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How can you improve your company outcomes and increase your return on investment (ROI)? That is the urgent story for today’s pharmaceutical commercial expenditure leaders like you. These objectives could include decreasing the time-to-market for new pharmaceuticals, enhancing digital adjacencies across the ecosystem for sales growth, and using deeper consumer data for enhanced brand loyalty, among others.

The need for you to rethink your value offer is self-evident. External commercial spend–which includes marketing, sales, and payor rebates–has been outperforming revenue growth for many pharmaceutical companies in recent years. Between 2013 and 2015, rebate spending and direct-to-consumer spending grew at a compound annual growth rate of 34 percent and 20 percent, respectively, according to a Mckinsey study, while gross sales only increased by 11 percent.

Furthermore, many of the pharmaceutical industry’s traditional sales and marketing techniques are rapidly proving unsuccessful, according to PwC, accounting for up to 25% of annual revenues on average. Despite the fact that direct-to-consumer advertising is underperforming, payers are aggressively seeking price reductions, and providers are restricting sales representatives’ access to primary care physicians, pharmacos continue to invest heavily in direct sales forces.

And, with both patients and physicians using the Internet and mobile devices to stay informed and interact, you’ll need to adjust your marketing mix quickly to ensure effective messaging.

Spend optimization with advanced data analytics

Is there a better strategy for you to take in order to reap the benefits of data analytics in terms of making better-informed decisions about pharma commercial spend? I believe the following four stages, if followed, will go a long way toward assisting you in achieving better business results:

  1. Create and manage core database: To begin, create a core database that includes all relevant sales, marketing, and payor characteristics. This database needs to be comprehensive, with data on all marketing channels, sales visits and messaging, customer relationship management, payor access, rebate levels, and so on. It must also be granular, with pertinent data segmented at the account, health care professional (HCP), and other levels.

The good news is that by repurposing existing internal databases alongside “off the shelf,” third-party data sets, you may build a critical mass database in weeks or months. Then you must expand on this foundational database in order to develop more complete data sets and gain deeper insights.

  1. Formulate and iterate hypotheses: Base your data collecting and analytics endeavour on specific working assumptions, which will need to be refined on a regular basis when new data insights become available. Keep the scope as small as possible to speed up the process of creating a usable database. So, rather than attempting to capture every single statistic, focus on obtaining the data that is absolutely necessary to answer the established business questions. Once the preliminary database is complete, test your hypothesis for various client groups to confirm or refute certain assumptions.
  1. Use hybrid data analytics: Because the performance of pharmaceutical commercial expenditure is mostly determined by sales, marketing, and payor, you should ensure that the impact measuring model you choose represents this fact. On this front, exclusive, stand-alone methodologies like mix modelling or econometrics will not provide you with the necessary knowledge. Instead of using one or the other, you should use a hybrid technique that incorporates regression analysis and test-and-control methods.

To mine structured and unstructured data at the same time, you can use modern platforms that allow you to combine numerous analytics methods, such as machine learning, natural language processing, and traditional statistical approaches.

In comparison to depending on a single strategy, using a hybrid analytics method would allow you to assess the impact of numerous variables simultaneously. It would also allow you to uncover previously ignored prospective investment possibilities.

Wrapping up:

The rapidly evolving business reality of the pharma industry requires you to revisit some of your long-held operating models and working assumptions. Embracing some of the next-generation data analytics practices.

Here comes Mego, it is a decision support system which accelerates processes and dives deeper with business insights. Unpredictable outbreaks and diseases, ever-changing regulations, need for affordable drugs, booming markets. All of these complexities result in an overwhelming pressure to outperform the market. With Mego you are equipped with prescriptive analytics and robust scenario simulations as well as analysis to optimally balance complex trade-offs. Manage logistics. Improve your performance. Drive efficiency. All with Mego.

To know more visit: https://www.m76analytics.com/

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