Keeping pace with the challenge of change globally, the macro environment in the pharma business is also undergoing a metamorphosis. This includes areas, such as, strong product pricing pressure, dwindling new product pipelines, increasing operating expenses, stringent regulatory requirements, rising stakeholder expectations, and several others. All these developments collectively, are making the drug companies, both global and local, feel the tailwind of various intensities, in their efforts to achieve the corporate financial goals, more than ever before.
Despite this continuous change, most pharma players’ overall strategic business models to meet with the increasing economic expectations of the shareholders, other investors and the stock markets, have hardly undergone any path breaking, radical, or disruptive advancement, just yet. This includes even the most critical interface between an organization and the consumers – pharma sales and marketing.
That said, it is not uncommon, either, to witness some sporadic initiatives of major business process reengineering with sophisticated digital applications. Interestingly, all these measures are mostly replacements or for realignment of the same age old, and traditional strategic pharma sales and marketing models. Most of these are aimed at adding more speed and accuracy to the same business core process, along with ensuring greater management information and control to support the decision making process.
Despite this palpable environmental shift, general inertia within the pharma industry to respond to all these, with commensurate strategic game plans of surgical accuracy, is glaring. Currently, the general response to this transformation is mostly reactive and traditionally defensive in nature, rather than proactive, as the overall business environment around the industry keep becoming increasingly demanding. Most pharma players may not, but the time keeps galloping ahead, offering a mind boggling rapid advances in disruptive technological innovations – the potential game changers for its several business domains.
In the midst of such all-embracing changes, yet another disruptive technology – ‘Artificial Intelligence (AI)’, is prompting many business leaders to step on to a brand new paradigm, making use of AI to the extent required, especially, while preparing a detail strategic roadmap for the business with high precision.
A clear intent to seize this moment is now visible in many industries, though in varying degrees and scale, but surely it is happening. This is vindicated by the gradual increase in demand for AI, across a wide variety of its application areas.
Marketing to turn upside down?
On October 26, 2016 an article published in ‘The Huffington Post’ on how AI could ‘Turn the Marketing World Upside Down’ indicated its disruptive impact on the way innovative marketing strategies are conceived, created and implemented on the ground.
The article gave an interesting example of how paradigm shift follows a predictable pattern of development that starts with substitution, followed by augmentation, modification, and finally redefinition.
For example, the evolution of today’s smartphones also followed the same pattern, as follows:
- First replaced simpler landline phones
- Then adapted with the addition of a camera
- And finally redefined “phone” altogether, not just by replacing cameras, pagers, and many functions of personal computers, but by being able to perform with great precision an incredible number of various other serious requirements, well supported by related digital apps.
With the application of AI in marketing, the conventional ball game right from conception, to charting out and execution of marketing strategies, will be catapulted to a new and fascinating orbit altogether. I have no intent to romanticizing it. This is going to happen sooner than later, as we move on.
Artificial Intelligence (AI):
In a simple and commonly understandable way ‘Artificial Intelligence (AI)’ can be explained as the theory and development of computer systems, which are able to perform tasks normally requiring human intelligence, such as, machine learning, visual perception, image processing, speech recognition, decision-making, and language processing, besides many others.
In the Hollywood film industry, several sci-fi movies have already been made, based on AI as the core theme. Some of these international blockbuster films are ‘The Terminator’, ‘Transcendence’, ‘The Matrix’, ‘Ex Machina’, ‘Ex Machina’ or even ‘2001: A Space Odyssey’, among many others.
Some concern, but…:
Alongside, a serious concern has also been expressed by some global icons, that the evolution of AI could reach a dangerous threshold, where mankind will no longer remain in control of the creation of its own progeny, besides other living beings. This could, as they believe, jeopardize the continuity of an entire civilization, at least, in its present form.
In 2014, globally acclaimed Professor Stephen Hawking commented in an interview with the BBC: “Humans, limited by slow biological evolution, couldn’t compete and would be superseded by A.I.”
In fact, in July 2015, Professor Hawking reportedly joined Elon Musk, Steve Wozniak, and many others, warning that AI can potentially be more dangerous than nuclear weapons.
In the same year, even Bill Gates, co-founder of Microsoft, reportedly expressed his concerns, saying, “I am in the camp that is concerned about super intelligence…”
On the other hand, despite such apprehensions, AI based technology keeps evolving at a rapid pace, with the funding in AI research taking giant leaps forward. The technology has already found its cutting edge extensive applications in several warfare. We now hear almost every day about unmanned drones not just doing defense surveillance, but destroying strategic targets with jaw-dropping precision. Or for that matter, use of robots has become rather common to diffusive explosive devices of various kinds, intensity, and planted in important places to kill people. As reported by the media, ‘autonomous and self-aware robots to diminish the need for human soldiers to risk their lives.’
Google’s driverless cars also use similar AI technology offering advanced analytics-based algorithms, machine learning and deep learning processes, which could well be another game changing example in this area.
The benefits far outweigh the risks?
Be that as it may, the benefits of AI seem to far outweigh the risks, in various areas. This includes its strategic applications in the pharma industry.
This gets vindicated by the February 2016 research report of ‘Markets and Markets’ (claimed as the world’s second largest firm in publishing premium market research reports, per year), which estimated that AI market would record a turnover of around US$ 5.05 Billion by 2020, growing at a CAGR of 53.65 percent between 2015 and 2020. This market is currently dominated by the ‘Machine Learning’ technology, as it provides the computers with the ability to learn without being explicitly programmed, and are capable of updating themselves when exposed to new data.
