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Thought leadership and innovation for the Pharmaceutical Industry

Forecasting requires more than generating a series of numbers.

By Adam Hill on Jun 11, 2015

The pharma industry relies heavily on forecasting. The art of forecasting balances the ability to account for significant market factors with simplicity and transparency, empowering the organization to make optimal business decisions. Financial groups make R&D investments based on anticipated sales for a new drug, while marketing teams base campaign tactics on them and senior management need forecasts to provide overarching direction as they make product portfolio decisions – spotting gaps, quantifying revenue potential and allocating precious resources.

This makes it all the more surprising that pharma companies have tended to treat forecasters as relatively junior players in its infrastructure. “It has been viewed as an entry-level position, an analyst using a spreadsheet,” says Arthur “Art” G. Cook, Principal at global sales and marketing firm ZS. Cook was previously Director of Global Forecasting for Syntex Pharmaceuticals and has created forecasts for more than 150 therapy areas.

Strategic decision-making

Cook believes things are changing for the better, with firms in the sector increasingly seeing forecasting’s worth. “The value it brings is to decision-making rather than being purely about number reporting,” he says. “It is a strategic function, not a nice academic exercise.”

Good forecasters need varied skills. They must be able to understand and interpret complex models and figures, but they also require the ability to communicate them simply to all the other departments in the business that need their insight. “If I’m hiring a forecaster, I’d rather have an English major and teach them math, than a math major and teach them English,” Cook insists. He is only half joking here and obviously not denigrating the skills of mathematicians, whose attention to detail is vital. His point is that an often-overlooked part of the job is explaining complex analyzes to people who have no interest in the data per se and simply want to know what things mean for their part of the business. Excel spreadsheets are a vital piece, but not the whole picture.

The second edition of Cook’s book, “Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them,” is out now and pulls together his 30-plus years’ experience in this area of the business. He looks at the history of forecasting and the lessons it offers the pharma industry, as well as key tools, methods and analytics. Unsurprisingly, it is perhaps his thoughts on the future which will be most keenly sought after.

The new challenges

With the orphan market estimated to reach $127 billion by 2018, the industry is moving into the unknown – and forecasters will have to look for new ways to successfully predict market share and adoption".

The erosion of the blockbuster model is changing the pharma marketplace – but so is the sheer number of physical places in which to do business. “One of the challenges to forecasting is globalization,” he says. For example, the BRIC states (Brazil, Russia, India and China), plus Mexico and Turkey, are important for pharma and throw up new problems. Emerging markets offer less data on which to make predictions, for one thing. Basic information on epidemiology and treatment may not be so readily available as in, say, the U.S., Europe and Japan – and also there are a range of ramifications to pharma marketing, pricing and reimbursement in different countries.

Other changes to the way pharma does business are on the horizon, and the latest edition of the book reflects this with a new chapter covering orphan drugs and biologics. With the orphan market estimated to reach $127 billion by 2018, the industry is moving into the unknown – and forecasters will have to look for new ways to successfully predict market share and adoption. The FDA granted 293 orphan drug designations last year in the US (13% up on 2013) and approved 49 orphan drugs (a 53% increase). Biologics will also change how pharma approaches its business. “The launch of biologics has reinvigorated the atmosphere and the forecasting environment,” Cook says.

The element of chance

Forecasters go out of their way to reduce the element of chance, but predicting the future is fraught with difficulty and some things simply appear out of the blue. In the forecasting sphere, these are known as ‘wild cards,’ which are not particularly likely to happen but would have a huge effect if they did. Such ‘low probability, high impact’ events include the discovery of an HIV vaccine (thus changing the game in this therapy area), the launch of a curative treatment in oncology (ditto), or even an adverse event which leads to a product withdrawal.

