via mobile phones. The result is a reliable communications channel ensuring that clinics always have enough vaccines on hand.

While consumer packaged goods manufacturers have improved their supply chain collaboration with retailers, Pharmaceutical companies tend to remain isolated from their retailers or pharmacies by their wholesale distribution model. That means they don’t receive timely information on sales and must rely on sales reps to engage with pharmacists. In Italy, a joint venture, between Accenture, PharmaService, and several pharmacy management systems developers, has rolled out the iPharmabay pilot to 4,000 pharmacies to provide a new communication channel with pharmacists. The software provides a virtual agent that integrates with on-site pharmacy management software to provide the ability to create real-time marketing campaigns, to increase efficiency of sales order processing and customer service, and to provide greater visibility of demand.

Where to startTechnology leaders should first investigate the multiple collaboration platforms that exist in the enterprise today, and then identify appropriate business processes where increased productivity through collaboration will drive value. They should look to integrate social collaboration to the most important processes and focus on creating a user experience that will assure adoption and smoothly change corporate culture and behavior.

Collaboration within this expanding network is essential for the extended enterprise to operate securely, reliably and efficiently.

Seamless Collaboration: Right channel, right worker, right job

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Beyond the cloud: The value lies in putting the cloud to work

Cloud computing has gone from an intriguing idea to a core capability so quickly that leading Life Sciences companies are approaching new systems architectures with a “cloud first” mentality. They have found that the scalability, flexibility and responsiveness of cloud computing make it a compelling choice as they move into new markets or launch new products and services. The real “trend” therefore is a shift in focus to the next phase: weaving cloud capabilities into the entire fabric of Life Sciences companies.

Recent IDC research shows that worldwide spending on public IT cloud services will be more than $40 billion in 2012 and is expected to approach $100 billion in 2016, for a compound annual growth rate (CAGR) of 26.4%, five times that of the IT industry’s growth overall16. Life Sciences companies, in particular, have enthusiastically adopted Software as a Service (SaaS)-based CRM platforms such as Veeva, Salesforce, Salesnet, and Microsoft Dynamics. Now they are looking for potential payoffs from other cloud technologies for other areas of the business. Cloud vendors are continuing innovation in areas important to Life Sciences companies, such as cost and security (note that the U.S. Department of Defense17, an entity equally as concerned with security as Life Sciences companies, is already committed to cloud computing18). As a result, Accenture expects that Infrastructure-as-a-Service (IaaS) growth will pick up and Platform-as-a-Service (PaaS) will become the primary approach for application development. Life Sciences companies can now safely extend their cloud strategies to R&D, commercial, supply chain and enterprise functions.

Extending Cloud Thinking In R&DMost Pharmaceutical companies have restricted their cloud deployments for R&D to pilot and niche projects. Regulatory restrictions (governing who can handle data and how) as well as a strong desire to protect intellectual property have limited use of cloud technologies in Pharmaceutical R&D. But R&D requirements for large data sets and associated computing capacity—as well as collaboration across entities—makes R&D a prime candidate for cloud applications. In areas such as bioinformatics19, next-generation gene sequencing20, and molecular imaging and modeling, cloud offers a scalable, cost-effective and high-performance computing environment. In fact, Amazon Web Service (AWS) now offers an entire Life Sciences cloud stack designed to get such research platforms up and running quickly.21 This not only provides access to relevant and essential public data22 but also the tools necessary to analyze data quickly.

But forward-thinking companies are now taking advantage of cloud-based solutions to change their R&D operating models. Pfizer, for example, working with Accenture has implemented the “clinical aggregation layer” - a cloud-based platform for clinical data aggregation and reporting, which allows Pfizer to work more collaboratively with clinical research organizations (CROs) when managing clinical studies (see sidebar for details). The joint vision of the two companies is for this platform to become an industry R&D hub for consolidation and reporting, supporting industry-wide clinical operations and safety. As cloud technologies mature, service providers are devising advanced methods of partitioning them securely using highly flexible, services-based data layers, as in the clinical aggregation layer example.

