January 21, 2020/Aktana/Artificial Intelligence

Clay Hausmann and Matthew Van Wingerden

As a new decade begins (or is it the last year of the 2011-2020 decade? A debate for a different day), we’re on the cusp of a full-scale transformation in life sciences. As mentioned in Gartner’s recent report, Predicts 2020: Life Science CIOs Must Digitalize for Business Growth1 (Gartner subscription required), “AI (artificial intelligence) is one of the most powerful, transformational technologies to enable new business models, customer experiences, service offerings, and business ecosystems across multiple industries.” That transformation is underway in the way life sciences companies manage their commercial operations.

Just five years ago, we were introducing the concept of “intelligent suggestions for reps.” And today, AI has expanded to every channel and task in the commercial process. But there’s still a long way to go to maximize the potential of AI and machine learning. Where will that impact come from in 2020? Here are six trends we see taking hold across life sciences.

1. Omnichannel, Once and For All

“Oh no, not omnichannel or MCM again,” you’re thinking, “the staples of every year-end trend article for the last decade.” But yes, here it is again, and for good reason. Because certain factors have emerged to make “omnichannel” successful once and for all. One, companies have learned that in order for omnichannel to be successful, it has to be rooted in the personal relationship with the customer. The actor in your organization who knows that relationship best is the sales rep. When we bring that role into upfront strategy sessions and training workshops (which we do every time), the end result is always more effective. The field channel is not exclusively an execution channel to be incorporated at the last stage. It’s a contributor throughout and should be treated as such.

Second, AI can analyze and optimize the performance of every channel, especially as they relate with one another. We fielded a survey at a recent conference where life science executives told us that “multi-channel customer journeys” was the area of greatest AI impact in supporting commercial teams. Because we have the ability now to match channel communication to HCP preferences, monitor performance, and incorporate learnings in ways we never could before, omnichannel can be a reality and not just a buzzword.

2. Empowering the Intelligent Rep

The fear of AI “replacing the rep” has shifted toward AI “empowering the rep” in recent years. A recent report from Brookings, states that “just over 37% of the tasks carried out by technical sales reps can be automated by AI-based systems.” In the article, MIT economist David Autor stresses that “what technology doesn’t replace, it complements,” which we have seen over the past few years in working with our clients. 

Although AI automates certain tasks to improve efficiency, it has been proven that most tasks require the appropriate blend of AI and human oversight. Sales roles have already begun to change by implementing increased training, modified incentive programs, and evolving job descriptions. We are rapidly moving away from the traditional POA cycle, allowing teams to have more regular touchpoints around strategy to continuously improve and tighten execution. By shifting to this combination of technology and human insights, reps have a better understanding of how their customers engage to create a more cohesive and personalized experience. As 2020 progresses, sales representatives will have a much deeper understanding of what AI can do to support them, not replace them.

3. Moving Beyond CRM

Although the CRM platform remains the foundation behind many customer engagement efforts, it leaves much to be desired as an intelligent user interface for field users. Life sciences organizations are doing a far better job at recognizing and utilizing the communication tools that match existing user behavior. WeChat in China, texting and chat functionalities in the United States, and voice capabilities globally – each one is becoming more prominent in the communications toolkit, deployment roadmap, or both for life sciences commercial teams. The need to be more agile has a direct impact on business performance and overall customer satisfaction.

4. Increased Operational Resourcing

Just 18 months ago, most life sciences companies staffed their intelligent engagement efforts with a blend of IT, sales, brand, and analytics personnel working on it as a side project. Occasionally, there would be a dedicated innovation team, but often they remained organizationally separate from the region and brand-driven decision-making process. Trends across the industry are changing, and HCPs expect a coordinated, personalized solution on their terms. 

Today, as the life sciences industry recognizes that AI’s impact on their commercial operations is here for good, companies are resourcing these initiatives much more effectively – dedicated teams, with global representation, interlinked with other more established marketing initiatives that give increased strength and speed to the roll-out. One customer has increased their intelligent engagement team from 5 to 60 employees in the last year alone with plans to grow to more than 100 in 2020.

5. Global from the Get-Go

A second byproduct of the “when, not if” momentum around commercial AI is the increasing likelihood of companies to think globally right out of the gate. Gartner recently identified Life Science Commercial Analytics as entering the Plateau of Productivity on the Hype Cycle for Life Science Commercial Operations 20192 (Gartner subscription required). According to the report, Life Science Commercial Analytics market penetration has reached 20% to 50% of its target audience. For those who haven’t adopted life science commercial analytics, we believe the time to implement AI in commercial engagement is now. Companies are no longer launching in siloes, they’re assessing new ways to think about commercial efforts, including “one that can work seamlessly together across geographies and specialties while expertly leveraging technology to deliver a great customer experience whether they happen to be sitting across the desk from a healthcare professional or across the country,” according to Syneos Health.

At Aktana, we’re seeing more companies build multi-brand, multi-region programs from the start than we did just two years ago. Success metrics are still required to escalate that expansion quickly, but the customer mindset is now to assume success will happen and pre-plan for expansion.

6. Improved Predictability

As more companies implement AI in 2020, improved predictability will be found in many different places. For example, establishing a data framework to describe the physician’s perception and adoption journey will become the standard. This advanced per indication data model will grow and evolve with the market to help predict and improve productivity, thus bringing savings back to patients and their families. With improved predictions, Marketing can also quickly gather information for campaigns and adjust to improve customer journeys. AI technologies will continue to improve sales change detection in prescribing behavior with AI-based monitoring of sales volume, market share, and purchase timing.

For example, one of our clients wanted to identify new opportunities in the US market among non-target HCPs who saw an increase in cardiovascular patient pools. With our sales change detection module, the company was able to adjust for seasonality and trends, detect unusual changes in metrics, and identify gaps in purchasing and prescribing frequency.

 After a five-year growth and evaluation period, AI in the commercial process will fully take root in 2020. From effective task targeting to global resourcing to change management, the organizational investment is fully underway. How AI is deployed, measured and optimized will determine what the near future looks like and how quickly we derive the benefits. 

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1Gartner “Predicts 2020: Life Science CIOs Must Digitalize for Business Growth,” Animesh Gandhi, et al, 23 December 2019 

2Gartner “Hype Cycle for Life Science Commercial Operations, 2019,” Michael Shanler, Animesh Gandhi, 3 August 2019