For these reasons, the pressure to make accurate predictions remains incredibly high. In his book, Cook outlines methodologies “which can help various stakeholders strategize efficiently, effectively and insightfully.” This is welcome when the dynamics are so complex: the physician’s perception of a product, the role of government policy, the actions of your competitors, and the effect of different treatment paradigms all come into play. Anything that might allow you accurately to work out how to stave off competition or quantify the effect of a marketing program on ROI could represent a real competitive advantage.

Tools for the job

While statistical analysis of what has happened provides a good basis for forecasting, it is clearly not the only part of the jigsaw. “It is a nice starting point, but a long way from the endpoint,” Cook goes on. For one thing, just because something has never happened before does not mean that it will never happen – and, conversely, things that have happened in the past will not necessarily recur. “You can’t remove the chance element entirely,” Cook says. “But the uncertainty is something that the forecaster should be able to factor in.”

For those who wish to do their own thing, there are any number of off-the-shelf forecasting tools that pharma can buy, ranging from the simple to the elegant. Cook believes that consultancies offer a superb service, but he is gracious enough to say that pharma is developing its own in-house forecasting expertise. “Some companies are doing very well,” he says. “They have a very well-developed, sophisticated approach. These companies tend to be characterized by having a forecasting function that is freestanding, not put under the banner of marketing or market research.” They also tend to have forecasting as director-level positions, putting the practice firmly into the strategic planning realm rather than just financial reporting.

Missing the blockbusters

What’s come as a great shock to the industry is that there aren’t that many blockbusters coming to market. A lot didn’t perform to expectations.”

Cook believes that the four major challenges are forecasts are either inaccurate, biased, too general or too detailed. “There’s always bias in an organization,” he points out. Figures are vital, but you are also dealing with people who have human emotions – and nowhere is this more apparent than in what might be termed the ‘blockbuster era’ of the early 1990s to the late 2000s.

“What’s come as a great shock to the industry is that there aren’t that many blockbusters coming to market,” Cook continues. “A lot didn’t perform to expectations.” Every company that launched a product wanted it to be a Lipitor or Viagra, but the reality was very different for most launches. But forecasters – perhaps swept away, or at least influenced, by corporate enthusiasm –  did not always see these disappointments coming, and any number of much-vaunted $1 billion products failed to hit sales that were anything like. “Forecasting was culpable,” Cook agrees. “It didn’t push back enough.” It may have been hard to disappoint colleagues, especially senior ones, who had so much invested in a new initiative. Part of this goes back to Cook’s point about forecasting having been an entry-level position, making it perhaps difficult for junior staff to buck internal trends. “The experience level put the analyst at a disadvantage,” he suggests. Whatever the reasons, this perhaps led to a lack of respect for forecasting in some quarters, although things are starting to pick up.

Predicting the future

So how often do forecasters find themselves the bearers of bad news? “All the time,” laughs Cook. This is why, while they must have the data to back up their findings, packaging their conclusions in a way that is most likely to be accepted is a key skill. Cook believes the worst mistake any forecaster can make is to justify a report in a meeting by saying: ‘The model says.’ “You need the ability to explain complex forecasts in simple terms,” he adds.

Creating accurate forecasts is challenging and, with markets becoming more complex, there might be a temptation to produce even more complex algorithms to interpret them. But this is a mistake, Cook believes. “Some companies have headed in that direction, to their chagrin,” he says. “The less communicable and understandable they are, the worse it is. That balancing point is a crucial part of forecasting.”

Instead, as the market becomes more complex, forecasters must develop what Cook calls a “logic trail,” ensuring that their numbers can still be turned into actionable insight.

Cook believes the future looks bright for forecasting, as pharma is beginning to place it in the key position it deserves. “Those painful learnings from the missing blockbusters may prove to be a blessing in the long run,” he concludes. “There is a strong upward trend.”

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ZS Principal Arthur G. Cook is author of Forecasting for the Pharmaceutical Industry: Models for New Product and In-Market Forecasting and How to Use Them, available on Amazon.com.