The pharmaceutical industry’s primary sources of income 30 years ago were North America and Europe. Over the last 15 years, the landscape has changed due to the growing need for novel medicines in developing countries. Asia Pacific and emerging economies increased to make up at least 25% of the total revenues for most big pharma companies between 2005 and 2015.
Data access and quality are sometimes lower in emerging nations, which has hindered forecasting attempts. Additionally, many parts of the world do not agree with valid assumptions for America and Europe.
The huge pharma business model is evolving into a smaller, more streamlined operation, which makes commercial forecast solutions essential for pharma companies. About 50% of the product and portfolio mix comprises biologics and specialty goods. Localizing research units is happening in global innovation bioclusters. Emerging markets, particularly China, are the main drivers of revenue growth.
Biomedical sciences have made remarkable advancements resulting in innovative treatments for unmet patient needs. In addition, the pharmaceutical business must contend with difficult market dynamics, ongoing patent expirations, and high costs and reimbursement. Big pharma’s principal sources of revenue include shifting from primary care to specialty pharmaceuticals and biologics, realigning the R&D footprint, expanding emerging markets, and changing strategic focus.
The typical worldwide projection cannot manage this kind and size of market-specific variance. It involves international cooperation and technological platforms that explicitly adopt global trends for regional needs.
A centrally produced forecast gives interested parties a comprehensive view of the market environment. These are frequently created by international experts who have access to large datasets and construct extensive forecast funnels founded on in-depth product knowledge. Although it’s a great starting point, in the heterogeneous product landscape of today, it’s merely the beginning.
Forecasts at the national level offer a more detailed viewpoint from regional specialists. Because they are “on the ground,” these regional affiliates frequently have a greater understanding of what is happening in their market. However, it has been challenging to understand this regional affiliate perspective.
Global team members can be required to make calls, send emails, or guide country affiliates through a laborious “forecast submission” procedure. Alternatively, local affiliates may discover that their understanding of the market differs from the international norm because it is either oversimplified or overly complex.
As a result, some create “shadow copies” of commercial forecasts using their inputs and presumptions. Global organizations may never receive these “shadow” estimates, which means important information may be missed, and teams may not be aligned on real objectives.
However, there are more effective ways for local and international teams to work together.
Glocal Forecasting Platforms In The Future
A new development in pharma forecasting is “glocal” forecasting platforms. A collaborative platform that enables customizable frameworks and real-time accessibility to the same data and insights is provided by this new kind of forecasting technology.
The global and local teams collaborate in these models to create an accurate forecast. The global team frequently provides a prediction methodology and a list of the metrics that need to be tracked consistently across all markets.
However, within that framework, affiliates can modify the forecast estimates and alter specific regional funnel elements using their local research. Teams profit from having a single source of information that is accurate globally and locally under this arrangement.
Both teams benefit from a global structure of uniformity and local insights accuracy. Local affiliates can swiftly alter those measures, for instance, if the worldwide forecast assumes a net price discount that isn’t appropriate for a local market and estimates revenues based on that assumption. In keeping with a standard worldwide structure, they can also include unique features relevant solely to their market, such as the reimbursement landscape.
Pharma businesses should seek out a system that can do the following when choosing a platform to assist “glocal” forecasting:
- Being able to quickly and effectively include company and actual data sources in the prediction
- Reduce forecast cycle time by using a straightforward user interface that both forecasting specialists and generalists can easily use.
- Permit simultaneous, real-time forecast updates from numerous users (both local and international)
- Support a range of commercial forecasting models for various goods, uses, and markets.
- Ideally, able to handle pipeline and inline goods and maintain a shared forecast foundation while allowing modification as necessary.
- Include analytics and output tools such as visual output dashboards, market event modeling, what-if scenarios, and uncertainty analysis
The ideal solution would increase forecasting accuracy and transparency while ensuring that you are utilizing the knowledge of all subject matter experts in your company.
