Indegene Digital Summit 2020

When Aseem joined Unilever, his challenge was to build brands globally, with limited resources and a very small team. How would he understand consumers, identify what brands to launch, and support launches in different countries, with a team of 2 or 3 people?

His solution was a digital-first model. This approach has enabled the fast rollout of many brands in numerous markets, using a lean, agile team. Technology has been used to scale fast, learn quickly, understand consumers, test, and launch successfully.
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Aseem says when deciding what product to launch, the first step is social listening, using cheap or free engines. This provides data on brands and trends by category. Next, brand concepts are developed and A/B tested on social media. Online research panels are used for validation.

His team works with an agency that buys global media for them on all digital platforms. Media are used in a targeted way to influence customers, drive traffic toward eCommerce or conversion, to a direct-to-consumer website or, in the case of B2B, for lead generation. Puri asserts, “We are a 100% digital model. We don’t spend money on anything else. It is already the best ROI, and the most effective.”

“Forget the technology and platforms – it is all in the experimentation, the culture of experimenting. Testing and learning are the key. Turn it into a hypothesis and test it. Data will give you the answer,” he continues.

Aseem says traditional agencies craft Picassos, but digital consumers want Dilbert; they demand new content every 15 minutes. Digitally native consumers don’t expect perfection; they want quality content, education, or entertainment. This necessitates a content production engine that can produce a large volume at a reasonably low cost, which can be adapted based on testing.

Brands need a purpose that goes beyond selling products and serves customers’ needs. Patterns of online behavior can be uncovered by asking people what they do online. These insights inform the content strategy and decisions about what type of content to develop.

Aseem’s top priorities are brand awareness and penetration. He is less concerned about national market share and more interested in segment share. He states, “Marketing equals maths. It is less about brilliant creative, more about precision and targeting and focus.”
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Abhay Gandhi recommends learning from what innovations work, and do not work, in other industries over the longer term as things normalize. Digital is not an end in itself, but a delivery system to enable what is necessary for the business. Look at digital developments in the education sector, for example. Could pharma adapt what they are doing and adopt global digital training platforms?

In the wearables space, Subhasis Banerji has leveraged data and seen the extent to which chronic patients can drive their own recovery, outside supervised therapy sessions. That knowledge has helped during the pandemic, as 70% of sessions with the wearables are now being conducted unsupervised.
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Another insight gleaned in this period is that patients adapt and adopt new methods when left with no other choices. This means that the company can continue to demonstrate outcomes with almost no physical touchpoints between therapists and patients. Optimization planning around outcomes is being done internally but, for everything else, they are looking to outsource the processes and development to digital partners.

The purchase of 2 digital companies has accelerated Reginald Seeto’s transplant business by reinforcing an absolute focus on capturing data on the patient journey. “Moving to digital enabled us to put together the largest transplant data registry in the world,” he asserts.

Going forward, consumer behavior will impact design more than ever before. Innovations will come more from a “health” than a “disease” standpoint. It is important to observe what technologies patients are already using and leverage their existing digital habits and build around them.

The next evolution in digital will be to help companies scale globally. Solutions need to be found to overcome cultural and language barriers, as well as different regulatory constraints. As CEO Reginald Seeto puts it, “Scale-building with technology has to be core and front and center. Businesses need to think how things will change in the next two years and, more importantly, five years.”
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Today, customer experience (CX) in pharma needs to go beyond the traditional definition of how customers perceive their interactions with a company and adopt a more holistic view that encompasses “value” to the customer. However, a common definition of CX needs to be established across the organization, which can be articulated by all layers of the organization. Customer engagement and CX can be seen as 2 sides of the same coin. Engagement is the proactive action taken by patients, HCPs, or payers to engage with the company, and CX is not just how they feel, but what “value” they get from those engagements.
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Until recently, CX has been measured by the performance of reps or medical science liaisons. Impact and ROI are important measures for the business, but there are new, more customer centric KPIs that can demonstrate value to the customer. They also prove to the leadership the necessity of putting CX at the center, such as customer satisfaction scores, digital experience scores, and customer return rates.

