Using Data-Driven Insights and Analytics to Drive Decision Making

Blog-DATA DRIVEN-eye for Pharma
 
How data-driven insights can be used to effectively drive decision making within price and access.
How great would it be to be able to predict the future? Successful decision making ultimately depends on our ability to predict the future outcomes of today’s actions. If we could go back in time or foresee the future, we could remove uncertainty and clearly see the success or failure of our decisions with the security of knowing that our present efforts were on the right track.
Consider the example of booking flights for your family summer vacation: how do you make the right decision? How do you best optimize your time and money efficiently? If you could foresee the future, you’d be able to see the ideal time to purchase your ticket at the lowest price, the best time to travel and then modify your decision in the present day accordingly.
Predicting future trends
In business, the closest alternative we have to predicting the future are trends and insights. Until recently, decision making often came down to instinct. However, a gut feeling is not a good predictor and certainly not a great way of managing pricing decisions. Actions based on instinct are often subjective and as such a gamble or chance based decision. There having been plenty of strategists that have fallen flat on their faces because their instinct let them down at a crucial point.  The recent case of Turing, where the CEO raised the price of Daraprim, from $13.50 per pill to $750 per pill highlights the demand for pharmaceutical pricing strategies to be defendable and sustainable.
Big data is a term used to describe the combination of large datasets and advanced analytics. Predictive analytics encompasses a variety of statistical techniques from predictive modelling, machine learning and data mining that analyze current and historical facts to spot emerging trends. By applying these concepts, we have the closest thing yet to a crystal ball which can help us to forecast and predict trends such as payer reaction to new market entries, willingness to pay for a certain indication and how demand impacts the price and access conditions of a product. Whether we choose to follow or ignore them, common patterns in practices, payer behavior and pricing trends can help drive and support decision making.
Data-driven insights
Data-driven insights and predictive analytics are already being leveraged across other industries, taking away some of the guesswork involved in decision making. Consumer-goods companies used to depend upon channel demands and gut feel to determine price, promotions, and stock levels. These companies now use predictive analytics to refine decision making. Tesco systematically integrates analytics and consumer insights from its Clubcard loyalty program data to build a sustainable competitive advantage by targeting and segmenting customers.1
Uber’s dynamic pricing strategy is another great example of how analytics are used to adjust pricing strategies by setting a price that balances supply and demand. Arguably, pricing strategies for medicines is more complex than the examples listed above due to multi-dimensional factors, however, spotting trends from the past can help us anticipate the future. Data such as price achieved, access conditions/restrictions, clinical and economic arguments, population size, comparators, reference rules etc. can be used to build up a detailed multi-dimensional view to guide price and access decision-making more accurately. Data-driven predictive analysis drives awareness of the factors which could influence outcomes, giving us the opportunity to bring them under our control.
I believe that there is a clear place for data-driven insights and analytics within pricing and access for pharma.  We might not yet have the technology to actually see into the future or go back into time, but we do now have the ability to remove some of the guesswork and replace it with factual, data-driven insights. In my experience, however, the best predictions occur when we combine multi-dimensional insights with solid industry experience.
Find out more at:
Global Pricing Innovations
Eye for Pharma
References
1.http://www.mckinsey.com/insights/business_technology/big_data_the_next_f…
 

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