With the growing popularity and advantages of Data Analytics, it is nearly impossible to imagine an expanding company not utilizing these benefits. Owing to numerous sources that generate large volumes of sensitive and complex data that pharma companies deal with on a daily basis, incorporating big data analytics into their workflow provides multifold benefits.  

One of the major challenges faced in the pharma industry is reception of consistent, reliable, and well linked data and big data analytics helps structure and optimize the entire workflow right from research to drug release. With SmartInfoLogiks data analytics solutions, you can leverage these and many more benefits of Big Data for your business. 

Acceleration of drug discovery and development is one of the crucial benefits of data analytics in the pharma industry. Predictive analytics enables intelligent search across vast data sets of patents, publications, clinical trials and examination of previous results of tests. This brings forward only the relevant information and helps gain an insight into possible procedures that are most likely to yield positive results. It also helps in forecasting the drug effectiveness and more vital factors such as survival rates, possible scenarios where a treatment would be rendered ineffective and ultimately improves health outcomes for patients. 

Big Data Analytics also helps optimize and improve the efficiency and effectiveness of Costly and time consuming Clinical Trials. It assists firms to identify the appropriate patient group to participate in the trial by analyzing historical and geographical data, genetic information and also enables monitoring of patients remotely, previous clinical trial result reviews, and also helps identifying possible side effects of a trial before it is actually carried out. 

Advanced Data analytics allows pharma companies to identify underserved and untapped markets by making available to them demographic information and also social media trends. This largely improves the marketing and sales performance by utilizing the feedback received by sales teams across regions and analyzing the efficiency of sales efforts. It helps them identify their strengths and weaknesses and improvise sales and marketing strategies in the process.  

Big Data leverages data accumulated from customer feedback, social media, google searches as an early warning sign for any product safety issues for the pharma company. It also enables the firms to drill down data and gain perspective on the overall public sentiment towards their brand and products. Moreover, data analytics strategies support innovation and building of new tools for consumers, physicians, regulators etc by analyzing market trends making it the preferred strategy in the pharma industry for best results and maximum revenue.

In the pharma industry, competition is large scale and consumers have multiple options to choose from including online platforms for performing price comparisons. Data Analytics helps companies in the industry understand consumers at an individual level and helps inculcate Loyalty encouraging continuous business with the same partner. It empowers pharmacies to expand their revenue streams. 

The Pharma industry and its stakeholders are on the continuous lookout for ways to achieve a competitive edge over their counterparts. Proactive communication, immediate identification of weaknesses and solution to streamline them are the most effective resolutions for pharma companies making Big Data analytics a vital part of the process.


Smartinfologiks

As your single stop IT partner, Smartinfologiks has transformed businesses with strong and adaptable technological and digital solutions that suffice the prerequisites of today and unlock the benefits of tomorrow. Combining the various industrial expertise and cutting edge technologies, Smartinfologiks has trapped an honour of delivering reliable and scalable cross platform and enterprise software solutions for desktop, browser & mobile devices, & products that ideally suit the demands and behaviour of the end-users.