Peter Mansell queries some of pharma’s leading forecasters for their dos and don’ts on presenting a forecast
Factors such as increasing complexity of products and patient flows, diffuse geographies, and market uncertainties have complicated substantially the forecasting process for pharmaceuticals.
At the end of the line, though, someone will still be looking for ‘a number’—one that satisfies their particular needs and enables them to make rational decisions about the allocation of time, money, and resources.
While forecasters have to convey the margins of unpredictability and risk incorporated into those numbers, laying out scenarios that could tip the figure one way or another, end-users are unlikely to be impressed by a trawl through the theoretical undergrowth.
When it comes to presenting a forecast, then, the watchwords are brevity, clarity, and relevance, coupled with an awareness that different people in the room are going to want to hear different things.
1. Tell a consistent story
“Boil it down to simple things,” advises Robert Siegmund, director, Global Commercial Analytics at Actelion Pharmaceuticals. That means a base case, with upsides and downsides, the key assumptions underlining those cases, and a strong, clear link between the assumptions and the forecasts—in short, telling a “consistent story.”
Delving too much into advanced methods, such as Monte Carlo simulations, probability distributions, or patient flow analyses, is likely to prove counter-productive, especially as senior managers may not be too well versed in these techniques. (For more on patient flow analyses, see ‘Forecasting: How to get patient flow analysis right’, ‘Patient flow analysis and forecasting’, and ‘New challenges and techniques in forecasting’.)
Rather than “torturing” your audience with theory, Siegmund recommends turning the narrative around so that the results come upfront. Only a minority will want to trace all of the steps leading up to those outcomes. Cutting out the fat also encourages brevity, or at least a very tight focus.
The McKinsey presentation approach (seen by many as a gold standard) usually works for most senior managers, Siegmund says. When Siegmund worked for Roche, the company had a forecast management review board that would look at five to six forecasts in two to three hours. So the forecaster “usually could get by in 10 slides.”
Those 10 slides should include key assumptions such as epidemiology, pricing, market research, and preference shares, perhaps with some variability built in (e.g., using Monte Carlo analyses). Then the outputs will need to be stated in different “currencies”, such as kilograms for the supply chain, the number of patients treated for clinical, and dollars for finance.
2. Take ownership of the forecast
As Christopher Ehinger, managing director of Black Swan Analysis, points out, senior management will also want to take ownership of the forecast. As such, it represents a “transitional step” whereby numbers are put into language that can be applied to different parts of the business. The challenge, then, is to “make the numbers look easier,” Ehinger says.
It is also imperative to make the forecast as relevant as possible to a product’s market drivers. It should communicate likely risks as well as potential impact, using the forecaster’s own insights into factors such as competitive forces and price cuts, rather than just hearsay.
Risks are something senior management is especially concerned with being on top of, Ehinger adds: “They know a plan is only as good as a plan. And if it goes a bit pear-shaped, they want to know what are the biggest risks of this number not happening.” (For more on risks, see ‘Understanding uncertainty and risk in pharma forecasting’.)
Everyone needs to be convinced by the way the numbers stack up, and they should understand the risks and drivers involved, so that the ramifications are clear to each individual owner of the forecast. This “can be quite dicey,” especially with new products where there is no history to rely on.
Nor should forecasters forget that their calculations can go public, Ehinger notes. They also underpin a great deal of activity in areas such as sales, marketing, and promotion. If the forecasts are wrong, “the business loses traction very quickly” and can find it hard to regain momentum, he warns.
Although Ehinger agrees with Siegmund that “less is more” and a 10-slide presentation is optimal—framing the marketplace in two to three slides, then moving on to how the product fits into the equation, what events can be expected, etc—he differs on the order of service.
3. Humanize the forecast
“If you just talk numbers, you’re probably approaching it the wrong way,” Ehinger says. Better, he suggests, to start off with who the product is for, focusing on the need, “and then work towards the numbers,” so that management can “see the simplicity of the math.”
With a drug for Alzheimer’s, for example, the first step is to break the epidemiology down into relevant customer areas, such as mild cognitive impairment, patients who are potentially on another treatment, people showing early signs of Alzheimer’s, etc—all part of a potentially huge spectrum of need. “Your initial building blocks are [management] buy-in, effectively,” Ehinger comments. “Once these guys have fundamentally bought into what you’re looking at, then you need to progress from there and show how the numbers come together.”
Another advantage of this approach, he adds, is that it allows the forecaster to head off challenges too early in the presentation. Numbers are easy to disagree with, and in most cases there will be challenges, particularly if the audience is bringing in experience from other companies or product launches, Ehinger says. What matters is “the quality of the buy-in at the very beginning.”