Extending Cloud Thinking in CommercialThe market for SaaS is far more mature in commercial parts of the Life Sciences Organization, evidenced by the number of providers offering CRM and sales-force automation tools. Analytics remains on-premise due to the volume of data that still resides inside the organization and in on-premise systems, but vendors are likely to begin offering analytics-as-a-service that will take advantage of commercial data available on the cloud (i.e., salesforce data). One key barrier so far in making this a reality has been the lack of “pay-as-you-go” licensing model from application providers. This has meant that data now moves from the cloud to an internal data warehouse to run the analytics, and then back to the cloud for dissemination of the results to the sales organization. Accenture expects this to change as the services and licensing capabilities mature. We also expect that companies will continue to look for opportunities to reduce the complexity of their application portfolios, transitioning functions to make use of PaaS offerings, such as Salesforce’s force.com tool, Google App Engine, and such capabilities in Microsoft Azure, as identified in our Technology Vision 2012.23

Cloud computing has gone from an intriguing idea to a core capability.

Extending Cloud Thinking in Supply Chain and EnterpriseThe ability to collaborate with customers, suppliers and distributors throughout the supply chain makes a compelling reason to take a “cloud first” approach. While most Life Sciences Companies view the on-premise ERP systems that manage their supply chains as mission critical, there is evidence that this perspective is changing and large enterprises are starting to rely on public cloud options for some business units or geographies. Wireless Semiconductor manufacturer Qualcomm, for example, rolled out a public cloud ERP (NetSuite) to certain subsidiaries while maintaining its traditional ERP System (Oracle) at the corporate level.24 Workday is also rapidly gaining acceptance as a cloud-based HR

solution that is rapidly implemented and meets business need.

As cloud offerings mature, and enterprises build up success stories they will be confident of using public cloud alternatives. Few CIOs will be able to match the economies of scale that public cloud providers deliver—which is another reason why Life Sciences Companies must prepare for a hybrid world.

Where to startFor the foreseeable future traditional systems will continue to play a role in the overall IT landscape. Cloud and traditional IT will coexist. Today the biggest challenge in cloud deployments is the integration required to weave new operating models

and systems into the existing IT fabric. As business and IT work together on what needs to be on-premise versus what can be run virtually, functional business owners and IT will come together to make the optimum use of the transformation opportunities afforded by new cloud solutions. The architecture (data, integration, monitoring, security) across the tapestry will be very different as will its governance operation and its supplier and vendor management. The most valuable talent will be the architect who understands both the business functions and the roles played by the different systems and how they work together. Life Sciences companies will need to train employees with cloud skills in technology and operations.

Case Study: Cloud-Based Platform for Clinical Trial Data Consolidation and Reporting

Pfizer has changed its operating model to work collaboratively with alliance partners Parexel and ICON to execute clinical studies. A service running on the Oracle Life Sciences Hub platform aggregates critical clinical trial information held by the CROs, while the company focuses on timely analysis of data, monitoring progress and managing relationships with regulators. This innovative technology platform, built using the cloud, allows Pfizer to securely exchange data with its alliance partners. Its business users can also aggregate, analyze and visualize clinical trial patient data across studies and drug programs. This supports intelligent trial design, precision medicine, pharmacovigilance and regulatory inquiries. In addition, business users benefit from rapid and easy access to high-quality, relevant and analysis-ready clinical data. They get an aggregated view, or “single version of the truth,” across internal and external data that conforms to Clinical Data Interchange Standards Consortium (CDISC) standards. The result is a high-performance, validated environment capable of analysis and data visualization. Additionally, users realize better informed clinical development and risk-management planning and decisions.

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Software Defined Networking: Virtualization’s last mile

Software Defined Networking (SDN) will become an essential enabler for the digital business. The technology decouples the network functions from the intricacies of the underlying hardware and is the final piece of the virtualization story. Just as with the virtualization of hardware before it, the virtualization of the network promises to make IT far more cost-effective, agile and dynamic, enabling collaboration across different stakeholders, enabling expansion through mergers & acquisitions and globalization, and improving regulatory compliance throughout the enterprise.