Some of the key players operating in the artificial intelligence market are IBM Corp. (U.S.), Microsoft Corp. (U.S.), Google Inc. (U.S.), IPsoft (U.S.), FinGenius Corp. (U.K.), Rocket Fuel Inc. (U.S.), Mobileye N.V. (Israel), Kensho Technologies, Inc. (U.S.), Sentient Technologies (U.S.), and Zephyr Health (U.S.), the report revealed.
AI in pharma:
Over the last decade, AI is being increasingly used by various industries, as a key support to the strategic decision making process, in various areas of business. Understandably, in pharma its use has been rather limited, as on date. Nevertheless, there are several key domains within the pharma industry, where effective use of AI has the potential to be a critical performance enhancer. These areas include, not just in discovery research, or in clinical trials, or in sales and marketing, but also in setting the right strategic direction for the company.
However, in this article, I shall focus mainly on the application of AI in pharma marketing.
AI in pharma marketing:
Although AI is now being sparsely used, it is expected to be more widely used in pharma research and development. It also shows tremendous potential in developing creative sales and marketing strategies, with great accuracy.
So far, pharma marketing strategies are based more on the qualitative data, some traditional quantitative data, and a huge dose of marketers ‘gut feel’. It continues to happen, when the world, including India, is moving towards innovative data driven decision models. If one chooses to, now a pharma marketer also can make effective use of an abundantly available wide variety of quality data to feel the pulse of the markets, consumers and any identified issues, with great precision. Thereafter, based on these real life hard facts, the team needs to put in place for implementation, with an open and innovative mind, a creative sales and marketing game plan, to achieve the set goals.
Would that mean, a pharma marketer should necessarily be an expert in a huge volume of data analysis? I don’t guess so. ‘Machine Learning’, ‘Deep Learning’ and other analytics-based processes of AI can help them enormously to do so.
AI based analytics has now been proved to be far more reliable than any human analysis of the humongous volume of different kinds of quality data. Doing so is even beyond the capacity of any conventional computers that a marketing professional generally uses for this purpose.
The prime requirement for this purpose, therefore, is not just huge volume of data per se, but good quality of a decent volume of data, that a state of the art analytics would be able to meaningfully deliver, that is tailor made to meet the specific requirements of pharma marketers to create a cutting edge marketing strategy.
Areas of AI use in pharma – some examples:
AI will be extremely useful to arrive at the most effective strategic options available, with pros and cons, to achieve the core sales and marketing objectives of the organization, both long and short term.
It can also add immense value right at the decision making stages to determine the key ingredients of an effective strategic plan in a number of critical areas, such as:
- Arriving at the optimal product-portfolio-mix with the right expense tag attached to each brand
- Deep learning about market dynamics, customer behavior and their interplay
- Matching unmet customer needs with enhanced and differentiated value offerings – both tangible and intangible
- Effective bundling of brand offerings and associated services for each patient segment
- Selecting the right mix of communication channels, including social media, to ensure maximum productivity in reaching each category of the target audience
- Detailed strategic blueprint for each type of stakeholder engagement, along with related value offerings
- Arriving at the best possible resource-mix with the available budget
- Real-time monitoring of each strategic action steps, consistently, making quick changes on the run, if and when required
Pharma AI platforms are already available:
There are a number of AI platforms now available for the pharmaceutical companies, across the world. For example, in September 2015, by a Press Release, Eularis – a leading provider of next-generation advanced marketing analytics to the Pharma industry, announced the release of the E-VAI, the latest development in sophisticated machine learning technology delivering next-generation analytics and decision making for Pharma marketers globally.
Another recent example of AI in this area, as well, is ‘Salesforce Einstein’. It delivers advanced AI capabilities in sales, service, and marketing, and enables anyone to build AI-powered apps that get smarter with every interaction. According to Salesforce, it will enable everyone in every role and industry to use AI to be their best.
The use of AI in pharma is still in its nascent stage today. However, for a sustainable business excellence in its various domains, AI is increasingly proving to be of great relevance, now and also in the future. Sales and marketing is one such domains.
With the passage of time, both the macro and micro pharma business operating environments are changing fast, primarily driven by changing expectations of stakeholders, the public at large, and disruptive algorithmic technical innovations, based on advanced science, statistics and mathematics.
The scope to effectively utilize the full potential of advanced algorithmic technical tools, is huge. It is easier now to capture a massive volume of pharma related high quality raw data of different kinds, for tailor-made innovative analysis, with the help of AI based analytics, while creating cutting-edge strategic game plans.
Nonetheless, pharma players apparently continue to chart the same strategic frontier where there are many footsteps to follow. Many of them have restricted themselves to no more than digitally re-engineering the same overall business processes that they have been already following, since long. Just a few of them are making use of the leading edge analytics involving AI, such as ‘Machine Learning’, ‘Deep Learning’, ‘Visual Perception’, ‘Image Processing, besides many others, which can be more ‘patient-centric’ and at the same help deliver a strong business performance.
Thus, quicker adaptation, and thereafter continuous scaling up applications of high quality AI based analytics in creative pharma marketing, are not just of immense relevance today, they also bring with them the commensurate potential for sustainable excellence in financial performance of the organization, fueled by critical early mover advantage.
By: Tapan J. Ray
Disclaimer: The views/opinions expressed in this article are entirely my own, written in my individual and personal capacity. I do not represent any other person or organization for this opinion.