Besides changing hearts and minds across the organization, management must also provide the technology and data to ensure that all employees are attuned to patient or customer needs. There must be advocates in each function to champion innovation and work out a cohesive approach.

Regardless of industry or channels, consumers all want the same thing. They want to be understood, feel special, belong, feel in control, and reach their potential. “Generation CX” expects 24-hour connectivity and a consistently good experience across channels. This means creating and delivering an always-on, cohesive, consistent, and frictionless CX across touchpoints and channels.

Today, pharma is competing with digitally connected companies, as well as other pharma companies, and the future will only be more competitive. The plethora of data available now can be leveraged to help pharma predict what is necessary to give the customer a great experience or additional value. The industry can win by mining its data and creating engaging, 3-way conversations between the HCP, consumer, and brand. It can also leverage technology and wearables to personalize that experience.

Companies must discover the emotional outcomes that a consumer is searching for and work out how to make that experience come alive. The aim is to truly stand in the shoes of consumers and become the brand they love, not just the brand they buy.

Customer obsession means creating an adaptable customer journey that makes the individual feel that they are the most important customer to that organization at all touchpoints.
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In the new normal, digital channels have become the core channels of customer engagement, but doctors are being swamped with content, and push sales techniques are not working anymore. Pharma needs insights from customer behavior to understand what will work, and a high degree of personalization. It is necessary to consider the reaction of customers quickly, analyze the impact, and optimize the customer journey in real time, which requires a much more data-driven approach.

Also, it must be remembered that physicians are humans first and need a human marketing approach, rather than to be treated as doctors who only want scientifically vetted and compliant information. Trust in the brand is built by taking a human approach.

Using agile analytics allows leaders to make fact-based decisions faster. It comprises 3 components: first, the right data platforms to address questions with data insights in real time; second, analytic consultants who can facilitate discussions about data in real time among decision makers and enable them to make choices quickly; and third, a focused team to develop insights and facilitate actions. All stakeholders should confer regularly to agree on the actions necessary to achieve the goal.

Now is a time for experimentation. Pharma can use new data sets to gain insights into how the human HCP persona is behaving. Time-restricted experimental pods can be set up and given the freedom to use different paths to build trust through insights and performance. New ways of engaging the data, such as social listening about brands and physicians, can provide different paths to performance.

Pharma has been held back by its legacy data footprint. However, now the technology is available to integrate data sets. This enables organizations to move from a data acquisition and data reporting mentality to a data strategy and data decision frameworks. Pharma’s legacy data sets can be integrated and augmented with market research, for example, to provide answers together, enabling quicker decision-making. Now it is possible to activate a marketing mix, promotional optimization, and dynamic targeting.

The use of augmented analytics enables better connection of the dots across data, when one flow of analytics may not be providing the information needed.

Pharma faces a diversity of competition, not just from big pharma or biotech but also from technology companies. Innovation must go beyond the molecule and focus on customer experience. The industry must ask itself how it will get medicines and care to increasingly tech-savvy patients, on their own terms and in ways that are easy and engaging for them. What layers can be added on top of what the medicine does to make a difference? Can wearables or monitoring offer solutions? However, innovation should not start with a solution looking for a problem, but with finding solutions to the existing business problems.

Pharma can partner with the big tech companies to benefit from their customer-experience-first and data-heavy mentality. In return, life sciences bring deep science experience that can be merged with tech companies’ strengths to form new ways of engaging and helping patients. In addition, tech businesses can lend their voices to the discussion with regulators on advancing digital innovation and the use of data.

First and foremost, innovation should enable the corporate strategy, cross-functionally. It has to be embedded in the culture and incentives across the company. On top of this, good leadership is required, both at the strategic and process innovation level. Leveraging data not only at the strategic level but also at the process level is key to fuel innovation. Organizations should strike a balance between federating innovation across the organization while avoiding fragmentation.

