6 minute read
Global AND Local
By Richard Marcil and Jessica Naman
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The pandemic has significantly accelerated Healthcare Professional (HCP) digital behaviours as well as increased Medical Information engagement. Across the world, Medical Information teams have been developing robust, self-service capabilities to grow capacity, accessibility, and customer satisfaction, while delivering compliant real-time engagement.
Consistent with other industries, conversational Artificial Intelligence (AI) is gaining a strong foothold in life sciences, and particularly in Medical Information. It’s a powerful technology and one that requires global and local planning, as manufacturers seek to deliver consistency, compliance and cost effectiveness across markets, and market-level teams adapt the technology and conversation sets to local stakeholders’ requirements - externally and internally. In this article, we look at 15 elements of conversational AI strategy that are key to successful scaling global AND local implementations:
1. Customer Experience
While seemingly obvious, choose a platform that truly meets the needs & requirements of global and local teams. Global teams require conversational consistency and compliance across markets, and an easy integration into global content and safety systems. Local teams will require ready adaptation of content into local customerfacing assets - digital and analog - as well as customer validation and Customer Relationship Management (CRM) systems.
2. Promotion and Awareness
Branding should be simple and consistent. Globally, many companies have moved to an AskManufacturer. com model, for simplicity and straightforwardness. Traffic driving will also be essential to growing utilisation, engagement and - ultimately - customer and clinical insights. Local teams will be key to driving visibility and access to these assets, using commercial-like tactics.
3. Data and Insights Leverage
Data and insights responsibilities will be shared amongst global and local teams. Global will often provide the technical infrastructure for data uptake and safety reporting integration, while local teams action data in near real-time - again, at customer and therapeutic level.
4. Consistency and Accuracy of Responses
Global teams will want to see a consistency of responses across markets whether it is the UK, Japan or America, and Local teams will ultimately adapt AI conversation flows and responses for their own country or region as per market and regulatory requirements. In time, consistency will lead to simplicity and universality.
5. Content, Information and Label Differences
This builds on the point above, it’s important to remember that conversation sets become business assets, from conversation flows, responses, and their respective data sets. Here, local teams will likely also consider marketspecific functionality, from service support to self-service automation to human escalation.
6. Accessibility & Access
Short of broadscale enterprise governance policies, accessibility and access are owned by local teams. This is especially key to driving traffic, utilisation, and cost deflection (from other more expensive channels) and generating powerful customer and clinical insights. This is an area where local teams will want to work closely with internal stakeholders to support broad visibility and access.
7. Languages
Most Life Science companies use English for the “core” set of conversations - the “master” so to speak. This master is adapted to other languages, typically by the local teams. The image below is an example of a conversation builder showing the English master, which is then replicated to Italian, Spanish and Japanese. This ensures consistency and compliance from a Global perspective, and easy adaptation by Local teams.
8. Workflow and Process Definition
Good workflow and process definitions are essential for global and local teams working together. Like a product monograph or label, Global will define and develop the core conversation sets and inform appropriate “on” label and “off” conversations. Local teams will build off of this and adapt these conversations for local markets, augment or add missing ones, and optimise customer onboarding and offboarding, including escalations and handoffs to humans.
9. Development Costs
Global most often takes the lead in the initial set-up and stand-up of the technology, including the configuration of the conversational AI platform, its validation, its integration in the tech stack, and even development of a core set of English conversations - again the “master”. When this is done, conversational AI becomes an organisational capability that any and every local team can, and should, take advantage of.
10. Data and Privacy
Data and privacy are equally shared across global and local teams. For both Global and Local, there is tremendous value in aggregate and customer-level data for clinical insights and medical-to-medical innovation. There is also great accountability around the data and privacy, so it’s important that conversational AI be integrated into the privacy, security, and information risk management frameworks of the organization.
11. Integration into Medical Information Databases
Integration into Medical Information databases varies tremendously from company to company, and sometimes region to region based specifically on the company’s needs for case management, compliance, content efficiencies and human-escalation. These are all the more important as conversational AI agents take on voice and Interactive Voice Response (IVR) channels, i.e. first point of contact.
12. Ongoing Optimisation and Maintenance
“Conversational maintenance” i.e. optimisation is a local responsibility first and foremost, given the unique nature of each market and the local conversation set. Local markets perform conversational maintenance and tuning based on their local interactions. However, Global will also uptake these optimisations across markets to the benefit of all markets (at least with the right conversational AI platform). Lastly, Global will most often assume the technology maintenance, e.g. new features, functions and configurations of the global conversational AI platform.
13. Technology and Vendor Assessments
Technology and vendor assessments are very important and a shared responsibility from the outset, with global teams leading the charge but with affiliates deeply inputting on needs and requirements i.e. integrations, languages, and resource load. In time, you will likely have a distinction of responsibilities and partners too - global partners for the technology platform that Global continuously optimises, and local partners that help with conversation development and maintenance i.e. consultants, agencies, etc.
14. Speed to Scale
Speed to scale is a material consideration as Med Info teams race to add capacity, accessibility, and responsiveness to operations. Global is typically the lead due to technology, vendor assessments and platform validation as per above - and it’s certainly something we’ve seen with recent COVID-vaccine scale ups. Practically speaking, global leadership is also tied to initial funding efforts, which local teams will require short of the largest markets.
15. Safety Reporting Standardisation
Safety reporting standardisation is globally led as one would expect with Life Science companies, but the accountability is very much local. Ultimately, it’s important that the chosen conversational AI platform be able to identify, manage and report adverse events and product quality complaints with the same accuracy as humans - if not better - across multiple markets. This is key to meeting safety and pharmacovigilance requirements, delivering better customer service and experience on and off hours, and driving business efficiency. In summary, customers now expect real-time, personalised and helpful engagement with Life Science companies - after all, they are getting this in every other aspect of their lives, e.g. financial, retail, travel, telecommunications, etc. Life Science companies are broadly scaling conversational AI capabilities to meet these needs as well as to drive operational effectiveness and efficiency. Best practices suggest that it’s the interplay of Global and Local - a coordinated investment approach to business value - that leads to the strongest, fastest, and most impactful business transformations and implementation of this AI technology. Curious to learn more about what is involved in deploying conversational agents? Get in touch with Richard Marcil with any questions at richard@conversationhealth.com
Richard Marci
Chief Customer Officer conversationHEALTH
Jessica Naman
Director of Marketing conversationHEATLH
