Many people will recall the famous Jamaican bobsleigh team which took part in the Calgary Winter Olympics of 1988. They came to the world's attention by competing and doing surprisingly well in an event for which their country was on the surface ill-equipped to prepare them for.

As well as providing fodder for an entertaining and life-affirming Walt Disney movie Cool Runnings the tale provides a useful metaphor for those setting out to compete in the pharmaceutical industry. With far too many new products appearing to be sliding down a slippery slope in an out-of-control fashion, how can we ensure that we have the best chance of winning a place on the commercial podium?

The questions you would put to an R&D pharmaceutical director can be likened to those you would put to a manager of an Olympic team:

• Are you competing in the events you have the best chance ofwinning?  
• Do you know what the finish line looks like?  
• Have you clearly defined what you need to win?  
• Have you been selecting the right candidates from the outset?

Pharmaceutical companies invest heavily in analytical tools to ensure that the fruits of their research meet critical clinical standards, yet when it comes to decisions that will ultimately determine the success or failure of their products, they often rely on underpowered research, unsubstantiated 'management judgement' or anecdote.

The result is that companies fail to maximise their performance potential. They occasionally get lucky, like the Jamaican bobsleigh team, but most of the time the race will be won by those who are best-placed and resourced to win in that event (the Swiss, the Canadians, etc). Inconsistent results mean that the profits made on the lucky few are wiped out by the costs of failure of the many.

The pharma industry cannot afford to just leave commercial decision-making to those who have presided over success in the past. Nor can they afford to trust market size to help them create a financial if not true winner. Decision-makers must be provided with the tools they need to practice a more exact science that actually models the formula for success. Experienced management is just the first element of that formula.

To many people, marketing is an 'art' reliant on creative flair to achieve success.

At an operational level, you could argue this is true, particularly with communication, but at the strategy development stage, relying on instinct and creativity can result in disaster and is unlikely to deliver consistent success.

Too many marketers start by making a decision, and then undertaking research to justify that decision. If the research does not support the decision, all too often it is sidelined or ignored.

Which tools can help companies address this issue? What disciplines can decision-makers in pharma companies adopt to provide robust evidence to support critical decisions regarding product development positioning, communication strategies and resource allocation?

A scientific approach can provide effective decision support in identifying which therapy areas are likely to give the best return on investment in the long-run.

Such an approach is already accepted in the R&D laboratory for identifying the type of molecular binding most likely to deliver results, but it can work just as well in supporting marketing decisions, ensuring that both disciplines set off on the right track, work towards the same end, and cross the finish line together.

Biostatistics is used to develop clinical models based on probable biological outcomes. It is a standard approach to conducting clinical trials. Econometrics follows the same basic principle, but instead of predicting biological outcomes, it predicts financial outcomes (ROI, NPV).

The rationale is the same: by applying multivariate analysis we can quantify the impact of different factors on our dependent variable, whether that is a clinical or financial end-point.

If it is so near our grasp, why is it not more commonly used to identify and prioritise Critical Success Factors (CSFs) for directing R&D and marketing?

Understanding CSFs in commercial decision-making requires us to be able to measure more intangible variables than the safety and tolerability requirements we are accustomed to in clinical research.

We know that companies which develop new molecules in areas where they already have sales relationships with the relevant customers do better but how much better? Enough to justify not researching NMEs in areas that you do not have a sales presence?  

The challenge, therefore, is to identify what the CSFs are and what is their relative impact on the expected commercial return of investing in different areas. The problem management is faced with is ow to count what really counts  

This is one of the most difficult judgements to be made in pharma management, and is often based not on evidence, but rather 'gut instinct'. As Albert Einstein said: "Everything that can be counted does not necessarily count, everything that counts cannot necessarily be counted."

In fact there is no one approach that enables us to identify the relative importance of the different 'Success Factors' in order to identify which are 'Critical'. Different outputs require different market research techniques and modelling tools. Let's have a look at some of these.

Which events should we compete in?

As in sport, there can be qualifiers just to get into the race. To get to the start line, there are some minimum requirements, both clinical and commercial, and expending effort trying to win a race that you are not even qualified to start in is clearly a waste of effort.

Both clinical and commercial baselines are based on the relevant stakeholder requirements and needs. This might be a question of efficacy or safety, but might equally be based on price or a specific clinician-dictated need, such as dosing or delivery methods.

Understanding the Expected Commercial Value (ECV) of investing in researching and developing NMEs in different therapy areas requires us to quantify the internal and external Critical Success Factors, and evaluate our ability and relative capacity to fullfil them.

