4 Ways Pharma Data Analytics Helps Streamline Business Decision-Making

The emergence of big data, technological advancements, and data science approaches have dramatically transformed industries like retail, finance, and travel. The Life Sciences industry is no exception. Companies in the Life Sciences industry have a high-volume of unorganized data sets they aren't aware of that contains hidden actionable insights. The life sciences industry hasn't fully adapted to new technologies but they've gotten off to a convincing start. Still, a huge number of enterprises haven't been able to decode the insights because of lack of expertise in pharma data analytics and inefficient pharma master data management. It's an undeniable fact that by leveraging big data and data analytics, pharmaceutical companies can enhance their business processes, accelerate their product development and achieve set sales objectives.

It'll be explained in this article how companies can take advantage of data analytics to boost their pharma sales in today's market.

Over the years, pharma companies have relied on the traditional ways of managing their pharma sales operations. In the past, many pharmaceutical companies would send their representatives to visit doctors personally. This exhausted the resources of the companies and lacked accuracy and actionable insights. With the traditional way of sales promotion, broad-scale production wasn't possible. Thus, the ROI generated was comparatively lower.

Today, the market is still at a fairly nascent stage and there are significant challenges. Such as poor data integration, lack of investment in talent and technology, and limited stakeholder alignment impacting this industry. However, best practices are emerging to help overcome these challenges and push pharma and life sciences analytics further on the path of rapid growth. According to a report by the McKinsey Global Institute, applying big-data strategies to make better-informed decisions could generate up to $100 billion in value annually across the US health-care system.

The report also suggests that the following can change the face of the pharma industry:

• Optimizing innovation.
• Improving the efficiency of research and clinical trials.
• Building new tools for physicians, consumers, insurers, and regulators.Why data analytics

  The ever-growing competitive drug market requires pharmaceutical companies to be nimbler to deliver patient-centric solutions that collaborate with payers, physicians, and patients. The dynamic drug market is urging pharmaceutical companies to realign their sales approaches to remain agile.

  In a survey conducted by Accenture, Life in the New Normal: The Customer Engagement Revolution1 the following was found:

  • 25% of their pharma marketing is delivered over a digital platform.
  • 87% intend to increase their use of analytics to target spending and drive improved ROI.
  • 77% of sales executives said they are already using third-party service providers to augment their sales and marketing activities.

  • By leveraging pharma CRM and pharma analytics, pharmaceutical companies can meet their cost reduction goals, master multichannel marketing, and improve their sales delivery models. Data is growing exponentially and will continue to grow over the foreseeable future.

    Designing your commercial business strategy with the use of big data and advanced analytics is a necessity. Patients, prescribers, and payers are all more informed and have a variety of information available to them. To drive a winning message to grow your brand and bring real value to patient’s lives, build a culture of data-driven decision making. Adapting digital transformation is the key to protect and grow your business. However, many pharmaceutical companies are suspicious about investing significantly in improving big-data analytical capabilities. In part, because there are few examples of peers creating a lot of value from it. Yet, investment and value creation in the big data era will take a significant portion of the company budget and it will grow in the coming years.

    Different data types like patient survey, pharma sales program, call center, sales visit, and other prescribers’ data has a deep relation to the effectiveness of companies on-going sales programs. In this scenario, pharma data analytics offers early opportunities for companies to up-sell and cross-sell. This will generate greater profits. These analytics help organizations in quick decision-making and eliminate delays in implementation because of poor decision-making.

Giselle Fernandes fernsgiselle4@gmail.com https://www.p360.com/birdzai/pharma-marketing-strategies-guide/