Enabling CollaborationLife Sciences companies collaborate across multiple stakeholders, including researchers, CROs, payers, hospitals, health care providers and pharmacies. SDN can make this collaboration more seamless because it allows networks to be readily provisioned and secured to enable sharing of data, voice and video.

SDN can also be used to virtually stitch together cloud providers, by allowing the creation of virtual networks that span diverse physical clouds and datacenters to achieve interoperability among different environments (see sidebar for example of how Google is innovating with SDN).

Aiding M&A and Globalization Analysts expect that loss of product exclusivity and health care reform in the U.S. will force another round of industry consolidation. In the past, companies’ ability to take advantage of acquisitions and mergers has been slowed down because of the difficulties in integrating IT infrastructure and providing intercompany access. Generally, companies have had to

integrate system by system and application by application in order to avoid data loss and processing errors. With SDN, this integration process can be both rapid and ensure high levels of accuracy. SDN simplifies network interoperability, and with this crucial step, companies can focus on integrating processes rather than technology.

In addition, as companies expand into emerging markets, SDN provides the infrastructure flexibility to bring remote offices up quickly and ensure globally consistent information security without having to hire more networking staff to maintain the integrity of interconnections. Further, SDN can be leveraged to rapidly deploy cutting-edge active defense strategies (see the section on Active Defense) that protect data networks.

Improving Regulatory Compliance Life Sciences data is frequently highly sensitive, whether it relates to patient information or results of clinical trials. Life Sciences companies must contend with strict guidelines from regulatory bodies such as the FDA and EMA relating to the storage and usage of data. Regulatory compliance requires some of these applications and data to reside in isolated environments. This can be difficult to implement in highly virtualized, dynamic datacenters, but SDN makes it easier to accommodate these needs. With SDN, companies can maintain virtually isolated networks for each application and dynamically adjust them to accommodate movement and scaling of application resources. The centralized management capability of SDN provides an integrated view and enables policy-based audit of isolation across all applications and infrastructure.

Evolving SDN MarketSDN is a new technology, but one which is rapidly evolving as the technology gains momentum and acceptance. IDC analysts estimate that SDN-related revenues will reach $3.7 billion by 2016 from $360 million in 2013.25 Established networking vendors such as Cisco Systems, Hewlett-Packard, Juniper Networks and Extreme Networks offer SDN products, while a host of startups are also bringing their solutions to market. Some vendors with little presence in the data center segment have acquired smaller vendors to augment their SDN capabilities; VMware acquired startup Nicira26 for a whopping $1.26 billion.

SDN is well on its way to becoming a key contributor to the agility that is critical for the digital business. Therefore, it is important that companies start to plan how to take advantage of it. Fortunately, this does not require a complete overhaul of the existing infrastructure; SDN can be implemented selectively and gradually, starting in places where it adds the most value and return on investment. Life Sciences companies should start with small pilot projects evaluate, iterate, and scale as appropriate.

SDN is well on its way to becoming a key contributor to the agility that is critical for the digital business.

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Software Defined Networking Primer

In a traditional networked environment, hardware such as switches and routers need to be configured to define logic for routine functions such as the prioritization of incoming data packets. The configurations are hard-coded, reducing the flexibility of the network. SDN separates the physical architecture from these functions. In this respect, it is very similar to the cloud, which focuses on the application or services rather than the underlying infrastructure. Just like the cloud, this abstraction is achieved through layers: the data layer talks to the physical equipment, the control layer optimizes the network operations, and the application layer provides business functions such as security, monitoring and load management.

While there are few large-scale implementations today, several technology companies have implemented proofs of concept. Google has used OpenFlow, an open-source SDN protocol, to power its data center network utilization rates reportedly to well over 95%, a number that is unheard of in the industry.

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Active Defense: Adapting cyber defenses to the threat

As Life Sciences companies evolve and become digital businesses, the importance of protecting intellectual property and maintaining control of critical regulated components becomes increasingly important. At the same time, potential attack surfaces continue to expand as more devices are deployed, flexible “bring your own device“ policies are introduced and more applications and processing moves to the cloud. Expanding developing markets also provides more avenues for attackers to infiltrate.

