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Over the years, biopharma companies have gone to great lengths to transform themselves digitally. They’ve onboarded serious technology, made eight-figure investments and hired scores of subject matter experts.

However, as counterintuitive as it may seem, those in the marketing and commercial ranks say the industry has yet to make major gains on the digital transformation front. Data from the second annual MM+M/Publicis Health Pharma Marketing Transformation Survey backs up what industry leaders told MM+M.

Just 39% say new ways of harnessing advanced tools such as AI and machine learning are deeply embedded throughout the organization, including for marketers, which is up from 27.8% last year.

The less-than-stellar state of progress underscores the need for a more extensive root system that can foster vigorous growth. Innovation can’t bloom without real integration of these advanced analytic tools.

Improvements — or lack thereof — vary across companies, explains Arpa Garay, a marketing and digital transformation veteran who held executive roles at Moderna and Merck between 2022 and 2024.

“In the past three years, there’s been much more of a top-down sponsorship on adopting data and technology,” notes Garay. “So I feel like the pace for transformation has accelerated. Is pharma completely there yet? No, absolutely not.”

Infusion rates

That said, Garay has observed “more of a willingness and an interest” among marketers to learn about the capabilities of data and technology, as well as an attitudinal shift away from looking at these merely as cost-cutting tactics. We’re beginning to see significant year-over-year change. And although we’re not talking Amazon-level yet, the fast pace of AI advancement means pharma will have many opportunities to deepen the tools’ adoption rates and understanding of how to use them properly.

Fifty-five percent of respondents say digital and analytics know-how is infused throughout the company, up from 44% in our inaugural survey. And 40.6% say expertise resides within a particular business unit, an improvement from 48.6% a year ago.

Despite the gains, just contemplate how many organizations have made significant investments for and have drawn up detailed road maps toward going digital. It’s understandable, then, why many people would have expected the advances to be more significant by now.

“I actually find it kind of alarming,” says Kelly Tullo, who works in customer engagement at AstraZeneca, explaining that the aforementioned infusion rates expose the inadequacy of the overall implementation plan for digital.

“I don’t know if advanced analytics [initiatives], on the implementation side, have the depth that they originally were intended to have or were [even] set on the right course,” she says, adding that the data suggest many of the investments “were made for short-term gains versus, ‘Holistically, how do we actually define the value that we’re trying to derive from all of these tools?’”

And therein lies the ongoing challenge: “We all have to look more inwardly,” she says, “and decide internally how we’re actually going to make real progress.”

The AI letdown

The industry has its work cut out. For instance, while 55.6% of respondents say they’re using AI for sales and commercial functions, 45.8% say AI in that area is falling short of expectations. Ditto for content production, where AI is used by 77.8% of respondents but comes up short for 40.3%.

Felix Lee, interim head of organizational capability and transformation at Sanofi, interprets those results to mean companies are having success at driving a “mindset of transformation,” but that the reaction their people have when using the technology isn’t so hot.

There are real reasons for that letdown, of course.

“There is a big difference,” Lee notes, “between what we hear about the potential of what AI and generative AI can do for us, versus exactly how much we’re able to start doing as a company because of the inherent risks involved, as well as the infrastructure and architecture it takes to actually make it happen.”

Indeed, Lee has seen this pattern before. “You get the mindset going first, so people are excited about it and want to try it,” he explains. Once they do, “They’re like, ‘Oh, well, it’s not so good,’ or, ‘That’s it? Can we not do more?’”

These organizations may have yet to put responsible AI principles in place, Lee surmises, or may have started from low-risk activities versus those processes that showcase AI’s more cutting-edge possibilities.

Then again, he sees a silver lining in the tension: “The more people want to do things that are more advanced than what we currently are able to actually do … then the more we will strive to actually try to get there. So the directionality is there; that’s a positive sign.”

That directionality offers a platform from which to build — even if a whopping 68% say the medical marketing industry’s progress in adopting AI is “behind where it needs to be.”

Attitudes and buzzwords

In the early days of data and digital transformation, Garay recalls a lot of questions around what it can do to impact the business and how much should organizations be investing.

By contrast, the biggest barrier today isn’t “should we?” Indeed, Garay has seen attitudes shift over the past decade, with one sign being the spate of announcements involving partnerships between drugmakers and GenAI vendors.

It seems that skepticism around AI’s relevance has, for the most part, died down. ChatGPT, OpenAI’s consumer-facing GenAI interface, has done much to foster that acceptance.

“Now, obviously with generative AI and all these newer tools, it has almost forced employees outside of their day-to-day work to experiment in their personal lives,” Garay says, “which is actually helping some of that adoption and bringing that back in.”

Openness to other aspects of digital aren’t quite so pervasive. In talking with marketing executives, one gets the sense that many perceive transformation as a very buzzword-driven process rather than actually delivering meaningful change for their organization. Take the rallying cry around omnichannel marketing.

