Ever since the fall of the financial world in 2008, the global healthcare community has been in a unprecedented tizzy concerning its financial expenditure with very little direction towards salvation. The impact of this turn of events had been felt in the pharmaceutical industry, where the price for innovation and scientific progress was questioned. Leading pharmaceutical companies bore the brunt of the resulting promotion of non innovative/generic drugs and increasing pricing pressure for innovative drugs.
The pharmaceutical industry has responded to this crisis by being more cautious in their expenditure – R&D, promotions, sales, etc. Effective performance has been demanded from the salesmen and marketers, and this increased scrutiny has prompted an uptake in the usage of Analytics to make decisions at all the levels of business.
Analytics is the use of Data, collected with intent, from processes which define a business. In the pharmaceutical industry, the sales data (brand, geographical region, indication, line of therapy, pack size), sale rep visits, promotional expenditure, discounts offered, clinical data are some of the facets of business where Analytics capabilities have been developed and used so far. The onset of field of health informatics has enabled to analyze the demand side of the business, both for the payers and the Pharmaceutical companies. Outcomes research and real world evidence have gained significance for reimbursement decisions and formulary listings.
Although Analytics existed since the onset of the industrial revolution, the current capabilities including the big data collection and analysis has been created by the advent of information technology. Although the promise of Analytics has been realized in various other industries such as finance, retail and industrial production, the Pharma industry (except the big few) has been plagued by the limitations in know-how and essential infrastructure. Connected data processes (between manufacturer, wholesaler, retailer, healthcare providers) are an important requirement for collection of the data which is lacking ubiquitously in the industry.
The shortcomings in the Analytics capabilities of the Pharma industry has given rise to a host of third party providers who offer boutique solutions tailored to meet the needs. However these cannot replace the company’s own capabilities due to the lack of the overall corporate context in the outsourced set up.
Secondary research and analysis often have a time lag of 6-8 months which relegates its importance to the marketers. Marketing managers prefer to have fresh and dynamic inputs from the markets rather than the static insights from secondary research. Some of the key areas of applications of Analytics specific to the Sales, Marketing and Strategic planning in the Pharma industry are listed below with brief explanations
- Optimized marketing expenditure across customers and channels: Analytics offers marketing mix optimization using predictive analyses to suggest future best course of action. For example a push of a button can help run analyses that optimally allocate the total brand marketing budget across multiple internal departments within healthcare consumers such as health care provider (HCP) sales/marketing, consumer/patient marketing and managed markets contracting (rebates/allowances). This method includes adding the interdependencies of the variables and can provide ‘what if’ scenarios which offer a multidimensional view of the market.
- Optimized targeting of prescribers and the related investment decisions: The traditional approach of identifying the potential prescribers which is based on the historical data is passé. The historic data can suggest only based on historical prescription habit and cannot predict potential future leaders in prescription. Predictive Analytics can identify attributes of high profile prescribers and help spot potential leaders-with similar attributes-potential future prescribing leaders are highest productive target for sales force effectiveness. Identification of prescription patterns can also help segment the market which will help to streamline investments in the right directions.
- Optimize the marketing channels, and identification of key opinion leaders: Information about the preferences of the physicians about their mode of contact (mail, personal, e-mail) and frequency of rep visit preferred also helps to increase productivity of sales rep visits. Targeting the high value prescribers can be further improved if key opinion leaders/top influencers in the field are identified. Social media Analytics offers solutions which involve text mining tools scouring through the internet to identify individuals and groups who can have a direct/indirect impact to prescription through academic clinical research work; journal publications and conference speaking. Following the trending individuals and their works (studied through interdependent variables such as recent publications in top journals, key recent conference presentations, and key incumbent board positions) can help companies focus on the individuals with highest impact who are the most productive targets.
- Study the sentiments of the patient/provider feedback and sentiments: Social media Analytics uses text Analytics and descriptive statistics to identify key sentiments running amongst the various market segments. The interactive online initiatives through social networking sites organized by patient support groups, healthcare providers and patients offer an excellent opportunity for the marketers to understand the product performance.