When embedding digital innovation, it is critical to start the innovation journey from the customer, not from the inside. Beyond great products, people expect a great experience. The process must start with great user design and an understanding of how the customers interact with the product. Vast customer data is available, but it is hard to synthesize it into useful information without personal bias. Field observations can be valuable, and there are many tools available to gather data and map dynamic customer journeys. Tools like social listening, big data, and claims data give a longitudinal and personalized view of the customer and how they interact with medicines, their disease, their own lifestyle, and their ecosystem. These data can inform ways for pharma to innovate around their needs and make their lives better and easier. However, pharma should resist creating new “uni-tasking” tools, which are not seamlessly integrated, and create solutions that blend into their lives.

A data governance strategy may not be exciting, but the faster high-quality data can be accessed and used, the quicker innovation can be operationalized. However, data by themselves are not sufficient to develop fit-for-purpose solutions; they need to be transformed into actual knowledge and supported by embedded capabilities close to the business.

The 4 main categories where artificial intelligence (AI) is impacting pharma are Customer Experience, Document and Digital Asset Management and Life cycle, Predictive and Prescriptive Analytics, and Process Automation.

Among several areas of impact, the content supply chain is an area that can benefit a lot from AI, as it can lower compliance costs, improve the opportunity costs of time to market, help create more efficient and effective content by measuring effectiveness, as well as providing scalability of operations.
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One way for businesses to minimize risk is to use human-in-the-loop (HITL) – an approach where AI learns from human expertise and, in turn, human experts’ work can become more efficient. HITL is used in developing and training models. Curated data sets are provided by experts and fed into the machine to train it. Then, the machine makes predictions on unseen data and the experts validate its responses.

While HITL is effective for training, machine-in-the-loop (MITL) is implemented for live business applications. Here, the business process is centered around an expert or human-based workflow and the machines augment the processes.

In one example of the Machine-Assisted Call Center (MACC), HITL and MITL are combined to accelerate data entry in forms. The machine pre-populates fields and then experts validate the work. The machine learns over time in a continuous feedback loop.

Natural language processing (NLP)-based chatbots are useful to read and process large volumes of documents. Other areas where machine language (ML) and AI technologies can be leveraged are in medical record reviews to identify and verify claims, as well as in commercial content authoring, specifically for template-based emails. For regulatory submissions, an Intelligent Content Management System (ICMS) can provide suggestions for text changes, based on its learned knowledge of previous successful submissions.

A content performance prediction tool can assess how well a piece of content will engage with an audience. Another tool can read existing content and give insights that can be used for repurposing or reusing it.

When looking for ways to capitalize on unstructured data, which is a common issue, it is unlikely that there will be enough data available at the beginning of the process to create a useful database for analytics. Initially, all the materials require human review but, as the machine algorithms improve, this input can be reduced over time.
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One challenge for pharma is to meet the changing demands of the customer. Healthcare professionals (HCPs) with more traditional views have struggled to adapt to the rise of the empowered patient and participatory medicine. They need help to guide patients to the right sources of information and away from misinformation about products, clinical trials, and general health. So, the challenge for colleagues from the industry is how to use this continuous stream of data from digital tools and devices and provide actionable health information for both healthcare professionals (HCPs) and patients.
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The consumerization of health devices can be shown by the development of continuous glucose monitoring in diabetes, with sensors linked to devices that customers own already. A wearable sensor that can measure blood glucose levels in real time and send them to a phone or reader is convenient and helps people to live life normally. Patients can make decisions to adjust food intake or exercise based on the readings.

Pharma must understand what information HCPs value and how to serve it seamlessly across channels they trust. Right now, it is multi-silos rather than multichannel, but digital transformation acceleration due to Covid-19 is providing opportunities to improve both channels and personalize content coherently. The pandemic is shaping new behaviors and expectations, and the industry needs partners to help it understand how to meet these requirements.

Enterprise transformation at scale is an evolving process. Integration of business transformation and digital transformation is the key. Another option is to scale through strategic partnerships, moving from solutions to platforms and ecosystems, which introduces data, digital capability, and new business models. The lines between business and IT are blurring. Transformation is less about roles and titles and more about the jobs to be done. Teams need to be able to cross-pollinate, and businesses need to invest in digital transformation. Data is not the responsibility of technology alone; the transforming landscape of patients and HCPs means pharma will have to change mindsets and act differently.