The Life Sciences industry is a prime target for cyber-attack because of the potential revenue involved with cutting-edge treatments. Symantec’s Internet Security Threat Report for 2013 identifies that health-care-related companies and organizations account for the largest (36%) of data breaches reported27 and a separate report indicates IP theft alone within the UK pharmaceutical, biotech and health care sectors cost companies £1.8bn28 in 2012. More recently, the FDA issued a call to all medical device manufacturers to review their cyber security practices to address the potential of networked and connected devices disseminating malware.29 The motivations of attackers are varied and increasingly sophisticated, ranging from cyber blackmailers and state-sponsored groups, looking to harvest proprietary information about products and research, to hacktivists seeking to damage reputations. Once inside the firewall, no matter how they got there, attackers could access proprietary data or regulated information, or infiltrate sensitive infrastructure such as manufacturing control systems.

Life Sciences companies have made significant investments in security controls to protect sensitive data and provide customer privacy. They establish safeguards to protect perimeters, manage risk, and meet compliance requirements set out by auditors and regulators. But our discussions with Chief Information Security Officers (CISOs) suggest the current practices are not enough. Companies must change their approach by acknowledging that attackers may get through and then deploy tools, techniques and capabilities to rapidly identify and respond quicker and more efficiently to limit the impact. Digital businesses are making a shift in thinking, moving from perimeter controls to active defense. We define active defense as having two focus areas - moving from monitoring to understanding and moving from static controls to adaptive response.

Moving from monitoring to understandingMost security operations teams excel at identifying login failures, policy violations, or attempts to circumvent a perimeter defense, and responding to identified incidents. However, assessing threats which are not in plain sight requires a more profound understanding of security lapses and their potential ramifications. This understanding comes from security analytics that combine different types of data (e.g. geo-location, email, voice, web traffic, user behavior) to develop statistics, probability models and use threat intelligence feeds to spot abnormal activity, whether caused by individuals or malware, around sensitive assets.

Such analytics can alert security technicians to potential compromise, such as peculiar patterns of login failures or consecutive log-in attempts from multiple

servers, a likely sign of infiltration. These techniques rely on highly tailored statistical inference models that can, for example, indicate inappropriate transfer of R&D documents from infected servers. Security analytics processes and technologies allow security operations to gather threat intelligence, spot unusual behavior, and warn of anomalous activity, preferably while it’s underway so that it can be stopped and investigated.

Moving from static controls to adaptive responseSecurity developers are assiduously working on technology designed to make it more difficult, more expensive and less profitable for hackers to infiltrate. These new tactics apply the latest technologies, such as virtualization and software defined networking. Examples of Active Defense include use of decoy documents that provides false information or which inject “beacons” back into the hacker’s network to provide reconnaissance for detection and investigation. Sandboxing compartmentalizes risk by containing highly targeted applications (such as browsers, PDF, zip files and executables) in a virtualized environment designed to contain malware. Another approach, called Moving Target Defenses (MTDs), randomizes connections to virtualized systems in a non-stop version of musical chairs to make it more difficult to locate specific assets.

An example of Active Defense is the U.S Defense Advanced Research Projects Agency’s (DARPA) active authentication program. This program is investigating approaches to continuous authentication, using behavioral traits to establish a cognitive fingerprint, such as the way a mouse is used or the way words are crafted, to authenticate identity and behavior.

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This allows monitoring of a user’s search and file-access behavior, and identifying deviations from normal behavior, including extensive and widespread searches for information. Usage that deviates from expected behaviors or actions may indicate that a user’s computer is under the control of malware or has been a victim of credential theft. These types of anomalous activity on a laptop could trigger the deployment of a range of adaptive responses, including the deployment of decoy files or isolation of the suspected device in a confined and highly monitored network space. These examples of dynamic response tempt the attacker into a trap which can be used to gather intelligence on the source of the attack, techniques and broader intentions. Besides the extension

to mobile devices, this behavioral biometric modality can also be extended to cloud systems where sensitive data may be stored.

