Unfortunately, in order to adopt John’s new forecasting model, pharmaceuticals would need to undergo a big cultural change. As he outlines in his piece, many organisations have ingrained bad practices when it comes to budgeting. ‘Rigging the numbers’ is particularly prevalent in the sector. In terms of company performance, it hardly seems that one year is different from the next for many of the leading pharmaceuticals. But in a sector which has clearly experienced significant change, this does not ring true. For instance, a lot of large pharma companies operating across global territories now have to share a considerable percentage of their profits with those governments.
Additionally, with therapeutic pipeline improvement and the rise of more ‘me-too’ and biosimilar drugs, the sector is becoming increasingly competitive. Companies are losing out due to patent expiries. Whilst I do not think that this is justification for game playing and sandbagging, I think it stems from the sector’s fear of failure.
Aside from missing targets, failure to achieve budget can potentially result in a loss of share price and shareholders, who are great benefactors to pharmaceuticals. Alternatively, I actually feel that there is sometimes room for failure in these organisations, as it can act as a wake-up call and instigate change. As John referenced, the Google contact lens served this purpose, and is one of many disrupting technologies challenging pharma today.
Part of the problem is that pharma companies do not put enough emphasis on contingency and scenario planning for risk and uncertainties. You would imagine if you’re in a sector with long product lead times, this would be an essential component of a company’s planning and forecasting process. For many, however, it isn’t. Indeed, having to withdraw a drug from production on a global scale is not something that can be done overnight and the costs can easily destroy any financial model.
Pharmaceuticals must also become better at managing and analysing their data in order to mitigate risks. In recent years we have seen a number of drugs being withdrawn from the market due to unexpected side effects and subsequent fatalities (Vioxx (Rofecoxib), for example). Or we’ve seen drugs proving to be less effective than initially claimed (such as Tamiflu (Oseltamivir)). I believe, if these companies had more sophisticated data management tools, these problems would have been addressed sooner, avoiding wasted investment .
But it isn’t just risks that businesses need data to detect. Forecasting processes will also allow businesses to tap into new market opportunities. With the inevitable move to more personalised medicine (and the UK government £100 million genomics funding pledge), companies will need more data to understand diseases and cures.
Whilst some pharma companies might be succeeding without forecasting now, I strongly feel that they are on borrowed time. Speed appears to be one of, if not the strongest differentiators in pharmaceuticals today. Without the tools to pre-empt risks and opportunities, these businesses are unlikely to remain competitive, let alone respond to market change before it’s too late.