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Biopharmaceutical Commercial Models of the (Very Near) Future: Implications for People, Data and Organizational Change

Article
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In the Near Future…

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Things had to change. A commercial model built to deliver blockbuster drugs to the market was no longer effective for delivering therapies for complex disease states to smaller, more targeted patient populations and specialty providers. Patients became more empowered and discerning while physicians and other critical decision and policy makers became harder to reach. Customers integrated into larger organizations and consolidated their buying power at state, regional and/or country levels, with new value-based decision-making criteria and new decision-makers. The very definition of value evolved to encompass not only clinical attributes but also real-world outcomes and population health benefits as payers became more demanding. Conditional approval and reimbursement subject to re-reviews became the norm for many global products. Clinical development and commercialization timelines accelerated. Declining margins drove the need for more efficiency with promotional spend. Rather than receiving information provided by companies, key decision-makers now searched for the information they needed in the format and structure they wanted it. The universe of key stakeholders grew more diverse, and precious time could not be wasted before a company understood their needs and those of their patient populations, and how to meet their expectations.

And so biopharmaceutical commercialization models had to change. Being patient- or customercentric also meant being “consumer-centric,” like Amazon and Netflix, by delivering a wider range of services and support in ways people had become used to in other “consuming” areas of their lives. Consolidation and integration on the consumer side required integration on the company side, including the dissolution of brand silos and functional niches. Data and insights began to flow more freely between clinical and commercial teams, and companies became more nimble acting on them. Commercial strategy was better informed by clinical trial learnings, and market access and adoption insights were brought forward earlier in clinical development to inform evidence generation strategy. Digital transformation was embraced and predictive analytics illuminated customer drivers, barriers and Next Best Actions (think: the recommendations Amazon makes after you order something) with greater precision, enabling advanced engagement through coordinated action.

That’s the future we all see. The challenge now? Getting there, sooner rather than later.

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In response to these waves of change, no two companies’ commercialization models will evolve in exactly the same way, although a well-integrated model will consider key trends, specific influencers and their needs (Fig. 1). Furthermore, within diversified companies, different commercialization models must be adopted to address the specific needs of each disease state. What new commercial models of the future will have in common, however, are the new ways that people will start to behave and operate within more integrated organizations, and how data will be generated and utilized to generate actionable insights and demonstrate value. And every company will need to candidly assess its strengths and weaknesses, as well as company culture and mission, as it embarks on the always daunting process of learning and organizational change.

The Human Factor: People Power in New Commercial Models

With less dependence on face-to-face physician/sales rep interactions, the evolution to new commercial models will require individuals to think holistically about the relationship with the physician, take on new roles and responsibilities and hone new skills—including the use of new analytical and reporting tools to maximize the effectiveness of each interaction.

New Roles and Responsibilities

The “orchestrator rep.” In commercial models of the future there are fewer traditional sales reps, and the next generation of reps are not out in the field selling on their own but function more like the hub of a wheel. This “orchestrator rep” collaborates with and is supported by other roles on the customer-facing team and they are skilled at pinpointing customer needs and identifying the resources available to meet them. They are adept at selecting from an array of new team members, solutions and digital channels. They know when to push and when to pull to provide “just in time” services, when and where and how the customer needs and prefers them. They are also skilled at engaging customers the way they want to be engaged. They know whether HCPs prefer face-to-face or peer-to-peer interactions, for example, and what their preferences for digital/remote engagement are (e.g., email programs, self-guided portals, etc.).

Focused on key accounts. Increasing provider consolidation, complexity of administering new therapies and the increased burden of government reporting requirements mandate a steppedup focus on key accounts and organized customers. Depending on the local market, these could be large employers, ACOs, IDNs, HCP groups or combinations of these in the U.S., or country, regional, commissioning group or hospital-level teams in other countries. Importantly, all of these organizations operate within distinct, increasingly complex regional and local markets, requiring customer-facing teams to be skilled at local market analysis and strategy, able to identify and understand the key decision-makers and influencers throughout the local ecosystem.

In addition, organized customers are interested in tailoring interventions to their particular patient populations, again emphasizing the need for field teams to understand local market conditions and how to resource each market accordingly. Evidence needs can vary widely. Consequently, field teams need to:

  • Develop a deeper understanding of a drug’s population health benefits, particularly when it comes to chronic conditions like cardiovascular disease, diabetes and respiratory illnesses; 
  • Have greater fluency with health economics data as a key factor in the value equation; and
  • Think of themselves as “full-service” providers, able to package therapeutic area, above-thebrand and product-specific programs and services tailored to an organized customer’s needs (e.g., disease management and decision-making tools for HCPs, self-management and adherence support for patients, coordination of care programs, reimbursement support, joint research efforts, etc.)—all with the goal of improving outcomes. 

