Forecasting: Does Wall St know something pharma doesn't?

Andrew Tolve explores how pharma forecasters and Wall St analysts can improve their forecasts by learning from each other.

Andrew Tolve explores how pharma forecasters and Wall St analysts can improve their forecasts by learning from each other.

Which would you trust more: a pharma companys forecast produced with the benefit of internal insight but the possible bias of insider optimism or a Wall Street analysts forecast lacking some of that insider info but grounded in an external perspective?

In well-developed markets with established products, the discrepancy between Wall Street and pharma forecasts can be insignificant.

But with new products, in emerging markets, or during times of fiscal crisis, the gap often broadens.

And the wider the gap, the more it can hurt investment, impacting financial results and product innovation.

If [pharma companies] dont have the research dollars to spend, then they have to trim their ambitions, says Michael Abrams, managing partner at the strategic management firm Numerof & Associates.

And that can only slow the development and dissemination of medical progress.

The question, then, is not which you should trust but what can pharma forecasters learn from Wall Street analystsand vice versa?

Forecasting foibles

Historical success is a good thing.

It means a pharma company has proven its ability to bring products to market and market them effectively while continuing to develop the drugs of the future.

But during times of upheaval, past triumphs can lead to present oversights or prejudices.

Its difficult to recognize when the fundamentals have really changed and to acknowledge that business models and forecasting techniques must evolve, especially while youre still doing well, says Abrams.

The current economic volatilitycombined with popular discontent over the healthcare system, changing payer landscapes, diminished pipelines, and increased regulatory hurdlessignifies a major shift.

Were in a time when theres a distinctly anti-industry, anti-pharma dynamic, Abrams says.

Recognizing that that kind of situation raises the risks to the industry by creating uncertainty is something thats part of an analysts job.

Emerging markets

Some companies have tried to compensate for unknowns on the domestic front with projected growth in emerging markets.

But while strong growth in the BRIC countries may be inevitable, market access is not.

And even if a product gets through, it likely will have to make price concessions along the way.

Wall Street analysts, Abrams says, are more likely to acknowledge these uncertainties and err on the side of caution.

Moving forward, he adds, its critical that pharma companies prove the economic and clinical case for every individual product and evaluate the risks and vulnerabilities of their entire portfolios.

If we look at this gap [between Wall Street and pharma forecasts] as a proxy for the extent to which pharmaceutical companies as a group need to evolve in their own view of the marketplace, then they have some work to do, says Abrams.

Forecasting fortes

Primary market research is one of the common techniques Wall Street analysts use to forecast.

The problem with this data is that physicians often greatly overstate how frequently theyll use a new product.

Sometimes physicians cater to what a researcher wants to hear, and sometimes they simply overlook the road blocks that managed care may construct down the road, such as when a product is relegated to third-tier, for example.

If you take the physicians share estimates at face value, then youre almost automatically over-predicting what will happen once a product is approved and launched, says Todd Johnson, director of forecasting at Kantar Health.

Pharma forecasters have far more technically rigorous methods to accurately adjust for overstatements in primary market research, according to Johnson.

These include accounting for the kind of research, the size of the sample, the therapeutic area, and the profile used.

It can also mean taking into consideration cultural biases.

Japanese physicians often estimate future usage accurately for fear of being an outlier.

German physicians perform similarly, while Spanish and Italian doctors are more likely to exaggerate future usage.

You cant just use the rule of thumb that we always cut the share by 50 percent, says Johnson, because in some cases that may be too conservative and in others it may not be conservative enough.

Forecasting the entire market

Pharma forecasters also excel at forecasting the entire market, rather than just a single product, which reveals trends happening with second, third, and fourth entries.

Are they gaining steam? Is there room for another competitor?

We provide that level of granularity so you can do a sanity check and really see what products will need to be displaced to gain the kind of share youre forecasting, says Johnson.

Finally, whereas Wall Street analysts generally use sales data to forecast, good pharma forecasters combine that with epidemiological data that reveals not only whats happening currently or in recent history but also the potential of the market in the future.

You want to know how many patients could be treated as opposed to just those that are currently being treated, says Johnson.

So I think its accurate to say that we do have a more rigorous process than what you see on Wall Street.

The middle ground

Kantar Health builds unique forecasting models for its clients, which range from small to large pharma companies.

Kantars goal is to present models built from an objective third-person perspective that can be used internally to produce top-tier objective forecasts.

Johnson says that this approachmelding internal and external methods and perspectivesis critical to triangulating down to a suitable order of magnitude for a product.

Ultimately, this is about making decisions, he says.

Decisions about resources, whether to take a product to market, how many sales reps to put behind a product, how much to spend on advertisement. The more granular your forecasts, and the more well-rounded your approach, the better you can do that.

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