Learn the evidence-based techniques to forecast sales of pharmaceuticals – Know what makes a reliable forecast and how to forecast cost-effectively – Practice with an Excel-based forecasting tool.
You will learn techniques and approaches that have been proven to work best for forecasting sales of pharmaceuticals – including pharma-specific drivers like market access, step-care, targeted therapies etc.
You will be able to challenge the forecasts others have produced for you, and produce your own forecasts in most situations.
Concepts will be explained in simple, non-mathematical terms. Concrete examples from the pharma industry are used rather than vague concepts.
You will leave with a collection of techniques and principles that you can implement easily and immediately after the course.
You will receive an Excel-based forecasting tool that integrates all the techniques taught and applied during the workshop. This ensures you leave with the real hands-on ability to use the techniques.
You will receive Gary’s book Sales Forecasting for Pharmaceuticals: An Evidence-Based Approach, which will be a valuable reference to have with you.
Who Should Attend?
Forecasters who want to build more evidence-based approaches into their forecasts.
As well as any other executive who has to produce or receive a forecast as a part of their professional role.
When to use models and when to use judgment.
When to use extrapolation and when to use ‘causal’ (e.g. promotional spend).
Whether to use a single forecasting model or more than one.
Why you should ‘divide and conquer’ when building a forecast.
Why simple approaches work best (and what we mean by ‘simple’).
The other key rules that forty years of academic research into forecasting have proven.
What is meant by an ‘epi-based forecast’.
What is meant by a ‘patient-based forecast’.
What is meant by a ‘sales-based forecast’.
Fitting market access into your forecast structure.
When to use each of the above.
A simple totally non-mathematical explanation of how extrapolation techniques differ from each other.
Which simple extrapolation techniques work best?
Which ones are built into Excel and which ones require additional software
The key idea behind conjoint analysis (the most common research technique for looking at the impact of product profile).
How to build a simple conjoint-type model yourself, without a survey for forecasting.
How and why launch order affects your market share.
How to build a simple launch order model to predict the impact of your launch order.
How and why promotional spend affects your market share.
How to build a simple promotional spend model to predict the impact of promotional spend on your market share.
How market access has different effects at different levels of your forecast.
Simple market access modeling approaches.
How co-prescription affects shares.
How ‘lines of therapy’ affect shares.
How off-label usage affects shares.
Why therapy class uptakes tend to be ‘s-shaped’.
Why brand market share uptakes tend to be ‘r-shaped’.
A simple non-mathematical explanation of how the famous Bass Model can help you predict the above.
Flow/State models (new, repeat, switch etc.) and their role in forecasting uptakes.
Compliance and continuation/persistence.
Epidemiology sources and accuracies.
Diagnosis and prescription rate sources and accuracies.
Events (which events really matter and why most forecasts are “over- evented’).
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