“Yes, omnichannel strategies are being prioritized,” admits Tullo, “but there’s real confusion around the definition and the execution of it.” She adds, “It’s really unclear on how to deliver integrated and seamless across channels.”

That, she says, stems from a fundamental reluctance among marketers, many of whom are driven by the need to meet forecast goals, to even acknowledge the issue. It’s hard to achieve the potential of a new tool or change a strategy if those involved actually don’t think there’s a problem.

“If the playbook has met those [forecast] goals and is working in their eyes, why do they need to change?” Tullo posits. “Cultural resistance to change is so strong.”

Garay also acknowledges pharma marketers’ traditional reluctance to take monies away from the tried-and-true and put it into some of these newer areas.

“Some of it is risk aversion, and some of it is also that not all the capabilities are fully built in most organizations,” she points out. “So there’s still a reliance on vendors.”

Too, there are still conversations on buy versus build versus partner. “There’s a reality that more and more companies want to build capabilities, but they don’t necessarily have the talent to be able to do that,” Garay says.

Analytic graveyards

It’s no wonder, says Lee, that the vast majority of enterprise transformations fail to achieve their intended outcomes. Recent research from Bain & Co. puts the success rate around 12%.

“That percentage really hasn’t changed over the years,” he notes.

Among the main predictors of success, the consultancy found, is figuring out which roles are essential and getting the right talent into those positions. Behavior change starts from the ground up.

“Top-down doesn’t make transformation happen,” says Lee. “Top-down can change the structure, can give a new direction. But it takes everybody bottom-up to actually make the transformation happen.”

All of which underscores the need for deeper integration of digital tools. “Training, networking, trust-building and internal cultural shift is the only way to surpass the confusion and turn the resistance down,” Tullo says.

Asked for their transformation wishlist, 47.2% of survey respondents call for “better data.” But most marketers have access to a rich repository of it through self-serve analytic dashboards, sources say.

What is lacking are the actual skills internally to analyze and use data sets effectively. Just over half (54.2%) say they want “better and/or more frequent training on AI tools such as ChatGPT,” and half are clamoring for a “designated AI employee expert” to fully realize AI’s potential.

To hear Tullo tell it, “We have a lot of data scientists … but they don’t necessarily know how to create the storytelling around the data to have a really collaborative, strategic, action-focused conversation.”

Marketers, for their part, might not be as digitally savvy as a data scientist, and may not feel comfortable using all of the data science tools at their disposal. But they are absolutely in tune with their market, brand and the challenges therein.

“From my observation, the two are speaking different languages,” Tullo observes. “I see a ton of graveyards being created of very expansive analytical dashboards. In real life, a marketer is not an analyst.”

Garay, too, has frequently seen this “language barrier” between pharma and tech people. Until it’s addressed, transformation squads aren’t there yet.

“It’s very hard to change behaviors dramatically if you have the exact same workforce,” Garay explains, adding that companies need to hire more people with data, engineering and tech backgrounds who can help partner with the business on what’s possible with new technologies.

Talent hailing from outside the industry requires a learning curve to get up to speed on pharma’s regulations. An alternative way to bridge the linguistic gap is for in-house marketers to bring in a “translator” of sorts, someone responsible for bridging engineers and the business.

MLR falls behind

The study measured which marketing tasks draw the most AI adoption, lead by communications and creative at 73.6%, followed by omnichannel marketing at 66.7% and

content production, 62.5%. On the sales side, it’s forecasting and brand intel, 61.1%, and decision support, 52.8%.

Although MLR (medical-legal-regulatory) is such a big pain point for marketers, the adoption rate is a paltry 19.4%.

Yet, each of the other tasks in the marketing section requires MLR review before reaching any external stakeholder.

“Everything there is upstream of MLR,” Lee points out. “So, if we don’t do something with this low percentage for MLR review, we end up creating a different bottleneck. Because we are going to be much better at generating content, then, by definition, we are going to overload the MLR function.”

In fact, possibly because the upstream work has improved, results show MLR falling further behind. This year, when asked whether medical/legal staffers are able to keep up with pace of change, just 49.0% said “yes,” down from 55.6% in last year’s survey.

Garay, for her part, says she’s “not at all surprised” by this statistic, given that MLR staffers’ traditional areas of focus were not around technology. “They were around claims, promotion and what you can say and how you represent things.”

While that world is changing with the advent of tech, MLR teams, she says, are probably “not getting as much of the same training on technology and data as the marketers.”

Pfizer, for one, has reportedly applied GenAI to its content-generation pipeline, giving its MLR process the ability to “learn” about boundaries based on what’s been approvable before. In this way, the company can reach a point where new content generated is closer to what previously passed muster, something which may help relieve the bottleneck.

Meantime, the aforementioned use cases do demonstrate a motivation for using AI. Whether teams have the wherewithal to apply AI fully in those areas — not to mention other requirements such as a mature IT infrastructure, governance framework and ability to run pilots — is another matter.

