Achieving Digital Maturity

Most pharmaceutical and life sciences firms are well aware risks associated with medical compliance, but very few are aware of the risks associated with their marketing and commercial operations. With the advent of digital marketing in general and programmatic marketing in particular, the industry suddenly finds itself grappling with sophisticated marketing technologies, something that has not traditionally been their forte. Last year, Johnson & Johnson, one of the largest advertisers in US, pulled back their YouTube advertising amidst concerns that their advertisements were being displayed next to objectionable material such as hate speech. This was certainly not an isolated incident; across the Atlantic, another large pharmaceutical firm GSK was also cutting back their digital advertising spend, citing brand image concerns.

Pharma companies maintain a fine balance between (a) delivering a great customer experience and (b) optimizing their operational efficiency. The tenets of an operationally optimized system include delivering compliant and consistent content, scalable across channels in all markets, and finally data driven content strategy to gain insights from each HCP engagement. While a handful of companies display highly sophisticated, efficient and institutionalized operational setup to deliver rich customer experience, e.g. Magnums - majority qualify in the Greenhorn segment with minimal enterprise-wide digital adoption and maturity in operational systems. Pfizer, Merck, and AstraZeneca appear in the top quadrant for Magnums in a recent Digital Maturity study.

At the most nascent level of the digital maturity model, content production is decentralized to the extent that it is produced separately across different countries and channels. And this is where 90% of the problem lies. The pharma industry doesn’t see reuse of content between global and local assets across different channels. This amounts to time and cost overruns, not only from an operations perspective but also medical, legal, and regulatory (MLR) cycles and speed to market. The other end of the spectrum on the content maturity continuum envisions “content-on-demand.” The content at this stage of the maturity model is fully responsive and dynamic. With pre-set algorithms, the next best action is picked up by the channel and the content is tracked intelligently through its engagement journey.

With artificial intelligence (AI) and machine learning (ML), etc., trending on the horizon of digital initiatives, many companies are exploring this white space to see how these can be adapted to fit their requirements. Transcreation of assets across different channels can be expedited through the use of an AI-powered disruptive approach. With AI backed tools, the translation of global assets to multiple languages can be automated. Also, the content will be customized/localized as per regional specifications and regulations. This will not just result in significant cost savings by reducing redundancies but also bolster increased compliance.

As organizations move up the Digital Maturity Index, they start realizing the benefits of automation and put in place a unified operating system for coordinated workflow across the content chain (Content Strategy, Content Production, Content Storage, and Content Reuse). The unified workflow helps with operational optimization for development timeline as well as resource deployment. Further evolution on the automation front sees the finer nuances of AI and Machine Learning coming into play with tools like the Virtual Content Creator and AI-driven content reuse. Virtual Engagement Manager or VEMA is another example of a cloud-based platform to support workflow automation, access to templates and best practices, AI-driven asset tagging to drive content reuse, and real-time status reporting. At the most mature level, all technology as well as infrastructure enablers become increasingly adaptive and responsive to support new needs, thereby paving the way for end-to-end automation of content strategy, content deployment, and content outcomes. The current reality however is that pharma marketers’ see the role of automation mostly in the content deployment stage.

Digital maturity also brings recognition of the importance of analytics and KPIs. Organizations start investing in a unified architecture and a basic data warehouse for number crunching. Additionally, they start rolling out pilots and testing out strategies based on the insights being generated. Organizations thus graduate to the next stage of the maturity model wherein they consider data and analytics as an established competitive differentiator for themselves. Data is managed on a real-time basis. There are ample use cases that demonstrate strong correlation between analytics and business outcomes.

It is time for pharma companies to take a longitudinal view of their commercial efforts through digital maturity – one that enables them to walk the content, compliance and engagement tightrope with fair amount of ease.

Gaurav Kapoor is co founder and EVP of Indegene.