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.
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