Avoiding the pitfalls in pharma forecasting
The workshops relied on insight from more than two dozen industry participants, but one approached forecasting from a sales and marketing perspective, while the other took a forecaster’s view.
By on May 29, 2007The workshops relied on insight from more than two dozen industry participants, but one approached forecasting from a sales and marketing perspective, while the other took a forecaster's view. Not surprisingly, the two teams viewed the pitfalls of forecasting quite differently.
Pitfalls in pharma forecasting
After brainstorming and voting, the sales and marketing group determined that the top pitfall of pharma forecasting is a lack of communication and alignment across the company, followed by the lack of a shared vision for the brand or product. Other pitfalls identified by the group included (in rank order): a lack of governance and formal review of forecasts, use of a forecaster with the wrong or inadequate set of skills and a lack of understanding by forecasters of sales people, coupled with sales people's inadequate understanding of the forecasts.
According to the group, additional pitfalls plague pharma forecasting, including a lack of understanding of forecast objectives and decisions, conservatism at the affiliate level, poor use of product profiles to drive accurate forecast ranges, an over-reliance on and comfort with certain data sets and a lack of reflection of the true potential of a brand or product.
Participants in the forecaster's workshop, however, cited the lack of processes to incorporate senior management input as the top pitfall of pharma forecasting, followed by the tendency of senior management to have their own forecast number already in mind. Other pitfalls identified by the group included (in rank order): lack of ownership of the forecast, lots of numbers without a story, the use of different forecast types and versions and limited experience of a forecaster in a therapeutic area.
According to the forecaster's group, other significant pitfalls include the lack of pushback by forecasters on demands, assumptions and timelines, overly analytical forecasters, a lack of process for output and communication and the lack of incorporation of market risk and probabilities.
Best practice themes
There are, according to Alec Finney, Global Forecasting, Astra-Zeneca and Stephanie Hall of Creative Marketing Measures, four key factors of forecasting best practice: the forecaster, the process, the forecast itself and organizational stakeholders. These key factors are interdependent and drive the forecasting process in what the pair call a wheel of forecasting model that relies heavily on the knowledge and skills of the forecaster, coupled with a strong focus on consultation, communication and alignment among stakeholders.
Workshop participants identified some key best practice themes. First, pharmas must work to enhance forecasters's collaboration and communication skill sets to maximize collaboration and consultation with stakeholders, allow forecasters to constructively challenge entrenched organizational thinking and to present complex information in a clear, confident and logical way.
It is important, they say, to map out a clear process for communicating, consulting, presenting and reviewing a company's forecasts with all related functions.
Second, the groups say forecasters must tell stakeholders the story to avoid death by numbers. They suggest that forecasters must first explain all assumptions and then, in a logical flow, present forecast numbers.
Forecasters should challenge stakeholders to discuss the assumptions and encourage them not to tinker with the fine detail of the numbers. But if there is a magic number in the heads of senior management, Hall advises, it is better to know it sooner rather than later and understand why it is important.
The groups say forecasters also must incorporate market risk and probabilities within forecasts to reflect the changing external environment and differing management views of a product's potential.
Classic forecasting errors
Hall says classic forecasting errors include simple mistakes, such as modeling errors, out of date information and unchecked sourcing data. But other forecasting errors stem from communication and buy-in missteps, she explains. Failure to secure sign-off by operational stakeholders, over-promising and the use of key assumptions without organizational agreement are all potential pitfalls.
Internal bias also can lead to errors, she says. Forecasters and management must consider differences between internal aspirations and the available market, external forces such as competitor responses, disruptive technologies and events, and supply chain dynamics.
Other common mistakes include: not basing key assumptions on empirical evidence, not appreciating key sensitivities to the forecast, not linking inter-dependent budgets and assuming historic trends will continue, Hall says.
Past performance is not a guide to future performance, she cautions. Although financial firms are legally required to make such statements to prospective investors, Hall says, trend assumptions presented to senior management rarely include such cautions.
Improving the quality of forecasts
To improve the quality of forecasts, Hall says, forecasters must ask the right people the right questions. It is important, she says, to understand the purpose of the forecast and the needs and priorities of the stakeholders involved.
Other important aspects are the time horizon and the scope of the forecast, she says. Is it an operational or strategic forecast? What resources are available data, market research, software tools, or organizational support and experience?
Successful forecasters, she says, must be leaders within their organizations. They must help to alert the organization to future opportunities and threats and work to help the organization improve ROI metrics and support decision making.
Pat LaPointe of marketingnpv.com and the author of Marketing by Dashboard Light: How to get more insight, foresight and accountability from your marketing investments, suggests five ways to achieve better forecasts. First, he says, be specific. Determine precisely what units, measures, and variables are needed, as well as the necessary degree of accuracy.
Next, be structured, LaPointe says. Remove personal biases and filters, double and triple check all assumptions and formulas and audit and evaluate your logic and assumptions. Third, he recommends that forecasters be quantitative with or without data. He suggests trying a variety of quantitative forecasting methods and cross-referencing with experiential judgment.
LaPointe says forecasts also can be improved by being more than quantitative and finding causal factors. He recommends convening a cross-functional expert panel to identify such factors and understand why they are happening.
There is no power in a forecast for which people can'st understand the logic and process, he stresses.
In the end, Hall says, the ultimate forecaster is:
a visionary, able to see into the future,
a guru of products and markets and analysis and modeling,
a warrior, able to take on and challenge existing paradigms and sacred cows, and
a story teller and alchemist, able to create coherence and forecasting gold from the disparate inputs of marketing, sales and executive management.
To learn more about pharma forecasting, make plans to attend eyeforpharma's Pharma Forecasting Excellence Summit USA in Boston, October 24-26th. To register or to learn more, please visit www.eyeforpharma.com/forecastingusa07 .
Stephanie Hall can be reached at: steph@creativemarketingmeasures.com