The Way ForwardActive Defense makes it more difficult and expensive for adversaries to infiltrate, yet there is no magic technology that can address all security challenges. Cloud computing and mobile technologies provide Life Sciences companies the opportunity to rethink their operations for a smarter and more-global operating model. Success requires aligning security strategy with business strategy through consultation between IT and business leadership as it will require changes to business process

and operating models. The security strategy should address malicious as well as unintentional misuse. Companies should run pilot tests of security analytics for high risk areas, to ensure that the organization has the appropriate skills and diagnostics.

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Conclusion

Life Sciences companies are in the throes of change. They’re buffeted by market pressures on one side and regulatory demands on another. Accenture believes that business leaders must now set out strategic initiatives to drive change within their organizations and to reimagine themselves in the context of a digitally enabled world. In every company, IT will have to become a strategic competency woven through the enterprise—in particular, it will need to ensure the company can absorb technological advancements so that it can continue to grow, innovate, and derive insights from an increasingly quantified world.

One of the first actions required to become a digital business: retool IT to understand the business pressures and opportunities—and educate business professionals to understand the implications and possibilities of technology. Whether it relates to analytics, managing customer relationships, or protecting intellectual property, each group has much to learn from the other. Companies must design and implement cross-functional ways of working so that the retooling efforts stick and the silos of both data and thinking don’t recur.

Another key action: infuse the organization with a culture that is driven by insight. This calls for new ways of thinking about and acting on data. A digital business by definition creates, collects and curates data. Both business and IT professionals must develop their instincts and intuition regarding how to mine data, establishing standards, making the data and analytics tools available and formulating the right questions.

Organizations must then prepare for a state of constant evolution. This is where IT can step up to make the whole enterprise as agile as it can be, leveraging on-demand services such as the cloud, new patient and physician experience models, and data platforms. They must take a portfolio approach to technology so that many small experiments are constantly in play and those that prove to be winners can scale up fast.

And then there are the issues of skills, capabilities, and incentives—no small matters. These measures will involve a wholesale reframing of IT’s purpose, from cost center to business driver. And they will extend deep into the development of human capital, identifying and helping to implement new criteria for hiring, retaining, and developing data-savvy business professionals as well as IT staff with very different skill sets and aptitudes from their predecessors.

Companies must also devise specific measures to enable and motivate both employees, teaming partners, and even what may be traditional adversaries. That means rewards for collaboration, for innovation and change, not to mention increased tolerance for both experimentation and failure.

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Endnotes

1. Beyond the Patent Cliff: Signs of Recovery in Biopharma’s New Normal, Accenture Research Note: Biopharmaceutical High Performance Business Study, 2012 Update

2. http://blogs.wsj.com/cio/2013/05/01/glaxo-mined-online-parent-discussion-boards-for-vaccine-worries/

3. http://www.ucb.com/patients/programmes

4. http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Life-in-the-Normal-The-Customer-Engagement-Revolution.pdf

5. http://www.knowledgedirectweb.com/gamification-cme-medical-simulations/

6. Perrone, M. “Incyte pill is first FDA-approved drug for rare bone marrow disease”, The Associated Press, November 16, 2011

7. http://ideas.time.com/2013/03/14/10-big-ideas/slide/wear-your-doctor/

8. http://www.thetimes.co.uk/tto/health/news/article3728408.ece

9. http://proteusdigitalhealth.com/future/

10. http://homeinsteadsonoma.com/2011/08/introducing-glowcap/

11. http://www.fiercemobilehealthcare.com/story/fda-approves-first-remote-monitoring-drug-trial/2013-01-01#ixzz2HHl9mWK4

12. http://www.economist.com/news/britain/21567980-how-scrutiny-freely-available-data-might-save-nhs-money-beggar-thy-neighbour/print

13. Accenture Builds Digital Social Platform for Unilever Global Marketing in 12 Weeks - http://newsroom.accenture.com/news/accenture-builds-digi-tal-social-platform-for-unilever-global-marketing-in-12-weeks.htm

14. http://transceleratebiopharmainc.com/

15. Pfizer moves supply chain to cloud - http://www.ft.com/cms/s/0/1608e5d6-fc59-11e1-ac0f-00144feabdc0.html#axzz2SDGdfzoO

