Reuters Events | Pharma

Thought leadership and innovation for the Pharmaceutical Industry

It’s been roughly two decades since eyeforpharma first brought industry leaders together to discuss the pressing needs in commercial pharma. Back then, the discussion ensued under the banner of sales force effectiveness. 

 

Consumers ‘surfed’ the internet, hooked up to it via dial-up modems, and what we today refer to as the generation of digital natives was yet to be born. Most physicians had precious few digitized tools in their office. Communication on the benefits of pharmaceutical products occurred over the phone and via print brochures. Reps met customers (often at lavish dinners). 

 

It seems an eon ago in today’s uber-mediated world of digitized consumerism, and the nature of the work of pharma’s sales teams has changed in various ways. As pharma identifies new means to engage with physicians, for example, it needs to understand the effects of managed care formularies on the ability to prescribe treatments.

 

Yet there is truth to the saying ‘the more things change, the more they stay the same’, and the sales function has stayed the same on a few central dimensions. To effectively communicate a value proposition requires a personalized approach, one which focuses on a very clear understanding of the targeted customer needs. 

 

Pharma is still striving to secure insights about total and new scripts, adoption sequences, the tendency to use a variety of products and patient demographics. 

 

Digital transformation

What has changed is that the digital revolution has created a profusion of available and relevant information to act on. We are in an era where there is no alternative but to mine, link and position various data sets for commercial success. 

 

“The way digital technology is transforming this landscape, the way we use data for instance as with pre-call planning has really been a rapid change over the last 10 years”, says Frank Armenante, Director of Commercial Execution at Novo Nordisk.

 

Let’s take the typical situation where a medical science liaison (MSL) field force has established strong physician relationships through their education around unmet need, prior to approval of a novel treatment. What is the best deployment strategy for key account management and sales post-launch? 

 

Well, in any of the leading pharma companies the strategic response to this classic scenario is today likely driven by predictive analytics, leveraging hyper-targeted insights and some form of artificial. These data points stem from the proliferation of alternative channels through which doctors now interact with and consume product and disease information. 

 

“We shouldn’t forget that supporting the learning curve of both sales team and the physicians they engage with has become critical in successfully leveraging these new technologies,” says Armenante. “If you are a sales rep today, you probably have some of the most exceptional data sets at your fingertips, but [we] must enable their skill set to effectively draw on all these insights”.

 

Training before targeting, infrastructure before insights

In this environment, it has been widely reported that field engagement needed to become more centered around consultative selling, which it sometimes equated with deeper capacity for medical knowledge transfer and the call to deploy more MSLs. 

 

“Having a profound understanding of the clinical value proposition is at the essence of the knowledge base of today’s sales reps”, says Armenante. “But our ability to create human connections, to ignite interest and establish rapport in personal relationships is as vital as it ever was in a pre-digital world”. 

 

So is an excellent understanding the business realities a physician office faces. This translates into the need to focus training curricula on B2B selling, storytelling skills and new types of messaging. Companies like Novo Nordisk are heavily invested in training programs around business acumen, data interpretation and use of electronic systems in the field, for instance. 

But none of that replaces the mission-critical focus on helping patients. “You need to understand the struggles your patients are going through with the disease. This will lead you to the physicians that treat them,” says Armenante.

 

Changing buyer profiles 

Back in 2000, the vast majority of [GP] offices were physician-owned, whereas following years of consolidation, institutional actors carry a lot more weight today. Now, integrated delivery networks own 6 in 10 physician group practices. Treatment protocols and formularies are now defined by P&T committees, not the doctors. 

 

“In the new environment, the physician becomes an employee, with that you get some access challenges and some need for skills adjustment”, says Armenante. However, this doesn’t mean there is no way of engaging. 

 

“If you have a well-educated and appropriately-resourced salesforce, health systems recognize [its] expertise, knowledge and education as a resource to help their physicians and patients understand pharmaceutical products.” 

 

This also leads to new account models, and opportunities such as outcomes-based contracting, which address the novel reimbursement models and value-based care objectives institutional actors are invested in. 

 

Considering the major issue of abandonment of scripts and high discontinuation rates, other stakeholders have grown in importance when it comes to optimizing patient outcomes. The average patient sees their pharmacist a lot more that they would see their physician, for example. “What resources can we get in front of the pharmacist so that they can have a really good interaction with their patients? It is our obligation in industry to help pharmacists support patients,” says Armenante.

 

Leadership in data science 

The first couple of slides of any popular conference presentation these days describe how pharma has undergone a data-driven, customer-centric transformation. In the process we have witnessed the convergence of data from different disciplines and historically organizational siloes. 

 

That process is what ultimate enables commercial success, requiring the coordination, linking and triangulation of insights between managed markets analytics, social media, customer segmentations, longitudinal prescribing information, geo-location data and DTC marketing statistics, to name just a few data sources. 

 

As the amount of available information continues to expand, the journey from information to insights has begun and data scientists have become some of the most important players in the company’s’ commercial operation, says Bharti Rai, Novartis’ Vice President of Commercial Effectiveness. 

 

As a member of the US executive committee at Novartis, it is her task to provide the leadership for various disciplines of data science, analytics and commercial operations so they can drive solutions in concert. “We need a combination of strategic direction and simply getting the plumbing in order, the hands-on and centralized data management without which we cannot succeed,” says Rai.

 

The widespread fear that this new environment would signify the beginning of the end of the traditional sales force didn’t materialize, she says. New capabilities support rather than supplant. “Data science and digital are meant to supplement what our reps are doing. So, we invest heavily in more precise targeting and customer information, as well as tools to enable them to be more successful once in the field.” 

 

The overall objective is to enhance every stakeholder conversation, taking the interaction with customers to a new level. 

Results from PwC’s 2018 Digital Pharma & Life Science IQ survey supports this sentiment. Only 21% of pharma leaders see digital disruption as a threat to salesforce numbers but when it comes to actual execution, the same research revealed critical gaps: Only 43% of respondents would agree that their company is making effective use of all the data that are being collected today.  

 

Driving internal change

So what is needed to succeed organizationally in this new era? “The amount of change management and learning on adoption, required to fully use analytics and data sciences is often underestimated,” says Rai.

 

She acknowledges a popular demand for the next ‘AI’ and fancy models. “But the truth is that once you have built a capable data analytics team with the right expertise, data analysis is almost becoming the easy part. It is using the analytics, driving change across the sales and marketing organizations which takes twice the effort.” 

 

Even for fairly simple programs, implementation, measurement and learning necessitates vision, executive stewardship and a good deal of patience.

 

A useful analogy comes from the rise of so-called Moneyball in major league baseball, the use of rigorous statistical analyses for evaluating player performance and building competitive teams around various new datapoints. Sabermetrics (the empirical analysis of baseball) have changed the nature of the game, but as Novo’s Armenante points out, this is not enough on its own to drive any team to win a World Series. 

 

It is rather the unique balance between the art and the analytics that makes the difference. “The pharma industry has a similar opportunity – for commercial success we need to marry best-in class data science and insights with classic engagement approaches in the field,” adds Rai.