As pharma’s ‘golden age’ comes to a close, the new reality is startlingly clear: discovering new molecules that prove to have an effect on complicated, ever-evolving diseases — with minimum side effects — is a phenomenally expensive, risky business.
At the heart of the problem is the sustainability of the business model – few industries face such a daunting prospect as pharma companies when they lose patent protection for their best-selling innovations. Add a troubled global economy, and it’s clear to see why pharma faces an uphill battle.
The Gold to Platinum Analogy
If pharma’s ‘golden age’ is coming to a close, then perhaps we’re moving into a ‘platinum age.’ The value of gold has typically – like healthcare – existed outside normal economic cycles. Associating the industry with platinum reflects an important new reality: healthcare is no longer immune from wider, global economic downturns. But let’s also keep in mind that platinum can be more valuable than gold.
Survival Requires a New Approach to Strategic Planning
In the past, the pharmaceutical industry has been lauded for its nimbleness and dynamism. Now more than ever, it needs to reclaim that reputation. Pharma companies must change in order to take advantage of the opportunities within this new business landscape.
Amid all this uncertainty, pharma companies need to wade through the noise and steer themselves towards a steady, more foreseeable future. Perhaps more importantly: in today’s climate, pharma – like so many other sectors – needs to better equip itself to anticipate impending obstacles and reforms that require nimble maneuvers.
Historically, Little Need for Macro Forecasting
In the past, pharmaceutical companies haven’t typically had access to sophisticated healthcare forecast models. Why? Primarily a lack of demand: the pharma business model was a successful one, based on launching new blockbuster drugs to mass populations in developed markets.
There wasn’t an underlying need for a more robust macro-based forecasting model in strategic planning, so the industry generally relied on fairly simple – yet effective – models.
Global Shifts Demand a New Approach
As pharma increasingly looks towards emerging markets and niche patient populations, the need for better data and modeling is more apparent. In particular, pharma needs to quantify the impact of cost containment measures among payors around the world, whilst understanding the underlying socioeconomic trends.
It’s equally as critical to understand how the shifting dynamics of individual diseases affect the way in which we forecast market sizes, disease populations, and treatment patterns.
A Greater Need for Data Clarity
In today’s drastically changing landscape, as the drive for commercial innovation and survival intensifies, access to data on the complex, variable growth trend of healthcare expenditure is becoming critical. At the core of the emerging healthcare expenditure model lie global macro forecasts, which are key drivers of health spending.
The simplest model for forecasting health expenditure is to assume that the rate of growth this year will be the same as last year. But simple models won’t cut it in the new pharma business landscape. A successful model requires an amalgam of reliable data, proven econometric models, and expert analysis.
Quantitative Data Needs to Take Centre Stage
While year-on-year historical data has been used for short-term (one-year) forecasting, it isn’t effective for medium-to-long term forecasts, as it doesn’t capture the impacts of macroeconomic factors on health spending.
To accurately forecast growth trends in healthcare and pharma markets, macro values need to take a more central role in the modeling process. A rigorous econometric approach provides a far sharper analysis of the true market opportunity.
Fusing Quantitative and Qualitative is Critical
While quantitative data provides a solid foundation, the pharma landscape is prone to rapid change, through scientific innovation and shifts in policy. A truly successful strategic model needs to factor in both quantitative and qualitative factors.
It is precisely in the area of qualitative analysis that forecasts so frequently fall short. If these developments are ignored, there are huge gaps in the forecasts that don’t reflect the critical drivers impacting the industry – just think of healthcare insurance expansion in China, major price cuts in Southern Europe, and the expansion of health technology assessments across almost all markets.
By integrating quantitative and qualitative information, pharmaceutical companies are better equipped to anticipate how complex, inter-relating factors may impact their businesses.
On the one hand, we are in a time of great political and economic turmoil. But on the other hand, it’s also a time of dramatically shifting scientific developments. If these two forces are successfully harnessed into a strategic business model, the “platinum age” of pharma really can become a time of high growth.
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The content of this post is taken from our complimentary eBook Healthcare Forecasting 2.0 — How Can Pharma Successfully Harness New Strategic Planning Models?