From generalist to expert. Customer-facing teams in new commercial models are trained and structured to provide more in-depth knowledge about complex disease states and therapies, and to engage in higher-level information exchange and two-way dialogue with both HCPs and senior customers in larger organizations. But this new level of interaction must, as always, be fine-tuned to avoid crossing boundaries into the territory reserved for medical affairs and scientific exchange. Teams become less focused on selling outright and more on becoming clinical and therapeutic area experts and service providers. Customer relationships become less focused on pushing key messages and less transactional, while becoming more focused on building needs-based partnerships and co-creating with customers.

“One team” players. Even as field team roles and responsibilities evolve, it is important to simplify team structures, with clear mapping to key stakeholders from top to bottom and throughout the customer organization. However, a cautionary note: Companies need be careful not to erect further barriers to collaboration by creating additional roles that end up reinforcing silos. Successful companies are moving to a “one team” approach for accounts and offices, led by an account manager who is able to call on the customer at a high level, is familiar with all the processes, procedures and unique needs of the client, and able to coordinate a well-integrated customer engagement strategy. This more integrated approach also means establishing a more effective balance between portfolio and brand promotion, with a better mix of promotional and therapeutic area or indication-focused roles. And it requires more cross-functional planning to generate the insights that enable customized engagement and partnerships.

The Data Imperative: Connecting the Dots in New Commercial Models

Successful evolution in what people do and how they behave in new commercial models depends to a very large extent on fundamental shifts in how data is generated and utilized by commercial teams to mine for actionable insights, shape strategy and facilitate rapid response to change in the marketplace.

For account teams to identify the trends in offices and institutions that signal unique customer opportunities, and become more relationship-driven and problem-solving in their approach to forming strategic partnerships, they will need to blend their clinical backgrounds with analytical capabilities. They will need to become, in short, more savvy in the “business of medicine,” developing new skills in:

  • Business analytics and insight generation
  • Customer-need diagnostics and engagement
  • Business planning and coordination
  • Leading without authority

Training will need to include optimal segmentation techniques and better understanding of the branded and unbranded organizational tools, messages and programs that can be designed for—and even with—customers in areas such as data utilization, outcomes research, patient engagement, adherence, coordination of care, reimbursement and decision support. The shift from one-directional pushing of key messages toward more needs-based, strategic partnering can be facilitated by creating tool kits that provide partnership and co-creation opportunities, supported by case studies to help sales teams better understand customers’ needs and relationship-building strategies.

R&D has already begun using big data, artificial intelligence and predictive analytics to change the way drugs are being developed—using them to sift through vast amounts of genetic, metabolic and clinical information to identify patterns and biological underpinnings of disease, and to identify medications likely to work in specific patient populations, while quickly steering companies away from drugs likely to fail.

Accomplishing a similar digital transformation on the commercial side is taking more time, during which numerous tech companies are rapidly ramping up their efforts to collect, organize and access healthcare data in new ways. There are many examples of digital tools being used outside of biopharmaceutical companies to transform our approach to healthcare. Some are figuring out how to derive meaning and insight from the raw sensor data captured on smartphones, which when combined with health-related claims data, is giving us a preview into how health outcomes can be steadily advanced through the combination of digital insights plus effective interventions. Improvements in natural language processing (NLP) are helping to tackle the challenges of managing vast amounts of paper-based data. The companies advancing these innovations are rapidly outpacing pharmaceutical companies in their ability to capture deep insights into the therapies and protocols that can best manage chronic diseases such as diabetes, hypertension, hyperlipidemia and other costly conditions. Pharmaceutical companies could and should be doing more to increase value by using the big data at their disposal to design accessible user experiences and help HCPs and patients make better treatment and disease management decisions.

However, the reality is that, just like people in many biopharmaceutical companies, “big data” still largely exists in discrete, disconnected packages and functional silos across the clinicalcommercial spectrum and external to the company. Data that “lives” this way can never tell the whole story. New organization structures and technology enhancements are needed that are capable of harmonizing all this data, deriving business-relevant insights from it and acting on it in real time. Furthermore, data generated and owned by the company needs to be seamlessly harmonized with external data sources, both public and proprietary.

For commercial teams, this means improving the flow and integration of data from throughout the organization (Fig. 2) to support agility in:

  • “Always on” analytics, including machine learning and workflow integration, to generate real-time customer profiles and information differential resourcing;
  • Precision targeting, to dynamically allocate resources across customers and channels based on insights;
  • Customer journeys, to more consistently integrate drivers, barriers, needs and pain points into strategic solutions;
  • Advanced engagement, to more rapidly incorporate lessons learned to enhance multichannel engagement and content, tailor to customer needs and preferences, and integrate customer-facing roles accordingly; and
  • Integrated deployment, to adopt measurement results and provide stakeholders with “Next Best Actions.”