This year, companies have faced 2 challenges: how to change their model to react to the emergency situation and how to pivot to harvest benefits from the new ecosystem it has created. Businesses must have a cycle of measurement and recalibration. Now, HCPs demand and expect new standards. The challenge is to provide both quantity and quality consistently. Pharma must listen to, and take care of, the customer. The customer is the North Star to guide the direction of travel.
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Real-world data (RWD) is defined as the information captured at the bedside or in clinical practice. Real-world evidence (RWE) is generated by applying technology and statistical methods to RWD, which provides meaningful insights for different stakeholders.

The combination of RWD and conventional or advanced analytics offers great promise for informing the production of safe and effective treatments and for accelerating the delivery of clinical trials.
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The leap from RWD to RWE requires centralization of data and analytics platforms within the organization, bridging R&D through commercial, and even corporate, functions, to look across the whole drug life cycle. Data experts must have a seat at the strategic table. The organizational structure should enable dedicated teams to focus on the conversion of RWD into RWE. Hubs in different parts of the business should be able to interrogate the centralized data to answer their specific questions.

To achieve success with this model, there must be a culture shift within the organization, too. If teams are brought along in the process to witness the healthcare benefits that can be achieved, any initial inertia can be overcome. They also have to accept that they need to take risks.

Evidence has to be generated throughout the life cycle of the product, to address needs at the different phases of the drug development process. From the outset, evidence is generated so that the team can begin assessing the cost and burden of disease. This allows predictive modeling to see where the product will stand in terms of patient access and reimbursement once it reaches the market. When it is on the market, RWE is utilized to strengthen its value proposition and demonstrate to stakeholders how the drug performs in the real world.

It is vital to build trust and confidence among stakeholders in the RWD that are being used to generate evidence. Alongside the organizational changes, data must be made accessible and usable, and this takes a lot of effort, and trial and error, to perfect. Challenges in terms of the quality and completeness of the data still remain. While pharma is building its own data repositories, it must also look to work with external sources and federated data. Technological and analytics advances are improving the situation, but there is still a long way to go.
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In March 2020, when the pandemic gripped the entire globe, pharma companies decided to be empathetic with their customers and pause all active promotion. There was a fall in patient visits and claims volumes in the early months of the pandemic, while telemedicine saw a sharp rise. Companies now need to figure out the ratio of in-patient visits versus telemedicine that will continue in the long term. Another influence is the economic impact, namely, unemployment and how long people can afford to pay for care. In addition, engagement preferences of healthcare physicians (HCPs) must be taken into account. Access, affordability, and patient support are increasingly important in the next normal, and services around them will be critical in the new business model.
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There are also questions about the ongoing role of the large field forces. The new environment has brought about a test-and-learn approach that allows for experimentation with the full marketing mix, as opposed to the traditional approach over an indexed face-to-face channel.

Simplicity is important for optimizing HCP engagement. HCPs are humans first, so the goal is to create experiences that fit in with how they live. It is critical to see how other industries create good customer experiences as pharma moves beyond face-to-face interactions with HCPs. Those who commit to an omnichannel approach and resize the field force, should not only consider promotional response analytics, market coverage, territory coverage, and other traditional inputs but also redefine the productivity of sales professionals. With the right marketing technology investments and a strong change management plan, sales professionals’ roles can be reimagined and productivity may be increased.

Once the IT and data management foundations are in place, advanced data analytics can improve the delivery of customer experience. A lot can be learned from other industries. Predictive analytics informing on the next best actions and recommendation engines, like the one used by Netflix, are very powerful tools when adopted at scale. An “always on,” real-time orchestration engine tied to a decision engine can drive a connected customer engagement in a rep-driven orchestration model or a balanced omnichannel orchestration model. The goal is to create a frictionless customer experience, and this requires a full breadth of analytics and operations support.

The cultural revolution that is needed to drive this transformation should not be underestimated. From the rep in the field to the C-suite, everyone must learn to accept recommendations made by technology. Culturally, this is very difficult, particularly for risk-averse pharma.

Pilots are also a useful tool, allowing fast learning in particular markets and quick decisions about whether to scale up. The pandemic has made people more willing to share knowledge, break down boundaries, and embrace new approaches. Collaboration and a sense of community are enabling rapid scaling.

