Article

Find, Search, Reprint, Submit Articles For Free

The Role Of Analytics In Life Sciences Industry


Life sciences companies try to stay pace with the customer. they're moving from treatment to preventive scenarios. But are they doing enough? How can they use the vital patient information available to them to the simplest of their advantage to manage patients' health outcomes? a bit like the opposite industries, it's time that the life sciences companies adopt data analytics and leverage the insights strategically to their advantage.

Early detection of patterns and therefore the strategic intent to urge to real-world results is that the key for effective business strategies. Most decision-makers have felt the necessity to reply to the unprecedented change within the life sciences world. this alteration has been compounded by developments like transitioning sales and marketing models, greater collaboration among regulators across the world , evolving physician-patient dynamics and therefore the all-important growth avenue of emerging markets. Life sciences companies are moving from treatment to preventive scenarios and management of the patient's health outcomes.

The benefits of  data analytics in life sciences are manifested in significant areas like early detection of prescription and treatment patterns, strategizing the intent of the patient to world results and most significantly achieving the operational excellence to drive through the intellectual journey of patient centricity.

The pharma world must transform today's health system to scale back healthcare costs, improve patient outcomes and enable access to health information. this needs that organizations transform from being traditional 'pharma players' to 'health players'. the littlest change in one area features a cascading effect through the whole health system. Therefore organizations must embrace the potential of signal, detection and prediction enabled by technology.

Though there has been some adoption of analytics within the life sciences sector, there still are tons of gaps to the plugged. there's definitely a requirement for better tools and processes to urge the industry players closer to understanding their customer needs. Losing out on analytics driven insights affects the important world effectiveness of their business strategies and translating in to heavy losses in certain cases. it's time that the life sciences sector internalizes the insights generated from analytics into its basic operating model and track execution against strategy.

Every business player is cognizant of the worth of analytics, but it takes winners to tap into its commercial aspect.

Commercial analytics is all about running a business efficiently to convert insights into income and data into dollars. To drive performance, organizations must be ready to discover new data sources, apply analytics and generate insights which will be quickly translated into action.

Commercial analytics plays an important role within the life sciences industry. The ROI cycle varies significantly for patients, physicians, providers, and pharma, and every stakeholder must identify its strength and analyze commercial outcomes before investing.

The cost incurred within the development of one drug is on the brink of $350 million per company. For pharmaceutical companies, the research and development phase of each drug requires huge resources both in terms of your time and money, and hence they have to start out right.

While handling such investments, organizations must answer a couple of basic questions such as:

What is the danger of failure?
What is the ROI?
Will the drug pass all clinical phases?
How long will it fancy develop the drug?
This list are often more exhaustive, and therefore the questions are often more complex than those posed. Businesses got to work on answering them backed by facts, and this is often exactly where commercial analytics goes to play a mammoth role.

Applications of economic analytics
While implementing commercial analytics to drive customer engagement and identify cash cows, few areas must be focused upon. These include:

Customer segmentation and targeting
For pharmaceutical companies, it's important to spot physicians whose prescription patterns suit their drug portfolio. Every physician is sure to follow a pattern of prescriptions, but there must be right mapping to the physicians. Organizations got to determine the churn rate and physician lifetime for a given drug.

Patient data analysis
Data concerning drug efficacy can help pharmaceutical companies estimate the lifetime value of its product. By analyzing terabytes of patient data, companies can easily identify their future stars and matured cash cows.

Social media analytics
In a world where voicing opinions matters, organizations cannot turn a blind eye to social media. the emotions of a population cohort can reveal the bottom truths a few drug. Unbiased traction for a newly launched drug are often measured by analyzing social media, an immediate medium for understanding customer voice.

Analysis of selling channels
Every organization uses unique ways to plug its products/services, and each marketing channel has its own pros and cons. within the age of fast-paced digital marketing, are the normal channels keeping pace? Are they still relevant? If so, what's the value to the business? Answering these questions enables investors to organize channel-based go-to-market strategies.

Keywords

life sciences,data analytics in life sciences,

Nithin Raju

I am an IBM certified Enterprise Design Thinking Practitioner and as a product growth enthusiast, I love to build teams where people work together to bring the best in each other with a clear focus on customer success. Apart from work, I love experimenting with food and play chess.

Author's articles

Other articles