Some pharmaceutical companies are starting to experiment with various frameworks to support these new modes of behavior, skill sets and data flow, but none have fully succeeded just yet. In particular, leveraging clinical experience to improve the chances of launch success remains an opportunity for most biopharmaceutical companies. Crucial insights into prescriber behavior, payer needs, competitive dynamics and patient profiles often remain with clinical teams, failing to be integrated into downstream adoption planning. Potential data and opportunities to integrate clinical data into launch planning include:

  • Frequency, consistency and quality of enrollment, and other development-derived evidence (e.g., patient, key opinion leader and site/investigator insights);
  • Patient and provider targeting lists from trial data (where permissible by local regulation, e.g., General Data Protection Regulation);
  • Key brand distribution, dispensing and support service needs from trial experience;
  • Real-world data/evidence analysis on economic story can be integrated into launch plan to optimize payer access and adoption; and
  • Availability of reporting/collection and impact assessment of patient-reported outcomes can be brought into customer engagement strategies at launch.

Organizational Change: Getting from Here to There

The new commercial model of the (near) future is different in so many ways from what commercial teams have been used to that change on this scale can seem like an overwhelming proposition. More challenging still, it requires remodeling the current organization while still “living” in it and running the business. How do you get from the current status quo to “options creating” commercial potential? And how do you prepare for challenges along the way?

Change of this magnitude usually doesn’t happen by decree. It can help to approach it as an iterative process that can take place as a series of opportunistic builds rather than large-scale, all-at-once transformation (Fig. 3). To start:

Develop your vision. Change begins with envisioning where you want to be in five years and, importantly, knowing what foundation needs to be laid over the next two years to get there:

  • What “crawl, walk, run” progression of capabilities needs to be nurtured to maturity?
  • Identify current best practices that can be extended and gaps that need to be filled.
  • Identify the information and insights needed and how to generate them or find them within the larger organization. What tools for doing this can you give customer-facing roles?
The goal is to increase growth for the portfolio while also increasing resource efficiency by increasing digital and remote engagement

Engage the organization. In the exact same way that customers will be far more engaged when involved in co-creation, staff will also be far more driven to change if they understand the problem in question and generate the answers. Specific interventions involve:

  • Utilizing face-to-face workshops to align on the problem, gather feedback, understand the complexity of problems, identify pockets of excellence and co-create organizational solutions;
  • Identifying change agents and giving them the appropriate support and focus that they need to deliver change; and
  • Identifying and rewarding behavior that tangibly supports the change to becoming a customer-centric organization.

Test and learn. Consider starting incrementally—opportunistically—by identifying “test and learn” opportunities for pilot projects with key accounts and/or other stakeholders, e.g.:

  • Assess critical engagement needs of patients and providers, and identify brand and indication-level opportunities for education, lifestyle, digital and/or advocacy.
  • Create and execute cross-functional action plans for local market pilots with key customers (e.g., organized customers) or other stakeholders (e.g., academic centers, hospitals) involving sales, marketing, market access and/or medical affairs.
  • Experiment with new roles (e.g., scientific advisers, patient navigators, etc.), tools and solutions.

Be introspective. Consider your strengths and weaknesses and what collaborations or partnerships would help to augment or replace certain capabilities to support more connectivity. Ask, what are you really good at? And be introspective about your core competencies and where you can play. Having a large sales force has always been a measure of success, a badge of honor. But what if you could turn it from a fixed to flexible cost, customized for each launch and target customer?

Concluding Thoughts

When using the term “new commercial model,” the image that most readily comes to mind is some kind of new organizational structure. What does the organizational chart look like? And restructuring is definitely called for as biopharmaceutical companies must adapt to powerful new trends, influencer segments and unmet needs in the marketplace. But it is equally if not more important to consider how people within those organizations will need to adapt, and what new behaviors and skill sets will need to be cultivated. It’s also critical to think in terms of how data “behaves” in these new organizations—where can it come from, how will it be obtained and analyzed, and how will it flow, be shared and made actionable. To make organizational change on this scale feasible, it is helpful to consider ways these capabilities can be nurtured in pilot projects (both large and small) and brought to maturity over time, with continuous learning aided by enhanced insight generation and data analytics.

 

Check out The Syneos Health Podcast on this topic here.

Authors

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Howard Brock

Managing Director

Syneos Health Consulting

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Jackson Carroll

Senior Engagement Manager

Syneos Health Consulting

About Syneos Health Consulting

Syneos Health Consulting is an industry-leading consulting firm specializing in the biopharmaceutical industry and part of Syneos Health, the only fully integrated biopharmaceutical solutions organization. We provide services across a comprehensive range of key areas, including commercial strategy and planning, medical affairs, risk and program management and pricing and market access. Recognized by Forbes magazine as one of America’s Best Management Consulting Firms for three years running, our industry focus and depth of functional expertise, combined with strong scientific and market knowledge, uniquely position us to tackle highly complex business and market challenges to develop actionable strategies for our clients. For more information, please visit syneoshealth.com/solutions/consulting.

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