Calibrating Field Force Effectiveness: New Avenues for Healthcare

Navigating the Shift to Digital Engagements in Healthcare with AI

At the onset of the pandemic, life science organizations quickly pivoted to digital engagement. Virtual calls replaced in-person and non-personal promotion ramped up markedly. With virtual interactions expected to play a significant role beyond the pandemic, life science organizations have embraced a hybrid approach – one that synergizes in-person and digital engagements. Jeff Traenkner, Principal, TheMathCompany, explores the contexts reshaping field force effectiveness and outreach in a post-pandemic world. 

1. Amidst a rapid growth of hybrid care models in the healthcare landscape, how are Healthcare Professional (HCP) interactions set to evolve?

Increased digital traffic during the height of the pandemic quickly consumed what little bandwidth HCPs had left, leaving them feeling “spammed” by some life science organizations. Even worse, HCPs felt that much of the digital messaging missed the mark; it wasn’t relevant or insightful to them, their practice or, more importantly, their patients.

That said, in an encouraging takeaway HCPs have signaled they are still receptive to the right content when it’s delivered via the right channel at the right time. To communicate with HCPs effectively, life science organizations must embrace this learning and hyper-personalize content for each HCP, deliver it through the HCP’s preferred medium, precisely when the HCP wants it.

Effective communication through hyper-personalized content requires a significant shift in capabilities among life science organizations. Some are far along the personalization journey while others have barely begun. It necessitates deeper and broader datasets that also serve to integrate traditionally siloed stores of information, much of which has historically not been tapped for field force planning purposes. It also requires near real-time integration, eschewing traditional, cyclical data refreshes for always-on, automated processes.

2. How can data-driven insights help businesses better identify and close ‘Purpose Gaps’ in healthcare field forces?

Many businesses articulate a clear purpose statement but fall short of inculcating their values into every facet of their operation. Businesses that fail to embed their purpose may experience higher levels of employee dissatisfaction, more transactional customer relationships, and less effective decision-making. This is where data-driven insights can help life science organizations identify and close the resulting “purpose gaps,” principally in their commitment to customers. By fully committing to a customer-centric approach, organizations can create a positive, meaningful experience for their customers while simultaneously adhering to their core values.

A successful customer-centric approach requires an organization-wide transformation to re-orient each function and incentive toward customer success. Data and analytics can help drive this change and generate critical insights into optimal customer engagement. New data sources (or existing sources applied to new use cases), near real-time data integration and availability, and powerful analytical techniques can be combined to formulate a deep understanding of customers – how they prefer to interact, when they want to engage, and what messages resonate with them. These insights can help shape the organization’s customer-centric transformation, guide strategy and execution, and close purpose gaps.

3. Could you highlight some important areas in which AI and analytics can help in strategic field force placement? How does this translate to a more personalized and convenient HCP experience?

While field force placement has always been largely driven by analytics, we can now harness many more – and more diverse – datasets and advanced analytic techniques to optimally define coverage. AI has unlocked the ability to construct a far more detailed and comprehensive understanding of HCPs and their preferences than ever before, something that should be a driver of any coverage plan.

Armed with this information, we can design a coverage model to engage providers on their unique terms. This granular understanding of required workload directly translates into more accurate and appropriate field team allocation. Additionally, the advent of automated data integration and refreshes can help disentangle home office teams from the traditional cyclical approach, propelling a shift towards continuous refinement and field feedback loops. This approach also allows home office teams to shift their mindshare from repeated, operational efforts to higher-level, more value-add areas.

Aside from designing sales force coverage to be more aligned with HCP preferences, AI and analytics can also drive more personalized digital experiences. The pandemic triggered an escalated volume of digital promotion that often led to poor customer experience for HCPs. AI can help break through the noise, leveraging a significantly broader and deeper dataset to understand optimal channel, content, and cadence to reach an HCP.

Despite the early missteps with digital communication, HCPs are still receptive to relevant, personalized outreach. AI harnesses data sources across the enterprise, including those not previously utilized, to allow for hyper-personalization and custom tailoring of the message, including how and when to deliver it.

4. How can cognitive technologies be capitalized on to create optimized visit schedules and route plans?

Cognitive technologies open the door to factors and influences previously not incorporated into call plans. Traditional means of optimizing call plans and routing limit the number of data sources and the amount of data that can be reasonably utilized in the process. Due to longer processing timelines, legacy approaches also follow a cyclical process, typically one or two times a year. Cognitive technologies help remove these data and timing restrictions and permit significantly better personalization - key to reaching HCPs in today’s “new normal” and its hybrid digital/in-person environment.

Often, HCPs feel overwhelmed by prevalent, impersonalized outreach that ignores their personal preferences. Traditional call plan optimization is not designed to factor in those nuances, especially at the granular levels required to capture post-COVID HCP preferences. This is where call plan optimization driven by cognitive technologies excels: harnessing massive amounts of HCP-level data in a timely manner, enabling organizations to adapt and proactively meet the personalized needs of HCPs in a post-pandemic setting.

5. Considering your extensive expertise in healthcare, what recommendations do you have for businesses and field forces adapting to “Business Unusual” phases during and after the pandemic?

Some aspects of “business unusual” will inevitably stay with us and become part of “business as usual.” Many HCPs will continue to prefer virtual engagement and interactions to in-person calls, perpetuating the trend of reduced on-premises access. While digital engagement is an obvious path forward, it must be carefully orchestrated across all channels to cut through the digital “noise” of indiscriminate messaging. To successfully reach busy, overloaded providers, digital engagement should be highly personalized to ensure content is relevant and insightful. To operate in this environment, the field force will need to become increasingly digital savvy themselves.



Jeff Traenkner