The words stated by the Greek philosopher Heraclitus, “the only constant in life is change”, have specific importance where long-range pharmaceutical forecasting is concerned.
It is enough to consider recent global events to determine that long-range forecasting is naturally uncertain and inaccurate. Forecasters find improved results by identifying opportunities, evaluating risks, and planning for a broad spectrum of possible future scenarios.
This article will elaborate on why long-range forecasting is an inaccurate process and look at three strategies forecasters could employ to manage these difficulties.
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Understanding long-range forecasting as inherently inaccurate
The biggest difficulty with long-range prediction is the interplay of a complicated web of variables. It is the responsibility of the forecaster to predict uncertainty.
While it is quite straightforward to produce a highly precise short-term forecast, longer-range planning makes it tougher to forecast the impacts of future changes. This section will examine a few crucial factors that considerably impact long-range forecast precision.
Greater potential for uncertainty over the longer term
The further out we need to forecast, the more likely the potential for unpredictable events to erode precision. In the event of a chronic disease such as asthma, there is little variance at the market level as patient numbers stay comparatively stable year on year.
The intricacy lies in the hardships of developing and launching new products for such diseases. Only 12% of drugs entering clinical trials have been approved by the FDA, according to a report by the Congressional Budget Office.
With studies displaying evaluated average R&D costs per new drug varying from below $1 billion to over $2 billion, forecasters have the difficult responsibility of anticipating which competitive products may enter the market and how successful they might be, besides a web of other variables.
Political and internal motivations
One more debatable factor that forecasters must be aware of is any possible internal or political motivations that might affect the precision of the forecast.
The internal stakeholders of a drug might press for an excessively optimistic forecast to secure continuing funding for their study. On the other hand, companies might be pushed by a desire to satisfy shareholders that they have a powerful pipeline for new products.
For instance, one collaborated company insisted internally on coming up with a female sexual dysfunction drug with very powerful forecasts. The product was sold to an additional company and later stopped development when it was found that it was not a viable option to bring to market.
Opinion-based data
An ultimate variable to consider is the type of data being utilized for long-range prediction and how this data has been captured.
Reliance on market research could be a limiting factor, as physicians tend to overestimate their probability of prescribing specific products. Taking into account how to achieve evidence-based instead of opinion-based data is one method to increase forecasting precision.
Three strategies for better long-range forecasting
Methodology
Selecting the correct modeling methodology is the primary step to improving long-range forecasting. J+D Forecasting advocates event-based forecasting. This allows users to model the effect of factors left out of the scope of historical data.
For instance, this may be the effect of a competitor’s product launch at an unidentified point in the future. With this method, users can easily alter main data points to comprehend the effect of a range of possible future scenarios.
Instead of concentrating on precision above anything else, forecasters must aim to present a range of possible future scenarios.
A solid model that can capture the complete range of factors affecting the forecast allows forecasters to adjust their output response to stakeholder requests. This kind of model may be utilized to illustrate the steps needed to hit a specific financial goal with a new drug launch.
Identify variability
Concentrating on variability can aid forecasters in better determining risks and opportunities. To improve long-term forecasting, the key is to start with strong data and determine the primary sources of variability.
Investing in precise data-gathering for such areas of variability aids better assumptions and comprehension of the threats and chances of a particular scenario. The next step is to run various scenarios which have the potential to capture the inherent uncertainties of the future competitive landscape, specifying the most likely, worst, and best-case results.
Clear communication
Finally, yet importantly, forecasters must also take into account how they disclose long-range forecasts to decision-makers and stakeholders. Forecasts must enable an organization to perform strategic long-term business plans with clarity and confidence.
Long-range forecasts must be as easy to use as possible. This could be achieved by filtering and presenting the main data that stakeholders require and quoting ranges instead of accurate numbers for greater precision.
This kind of presentation needs forecaster mindsets to move away from the laser focus on precision toward a broader top-level approach. Stakeholders must be able to come away with a clear knowledge of the specific upside and downside potential of the project, which could directly improve their executive decision-making processes.
Final thoughts
- The basis of the long-range prediction is a solid and transparent model which could be adapted and enhanced easily as new data is available.
- Concentrating on variability helps to determine risks and opportunities in an efficient and effective manner.
- Instead of concentrating on precision, long-range forecasters must strive to comprehend where risks and chances lie.
- Clearly communicating such risks and rewards to decision-makers empowers them to act decisively and strategically in accordance with the data available.
About J+D Forecasting
From bespoke pharmaceutical forecasting models and innovative software, to interactive training and resources, we have the solution to your forecasting needs. At J+D we work alongside Pharmaceutical Forecasters, Analysts, Business Insights Managers and Marketing Departments to create models that meet the needs of both individuals and pharmaceutical companies. We balance market complexity with easy to use yet innovative technology, underpinned with the best pharmaceutical forecasting principles.
Our clients’ needs are central to the services and solutions we create, which is why we create solutions with specific business needs in mind. J+D understand the complex challenges within both global and local forecasting, allowing us to apply these to our solutions. With our knowledge, experience and passion for innovation, we aim to inspire confidence in pharmaceutical investment decisions allowing us to shape the market alongside our clients.
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