To do this accurately we need to build a picture of the market segment-by-segment, even pre-marketing, so that the ECV of a therapy area becomes the sum of the ECVs of each segment.

The ECV of each segment is a function of the segment's expected sales potential (£), the likelihood (%) of successfully bringing product to market, and the level of penetration (%) that can be expected if you do.

To be able to accurately estimate these figures, we need to know what the finish line looks like, to understand what we need to do to successfully complete, and even win, the race.

What does the finish line look like?

Calculating sales potential requires market research into customer purchasing frequency and willingness to pay for new products that better meet their needs.

Understanding prescribing triggers is key to knowing what you have to do to satisfy those triggers, and qualitative research can help identify the factors which are relevant to the marketplace in other words, what's driving the decision-making.

Those triggers can range from the level of sustained efficacy, through safety and tolerability, from compliance to price. Some will be more important to one market segment than to another, so simply knowing what these triggers are is not enough: the task is to weight their importance to your success, so that you know what level of performance will deliver what Expected Commercial Value (ECV).

Quantitative research techniques, such as online surveys using conjoint trade-off analysis, can provide a specific value of meeting each of these different customer needs.

The aim of this analysis is to identify the 'key' prescribing triggers for each segment. The word 'key is overused, but in this context it means those drivers which will have a statistically significant impact on prescribing behaviour under test conditions. In other words, we can know how much impact each trigger is likely to have on each segment's prescribing propensity.

The output is a Target Product Profile (TPP) that specifies the performance levels the market requires in each CSF to enter the race, and win the race.  

Can we win the race?

Getting to the starting line is one thing - winning the race is quite another, but no one enters the market to be an also-ran. So how can we measure whether we have a good chance of winning before the starting gun is fired?

The TPP provides a map from which we can work backward to identify performance levels most feasible for the company to achieve relative to the competition - which brings us to the expected penetration we can achieve in each segment within each therapy area.

It's important to realise here that winning is not necessarily the same thing as setting records. A combination of the market, your capabilities and/or existing technologies at the right price may mean the 'perfect' product is not immediately achievable; the final product might not be the best that can be produced - this may have to wait until cheaper technology or changing market conditions.

Think about Roger Bannister's four-minute mile: many doctors said that the human body could not do this, and those winning races before then were doing so with much slower times. Nowadays, a four-minuter would be an also-ran, well out of the medals. In other words, you only have to evaluate your capacity to win the commercial race as it stands when you are running it.

The percentage penetration figure will capture both commercial and clinical viability and risk. To calculate these values accurately, we need to use historical trend analysis of past products (our own and competitors') with similar market segments.

By using regression analysis of the clinical and commercial factors behind the percentage market penetration achieved and ROI, we are able to quantify the relative impact of each factor. Regression analysis is not the same as simply looking at past trends. It looks not so much at what happened, but why. This identifies the drivers behind trends that can be used to forecast how the market, and thus your TPP, will evolve in the future.

By taking correlations, based on past prescribing triggers identified from our historical driver analysis and the current ones identified via the conjoint analysis, we can provide further validation of the company's ability - or not - to be first past the post.

By then evaluating the company's relative performance in each CSF, we can start to model the percentage market penetration for today and in the future. Of course, conjoint analysis conclusions based on today's customers and regression analysis of what drove sales with customers in the past, won't always tally. If this happens, it demonstrates that there has been a structural shift in the market - perhaps through technological change, political priorities, or consumer attitudes moving.

Whatever the reason, it will be important to identify what is driving the structural shift and then model how that might impact on the segment penetration that could be expected in the future  Only then can you have an accurate long-term forecast of what will happen when the starting gun is fired in the race to meet customer needs.

Working through these processes means you end up with:

• A Target Poduct Profile (TPP)
• An understanding of whether this is a race we want to be in
• What we need to do to enter and to win
• How past performance market and company can guide us in workingtowards winning the race, as it will be when we run it

Once the therapy areas offering the greatest Expected Commercial Value (ECV) have been identified and assessed for strategic alignment, the Target Product Profile (TPP) can be used as the map for directing new R&D initiatives towards commercial goals.

Although there is a place for instinct and flair in making these sorts of decisions, they should be made against the background of sound, robust information and analysis.

This doesn't mean analysis will stifle innovation and creativity. Returning for a moment to the Jamaican bobsleigh team: on the surface it seemed a silly idea, but level-headed analysis might have been less sceptical.

Much like new product development, a bobsleigh race is won in the initial sprint at the top of the track (three-quarters of the team are passengers from that moment on). It wasn't really about ice at all, but sprinting. And the guys from Jamaica were good at that.