Arkana metadata

How to build flexibility into a modern global commercial model

By Rakan Sleiman

Most life sciences companies are at different points on the road to digital transformation. A 2020 KPMG survey found that nearly half of respondents have started limited implementations and nearly a quarter (23 percent) are
doing pilot programs specifically for artificial intelligence.

Most of these technologies and their requisite strategies are being rolled out incrementally, by brand and by region. The timeworn “trial, test, learn, expand” approach is more palatable to a risk-averse industry. However, this approach results in discrete strategy execution that looks very different market by market. Cultural, language, and regulatory differences; varying technology landscapes; differing channel options; data discrepancies; and divergences in physician and patient expectations all play a role, but this dated commercial model yields the same dated results.

As more pharmaceutical and medical device companies take stock in their early transformation efforts, CEOs say returns are slow. In 2020, about 80 percent said they expected to see a return on investment in one to three years. After years of taking a conservative approach, companies are now recognizing that their commercial strategy should be defined at the global level to move the business forward into the digital world quickly and then cascaded down to different regions and individual markets. Here, tools and tactics can be nuanced, but a holistic approach is the most streamlined.

Illness has no borders. Neither should commercial strategy, as the market-by-market approach can become cost-prohibitive when companies find themselves rebuilding many of the data pipelines fueling AI and other technologies. It’s also slow – an issue exacerbated by the new sense of urgency for digital engagement created by the pandemic and HCP expectations for personalized interactions in their preferred channels. 

It’s time, maybe past time, to scale digital transformation globally…but how? How can we make it more efficient to implement new commercial tools like AI? The key is to build flexibility into the global commercial model so companies can leverage economies of scale while incorporating learnings across markets. A flexible commercial strategy has three hallmarks: 1) leverages the common properties in the global brand strategy, 2) accounts for known variations, and 3) allows for cross-brand pollination.

LEO Pharma, a global provider of medical dermatology products, began its digital transformation journey by following six key guidelines to create a flexible commercial strategy that cascades down to regions (instead of the other way around). “We believe in the power of integrated ecosystems that enable engagement orchestration for a seamless customer experience across all channels,” says
Veronica Onisoara, customer engagement manager, Europe, at LEO.

As a first step, LEO is integrating an AI platform that facilitates a versatile, modular approach.

“Aktana’s Contextual Intelligence Engine is already enabling our commercial team to optimize their communication and be more consistent with planning and execution across markets.” Even in the early days, the AI solution has resulted in 78 percent engagement with field sales (versus a benchmark of 60-70 percent) and next-best-action suggestion acceptance of 48 percent (benchmark: 30-50 percent) in the United States. The program is being rolled out across key European markets this year.

The following are six guidelines LEO is following to build a flexible commercial strategy.

1. Standardize on the same CRM or marketing automation solution.

It might sound obvious, but there is extra complexity when companies use multiple CRM or marketing automation systems globally. For instance, rather than relying on homegrown CRM systems in some markets and different CRM providers in others, standardize on one. 

Of course, this doesn’t mean companies will have a single CRM instance. Many companies may have an instance for the United States, another for Europe, and so forth. However, it reduces friction and inefficiency to standardize one CRM configuration across all instances.

Similarly, it is valuable to standardize the commercial technology stack. If you are using one marketing automation tool in one market, use the same in other markets. The same is true for other applications like event management, the data warehouse, or the sales data pipelines. In all cases, consolidate and integrate systems wherever possible for a better user experience. This also simplifies data sharing and access across users and regions.

2. Align on common data requirements.

Next, it is critical for brands to standardize on a common set of customer data points that brand teams use for planning and strategy execution.

For example, customer attributes such as physician specialty, segment, consent status per channel, speaking skills, and account type are important to nearly all brands across markets. There are additional types of fast-moving data – such as whether an HCP attended an event or how they engaged with recent emails – that brand teams often need to both
measure impact and effectively execute their commercial strategies.

Technically, it is important to align on metadata first, then on the data itself. As figure 1 shows, there should only be a single global attribute (column) for the common customer properties (green dot). The second table is an example of what not to do, where every market or brand team has a unique data point (red dot) for what is effectively the same customer attribute.  

Arkana metadata

Figure 1

As one market builds up this list of data points, opportunities for cross-pollination become apparent: data points of value to one brand are also valuable to others, thus offering insights across therapeutic areas and geographic regions. This also provides companies with technology data management efficiencies.

3. Identify known HCP differences and make allowances.

 When thinking about how to characterize HCP demographics and preferences, it is helpful to identify “known” differences region to region, such as language, culture, country-specific regulatory constraints, marketing authorization and approval processes, data availability, and enabled technologies. There are also “common” differences unique to each HCP, such as types of patients treated, channel and content preferences, and channel availability.

Successful technology deployment across different markets depends on understanding the known and common differences and being able to act on them in a meaningful way. Such variations can be managed with the right data model and technologies.

4. Enable all communications channels (but offer a clear opt-out strategy).

The channels for communicating successfully with HCPs are many and growing. The pandemic has shifted many people – both sales teams and their clients – to digital channels like virtual calls, but that is by no means universal and permanent. To be relevant and enable evolution, a global commercial strategy should leave room for using all channels, including face-to-face. Likewise, focus on capturing channel consent from HCPs.

One caveat: the individuals responsible for executing the sales strategy day-to-day. If a field team is not prepared or incentivized to engage digitally, consider initiating a change management program, and offer training and onboarding so that your sales force can make the most of these channels when they become available.

“We have prioritized efforts to prepare our field team to take full advantage of our new AI tools by training them with the right digital skills and capabilities,” Onisoara says. “When launching the solution, it is important to explain how it works and its benefits, both to individual users and to the overall business. We have also educated marketing and medical teams so the system will become a natural part of the new ways of working across the whole organization.”

5. Embed intelligence into field users’ workflows.

A data collection process for gathering insights from HCP interactions should be user-friendly. You don’t want users jumping from one place to another to find different pieces of insights or the output of analytics. There should be one place where users can get all-encompassing sales, digital, channel, and engagement insights. And it should be available in the same way for users within markets. 

Ideally, all users around the world would consume insights in the same place. So, work to keep processes as consistent as possible across markets and have a specific, data-driven reason for any variances. While it can take more effort and discipline up-front to design (and carry out) a “one-stop-shop” approach, it becomes easier and more cost-effective as the project scales. 

6. Follow the 80/20 rule (80 percent standard; 20 percent custom).

At the beginning of an implementation, strive for standardizing across most (80 percent) data types and suggested next-best-actions. Inevitably, companies will need to customize some of their data sets as new requirements become known but minimizing data type differences is critical to establishing a global strategy that can cascade down into other regions. 

A governance structure will make the standardization and customization process easier to manage over time. For example, a governing body can evaluate the performance of the tool and update it in a way that is consistent with sales practices and data availability. 

This governance is vital to enabling a fast deployment across multiple countries. “We have clear frameworks for planning, impact measurement, and actionable insights established across the organization,” Onisoara says. “In this way, we are building flexibility into our new AI system so we can efficiently implement it globally while making critical allowances to provide HCPs with personalized customer journeys.” 

Commercial and medical teams are being stressed like never before by rapidly changing market conditions and demand for digital strategies. New technologies such as AI are becoming an essential way to cope, enhance customer experiences, and even get ahead. By taking the time to lay a smart foundation for scalability, a faster, easier-to-implement, and more effective program can take shape globally. 

Rakan Sleiman is director of product management for Aktana.