To wit: When asked to rate their own companies’ progress in deploying AI into workflow and products, an unflattering picture emerges: Some say they’re “nowhere” — thankfully, just 11% of respondents — but fully half say they’re behind. A quarter say they’re right where they need to be and 13% characterize themselves as “market leaders.”

Better together

If we base the extent of transformation success in marketing on the degree to which newer tools have been infused into organizations, then the overall survey findings imply that biopharma has achieved a transformation toehold.

Yet even the slight gains may be superficial. Many years on, marketing teams seem to be failing to align technologies with the broader business goals.

The problem falls squarely at the feet of those most responsible for championing transformation. That’s generally the chief marketing officer (25.0%) or commercial chief (11.0%), along with multiple execs across divisions in tandem with the chief technology or digital officers.

Garay, who’s walked a mile or three in their shoes, sums up the main reasons major progress has often eluded these leaders. Changing habits is hard, and technology is evolving rapidly, creating a moving target. Then there’s the difficulty of finding the right combination of technology, talent and data.

Tullo, for her part, concludes that until now, “I think people have found a way to not really disrupt their we’ve-always-done-it-this-way playbook. What they’ve added is omnichannel-esque.”

Pharma may still find itself lagging behind consumer-facing industries, but the improvements suggest innovation is becoming more embedded, as companies look to drive transformation into the future. To that end, according to the survey, marketing and tech execs appear to be co-leading experimentation of AI tools and processes.

Each has strengths: CMOs and CCOs are more adept at driving change because they can make decisions on trade-offs across tech and other levers much faster than CTOs or CDOs, who bring talents from the digital world, Garay explains.

Working in close partnership, they can potentially be greater than the sum of their parts. For those roots to allow innovation to blossom, they’ll need to be.

“The next phase of the transformation will be to say, ‘Where can we realize cross-divisional opportunities?’” predicts Garay. “The pace of adoption has accelerated, but there’s still room to grow.”

A year of digital transformation in pharma marketing

By Tracey O’Brien, chief client officer, Publicis Health

What a difference a year makes.

In the second year of the MM+M/Publicis Health Pharma Marketing Transformation Survey, we’re witnessing a clear shift in how pharmaceutical companies and their partners are coming around to more fully embrace advanced analytics and technology tools, particularly artificial intelligence (AI). While last year’s survey revealed a nascent but growing adoption of AI and data-informed approaches, this year’s findings paint a picture of a healthcare industry rapidly accelerating its data- and tech-driven transformation.

One of the most striking trends revealed in the survey is the increased infusion of digital and data analytics know-how throughout pharma and partner organizations. A considerable increase in respondents (from 44% to 55%) reported these practices are now better infused across various business units instead of being isolated within a single function. This dispersion of knowledge is a positive sign, suggesting the breaking down of silos and the development of a more collaborative and effective approach to leveraging data and technology.

Last year, we noted the rise of a new class of pharma CMOs, and this year, it became clear that these leaders are playing pivotal roles in driving transformation at their respective organizations. A quarter of respondents indicated their CMOs are responsible for translating marketing transformation initiatives into tangible value creation. This underscores the importance of CMOs as strategic leaders who can bridge the gap between technology and business goals.

While the survey revealed a growing optimism about organizations’ ability to succeed in today’s complex landscape, there are still challenges to overcome. A close majority of respondents (51%) expressed concerns about medical and legal staff keeping pace with the rapid advancements in technology. This highlights the need for increased education and training to ensure all stakeholders are equipped to leverage digital tools effectively.

AI is undoubtedly gaining traction in the pharmaceutical marketing space, with more than three-quarters of organizations saying they use it for content creation, production and marketing. However, it’s important to note that AI is not a panacea. While it offers immense potential, it’s essential to approach its implementation with a balanced perspective, considering both its benefits and limitations.

Our survey also shed light on the expanding applications of AI in areas beyond marketing. Medical affairs and clinical trials are emerging as key areas where AI can make a significant impact. For instance, AI can streamline the often-laborious process of medical legal review, improving efficiency and accuracy.

To fully realize the potential of the myriad advancements in technology and data, organizations must prioritize several key areas: Effective training programs are essential to equip employees with the skills needed to leverage new technologies and processes. Access to high-quality data is another critical factor, as AI relies on robust datasets to deliver the best, actionable insights. Lastly, buy-in from senior management is crucial to ensure AI and other tech-related initiatives are supported and prioritized.

By fostering a collaborative environment and investing in the necessary expertise, pharmaceutical companies can position themselves for long-term success in a rapidly changing world. This is great news for those of us who are committed to helping our partners navigate this transformative landscape and unlock the full potential of data, AI and other emerging technologies.

From the October 01, 2024 Issue of MM+M - Medical Marketing and Media