In the new world, it is vital to have good scientific-based discussions with HCPs, and having capabilities that enable the right people to have these discussions is critical in the new commercial model. Companies need to focus on capability evolution across the business, in sales, marketing, and advanced analytics.
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Setting up the digital ecosystem starts with the recognition that each customer has a unique set of needs and aspirations. They are looking for information via their preferred channels to treat the patient at hand.

While many digital transformations have been attempted, research has shown that only 20%-30% have succeeded. There are 6 common factors that make the difference between failure and success in creating a digital ecosystem. First, it is important to have a clear strategy with a specific outcome goal.
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A compelling vision must be created that brings value and satisfaction to each customer. The strategy must be informed by a deep understanding of the customer journey. The traditional strategic approaches of segmentation and targeting may not be helpful here, as micro-segmentation and micro-targeting must be embraced. Second, there must be a commitment to change from the leadership, as the transformation journey is not easy to sustain. Every employee must be encouraged on the journey and not be afraid of failures along the way. Third, a robust technology architecture that is modular and scalable and that allows for data analytics is required, which will generate insights and predict customer behaviors.

Fourth, and the most important, is the human aspect. As one presenter explains, “We tell our customers you are about to undertake a bionic journey, not a digital journey.” In this case, bionic means the seamless flow of concepts from engineering to biology. Success only comes when technology is blended with the organization’s human capabilities. The fifth factor is to embed new ways of working. The operating model must enable cross-functional teamwork and partnership with other companies to enhance the understanding of customer needs. The sixth is a commitment to reskilling the workforce. Getting one or two of these aspects right will not move the needle; for success, companies have to align them all. This is why this road map is a big undertaking and requires leadership commitment and investment.

One area of growth since the pandemic is the expansion of online meetings from small, regular meetings in hospitals to national academic conferences. Pharma has also leveraged online platforms for new digital product launches, as HCPs’ acceptance of digital communication accelerates. The first step lies in perfecting engagement between pharma and HCPs; the next challenge is for pharma and HCPs to work together to serve patients in the digital world.
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There are 3 simple maxims to support patient-centric healthcare and ensure that businesses get by through the pandemic: What do we know? How do we feel? What do we do?

What do we know? Eight months into the pandemic, we clearly know that Covid-19 is accelerating digital transformation. Short-term business models have to be rethought, and organizations must stay nimble and flexible. Digital pharmacy is rising rapidly and distribution options like contactless, curbside pickup and home delivery are being introduced.
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How do we feel? Business people have instincts and rely on shared knowledge and experiences to help with interpretation and to gain insights from consumers to make informed decisions. Companies must stay true to their core mission and not be distracted by shiny objects that don’t offer real solutions. This unprecedented situation can be used to better define who we are and what we are going to do.

What do we do? Healthcare professionals (HCPs) seeking to improve outcomes have to be deliberate about the ideas, practices, and protocols that are put into action. Social determinants of health such as isolation, housing, and transport are driving poor health, and they need to be addressed with innovations like providing virtual social gatherings for seniors. There is no substitute for in-person engagement, but digital enables organizations to reach out to more consumers with their products and messages. If an audience trusts the brand, then it can deliver much more, albeit virtually.

To use technology effectively and ensure the right focus, it is necessary to understand customers. In order to get seniors online, they have to be engaged with relevant, meaningful content; hence, consumer research has been extended during the pandemic. Surveying them regularly ensures their needs are being met, now and in the future. Most respondents have a “wait-and-see” attitude regarding the Covid-19 vaccine, which highlights an opportunity to provide educational content.

Remote patient monitoring, telehealth, and smartphones have game-changing potential with the right design, proper implementation, and a “patient-first” approach. Digital uptake will not only help with costs but also with reach. It is a means of engagement and activation that is uniquely distinct from physical methods. Digital data can provide insights into how to make services more attractive. The value is not just in the price but in the overall experience.

The more pharmacy, preventative health-oriented organizations and drug manufacturers collaborate, the faster and broader the impact will be on healthcare, and the greater the benefits to patients.
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