For all the effort and investment drugs companies have put into improving business agility, the gap between vision and reality is glaring. This could be because companies have yet to transform R&D decision-making, says James Man, Kinapse.
Automation
Attempts to improve R&D agility in life sciences have not had the desired results to date, a likely result of the convoluted way companies reach portfolio decisions. Real organisational agility and improved market responsiveness means being smarter about the programmes companies take on. This comes down to their ability to prioritise according to the criteria that matter most – for example, what the market actually wants (and will continue to demand in future). Yet, too often, effective decision-making is thwarted by restrictive governance structures, functional silos and a lack of 360-degree insight at key investment points.
Strategic alignment
Fragmented decision-making, divided across different teams and governance processes, leads to protracted rounds of approvals and a loss of perspective. The first step should be to bring down such barriers and bring decision-makers across R&D into closer alignment. Having a clear framework and criteria for decision-making will help to keep everyone and everything moving in the same direction towards known goals.
Simplicity is key, for example having a single approvals and review processes per therapeutic area, then an overarching governing body. This will create a clearer line of sight, so leaders will be better able to see the competing priorities of the R&D programmes and agree on trade-offs. In time, it may be possible to perform project portfolio reviews as a continuous, in-stream activity.
Broader data access
Increased observational research and capturing real-world evidence from the growing range of external sources, including online patient communities and scientific literature, are among the possible strategies for making the patient perspective central to all decision-making.
There may be some challenges in keeping the right data flowing into the decision process – such as access to external data for certain populations. Even harnessing internal data can throw up hurdles, needing to be drawn and collated from different sources, and combined and compared in reliable and meaningful ways to support confident decision-making. But appropriate technology and process automation can help with this.
Agility in decision-making should continue right across the product lifecycle, too, to ensure that medicines continue to be of value and remain differentiated in the market long after launch, and that R&D is able to react with speed to changes in market conditions and requirements.
Bringing process efficiencies & quality priorities in line
Agility in strategic decision-making must be matched by operational agility if companies are to get products to market quickly, efficiently and reliably.
Robotic process automation, machine learning and AI technologies offer a means to complete many routine tasks more swiftly, accurately and intelligently, accelerating routine processes – as long as plans for using these tools and techniques are well-coordinated. It follows that supply/service partnerships should be aligned with any plans too. It’s all very well having a strong agenda for change internally, but if this isn’t supported by agile partner processes and innovative solutions, the potential for transformation will be compromised.
Last but not least it will be important to review approaches to risk management to ensure these aren’t an unnecessary barrier to agility. One option is to adapt processes and systems so they provide more of a positive support to the business – geared more toward what could be done, rather than what shouldn’t. This may involve giving quality teams more direct input into strategic decision-making, rather than restricting their role to compliance and fine avoidance. Certainly, a willingness to think differently is an important pre-cursor to sustainable agility.