Post-COVID World Demands More Than AI

This is a new world for everyone. COVID-19 has disrupted almost every aspect of day to day life, and all businesses are fundamentally shifting to meet the demands of this novel moment. A crisis like this is often not one event, but many interconnected crises. If we’re not constantly learning and adapting, we’re going to be facing a long, painful recovery. We need to modernize how we operate. 

This article will address how Contextual Intelligence, a unique blend of advanced technologies and human intelligence, is needed to transform pharma commercial operations in our new normal and how this moment provides, in the words of Eli Lilly CEO, a “once in a generation opportunity to reset” the industry.¹

A Post-COVID world for pharma execs

Years before this crisis hit, communication between healthcare professionals and pharma organizations was evolving rapidly - driven by a demand for more personalization.

COVID-19 has dramatically accelerated that evolution and raised the bar for personalization. Almost overnight, the industry was forced to move to digital and remote engagement. To cut through noise, timeliness and relevance of communications became paramount, prioritizing empathy for how individual HCPs were affected by the pandemic. Content development and digitization needed to be more agile, and expand beyond brand focused messaging to include content focused on HCP and patient needs.

The added complexity highlighted the need for better coordination and planning across channels to avoid uncoordinated overlaps, unintended relationship gaps, and interaction fatigue. The role of supporting field and marketing teams became more important as they played a critical role in overcoming the information overload that accompanied more channels and content and improving data-driven decision making.

As we settle into a “new normal,” a mix of traditional and digital engagement has become the newly-minted engagement model of today. It is more important than ever to use advanced technology that uses real time feedback and data-driven decision support, to help coordinate activity across multiple channels in a way that aligns with HCP expectations as well as a post-COVID world. 

AI - it’s not a catch-all

AI has been applied in broad, uncertain strokes for years. One can’t simply dip a brush into the AI paint can, slap it across the surface of the pharma commercial model and expect results. 

It requires an approach which is dynamic, tailored and sophisticated given the myriad of variables to consider, with much at stake. Pharma mandates a very specialized approach due to factors related to the industry (e.g. regulations, data privacy, and therapeutic area constraints) and each company (e.g. available data, channels, and the nuances of each brand’s strategic priorities).

The reality is that today most solutions marketed as “AI” are really machine learning solutions. These systems consume data, create algorithms, and make predictions. But if the goal of AI is to achieve human-level or human-enhancing intelligence, then machine learning alone is not enough. Machine learning technologies can’t master even the simplest challenges without human-provided context. Because the fact is, context matters.²

Introducing Contextual Intelligence

Contextual Intelligence is the ability of a system to take what it knows and make it work from one situation to another and not just the environment in which it was learned. For life science commercial teams looking to leverage AI, it enables going beyond basic triggers and predictive models to ensure intelligent engagement is relevant (reflecting the interests and preferences of HCPs), aligned (ensuring coordination across sales and marketing efforts in every channel) and learning (refining strategy based on what is succeeding and failing in the market).

Over 10 years working with major global pharmas on this exact challenge, we have learned that the key is to incorporate the right blend of advanced technologies and human intelligence. This allows for a “human-enhancing” level of intelligence that is delivered in a way that people want to adopt.

Key ingredients for achieving contextual intelligence

The following key ingredients have proven to be critical for a well-oiled Contextual Intelligence system.

● Business logic: Business rules allow the knowledge of experts, like the go-to-market strategy of your brand team and the behaviors of your top performing sales reps, to be codified in a system. This not only provides a powerful starting point for intelligence but also acts as constraints in which machine learning and optimization can operate.

● Machine Learning: Machine learning ensures that we take advantage of what can be learned from every interaction with each HCP, to work out the ideal message sequence, timing and channel, using the most up-to-date information available. Used in the right way, it not only removes the time and overhead of capturing all permutations of your strategy as discrete rules, but also identifies micro-level insight that may have been difficult for experts to gleam.

● Optimization: Optimization plays the crucial role of prioritizing theoretically ideal outcomes against real world constraints like limited resources, time and attention. This increases adoption of recommendations, by keeping things practical and simple for sales and marketing decision makers, and also improves relevance for HCPs, who have limited attention.

● Explainable AI: Explainable AI (xAI) provides decision makers with the data and context they need to act on recommendations. This is critical for ensuring adoption and impact by sales and marketing users. In addition, it provides clarity into what is working and what is not working in the engine, enabling a feedback loop that allows strategy to constantly improve.

● Human Intelligence: Two elements of human intelligence tie the technology together. In-house team experience needs to be captured in the business rules and is required to successfully govern how technology is integrated into your commercial business processes at scale. Expertise (including best practices) is also important to ensure success at launch, ongoing evolution and future expansion. At Aktana, we draw upon the knowledge we’ve accumulated from launching and scaling AI across 250 global experiences, and our customers benefit from this expertise.  

Along with these key components, we’ve learned that it’s the proportion, timing and expertise with which they are applied that generate truly transformative results. It’s the perfect blend of technology and humanity that works together to solve this important challenge for the pharma industry.

Context is key for our new normal

COVID-19 has blown the doors wide open on theoretical priorities, and driven the industry forward on the path to a new commercial model by years in a matter of months. Contextual Intelligence combines technology and human insight to meet the bar for engagement in a post COVID-19 world where HCPs are expecting seamless handoffs, responsive engagement, and timely follow ups. Pharma commercial teams need to be able to use right channels and content, in the right way, based on all the relevant context. 

AI plays an important role in how the industry is adapting to these new challenges, but to successfully deliver business impact, we need to take into consideration every relevant factor and apply it in context. While analytics and machine learning are important, alone they are not enough.

Derek Choy is co-founder & Chief Operating Officer of Aktana.

Notes

1. www.fiercepharma.com/pharma/amid-challenges-a-covid-19-opportunity-for-pharma-a-chance-to-bolster-its-reputation-lilly

2. www.technologyreview.com/2020/05/11/1001563/covid-pandemic-broken-ai-machine-learning-amazon-retail-fraud-humans-in-the-loop/