4. Keep it simple
For Kevin Norell, senior vice president at Kantar Health, the biggest challenge in presenting forecasts usually revolves around presenting highly complex issues in a simple and understandable format. In oncology, for example, people “come in with a preconceived idea that there are these buckets of patients available to them, and they simply apply a share,” Norell comments.
The reality is that a forecast needs to account for interrelationships and patient flows, such as patients receiving a drug as first-line treatment, thereby rendering them ineligible in the second-line setting. Another area susceptible to received opinion is duration of therapy. While the standard regimen may be six cycles of a drug, some patients may discontinue treatment after one cycle. And in particularly severe cancers, by the time the third cycle is reached 20 to 30 percent of the patients may already have died.
Numbers that financial analysts and other commentators have already “thrown out there” fuel these preconceptions, Norell observes. Breaking them down means walking managers “through the entire cascade” so that they understand how the available patient population thins out through first line, second line, and so on. Inevitably that takes time, in a situation where brevity is at a premium.
As Norell comments, “everyone wants to skip to the answer.” If you do that, though, “immediately they’ll throw up a barrier.”So tools such as flow diagrams help to move through the process smartly without losing the audience or the detail. (For more on oncology forecasting, see ‘Biomarkers and oncology forecasting: How to hit a moving target’ and ‘The challenge of oncology forecasting’.)
5. Educate the educators
Presenters should make sure they can not only illustrate these nuances but back them up with documented data sources, Norell emphasizes. Otherwise, “it’s easy to be accused of being sort of a black box.” They also need to bear in mind that the managers they are briefing will often need to present the forecast to senior managers themselves. What went swimmingly a week ago may not carry forward so well at the next step, so “you have to kind of educate the educators” and ensure the forecast is easily explainable.
Another crucial issue for Norell is “dealing with uncertainty” in the forecast. People tend to interpret a forecast as a firm prediction, but “that’s just a fantasy,” he says. Tools such as Monte Carlo analysis can help but not many companies will use them as a basis for decision-making.
A more viable approach, Norell suggests, is to come up with a single number and then divide it into “internal and external and variables” or “variables specific to their product and variables specific to the environment.” For example, you could run a scenario assuming a single competitor to the company’s product once it hits the market, and then one assuming four competitors, “just to try and illustrate that there’s a range around these things.”
The tolerance level for these kinds of variables will likely depend on a company’s internal protocols and priorities. “Sometimes they’re saying, ‘Look, I’m feeding into a system and finance needs one number,’” Norell notes.
If a circumspect forecast demands awareness of patient flows and uncertainties that can reshape estimates according to a range of scenarios, it also needs to take into account the varying agendas within a company that will tug the forecast in one direction or another.
In Siegmund’s view, thinking about the stakeholders involved in a presentation, and whether they want to “kill or grow” the product, is a critical part of entering the room prepared. A country manager, for example, may want the forecast to be as low as possible since bonuses are tied to exceeding that estimate. A brand director at headquarters level, on the other hand, may want as high a forecast as possible so as to secure the optimal level of resources for the product.
Having these kinds of opposing forces in the room can actually be a good thing, as “you can challenge every assumption and come to a consensus,” Siegmund comments. But it is also useful to have managers present without a particular axe to grind, such as representatives of the supply chain, who “just want to know how many kilograms to make, and do I need to build one factory or two factories.”
6. Know the agendas
How much weight these various agendas will carry depends to an extent on how a company’s decision-making bodies are set up. “Quite a lot of companies use international brand teams in their strategic planning,” Siegmund points out. “They would usually involve representatives from the key countries or the key affiliates, so you should be able to get this balance between the headquarters, the brand director and the affiliates.” That applies only to forecasts for products in late Phase III or at launch, though.
With products at Phase I or II, the discussion is usually among clinical, strategic marketing, and often business development, Siegmund notes. If business development is involved and is looking at a licensing deal, they may want a more positive peak-sales number, whereas strategic marketing are likely to be more impartial “because it’s not their product.” With “any story that you want to tell, it’s good before you go into the room to think about what the different people’s agendas are, and how you can answer each of those agendas and challenges,” Siegmund says.
For Ehinger, this “push and pull” among factions will always be axiomatic when a forecaster takes the floor. “You have to really base it on fundamental things,” he says. “Then no one can really put their hand up and say, ‘Hang on, that’s not the right number of patients.’” The trick, he adds, is to “start somewhere where you get communal agreement, effectively, and from that you start boiling it down to other factors happening in the market … And then once you understand the utility of this thing, when it’s used, when it’s not going to be used, then you apply the unit number onto it.”
Nevertheless, Ehinger warns, “it’s a bit of a battle, because it’s a room that’s incredibly divided. And what they’re looking for from you is some truth, something that the whole company can hang their hat on.”
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