16. Predictions 2013: New Models Take Hold and Opportunities Emerge in the Global Services Market. By Rebecca Segal, Cushing Anderson, Rob Broth-ers, Chad Huston, Gard Little, Melissa O’Brien, Melanie Posey, Lisa Rowan, David Tapper, Ali Zaidi, Peter Marston, Mukesh Dialani

17. http://dodcio.defense.gov/Portals/0/Documents/ITMod/CIO%2010%20Point%20Plan%20for%20IT%20Modernization.pdf

18. http://dodcio.defense.gov/Portals/0/Documents/DoD%20Cloud%20Computing%20Strategy%20Final%20with%20Memo%20-%20July%205%202012.pdf

19. http://research.microsoft.com/pubs/140453/mtags.pdf

20. http://www.biomedcentral.com/1471-2105/13/315

21. http://aws.amazon.com/lifesciences/

22. http://aws.amazon.com/publicdatasets/

23. http://www.accenture.com/SiteCollectionDocuments/PDF/Technology/Accenture-Technology-Vision-2012.pdf

24. “NetSuite steps up large enterprise push: Lands Qualcomm, Groupon, partners with Accenture” ZDNet, May 9,2011 http://www.zdnet.com/blog/btl/netsuite-steps-up-large-enterprise-push-lands-qualcomm-groupon-partners-with-accenture/48496

25. http://www.idc.com/getdoc.jsp?containerId=prUS23888012

26. http://www.vmware.com/in/company/news/releases/vmw-nicira-07-23-12.html

27. http://www.symantec.com/content/en/us/enterprise/other_resources/b-istr_main_report_v18_2012_21291018.en-us.pdf

28. http://www.pharmaceutical-technology.com/features/featurecybercrime-pharmaceutical-industry-biotech

29. http://spectrum.ieee.org/riskfactor/telecom/security/this-week-in-cybercrime-fda-urges-tighter-cybersecurity-for-medical-devices

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This document makes descriptive reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by Accenture and is not intended to represent or imply the existence of an association between Accenture and the lawful owners of such trademarks.

Accenture, its logo, and High Performance Delivered are trademarks of Accenture.

For More Informationwww.accenture.com/technologyvision

Authors

Anne O’RiordanGlobal Life Sciences Industry Managing Director+85 2 2249 2643anne.oriordan@accenture.com

Sunil RaoGlobal Life Sciences Technology Managing Director +91 80 4106 1073sunil.rao@accenture.com

Raj BhasinGlobal Life Sciences Technology Strategy & Architecture +44 207 844 4637rajesh.bhasin@accenture.com

Paul DaughertyChief Technology Officer+1 917 452 8279paul.r.daugherty@accenture.com

ContributorsSendil Kumar Life Sciences Analytics

Jeff Elton Life Sciences Consulting

Doug Mowen Life Sciences Medical Devices

David Logue Life Sciences Commercial

Mark Hammond Life Sciences R&D

Alan Foreman Life Sciences Technology

Raj Wickramasinghe Life Sciences SaaS

Kevin Richards Technology Consulting Security

Jonathan Burr Life Sciences R&D

John Morgan Life Sciences Supply Chain

Stefano Bergantino Life Sciences Supply Chain

About AccentureAccenture is a global management consulting, technology services and outsourcing company, with approximately 266,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world’s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. The company generated net revenues of US$27.9 billion for the fiscal year ended Aug. 31, 2012. Its home page is www.accenture.com.

About Accenture Life Sciences

Accenture’s Life Sciences group is dedicated to helping companies rethink, reshape or restructure their businesses to deliver better patient outcomes and drive shareholder returns. We provide end-to-end business services as well as individual consulting, outsourcing and technology projects around the globe in all strategic and functional areas-with a strong focus on R&D, Sales & Marketing, and the Supply Chain. We have decades of experiences working hand-in-hand with the world’s most successful companies to improve their performance across the entire Life Sciences value chain. Accenture’s Life Sciences group connects more than 10,000 skilled professionals in over 50 countries who are personally committed to helping their clients achieve their business objectives and deliver better health outcomes for people around the world.

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