The route to success in the pharmaceutical sector is rapidly changing. The negotiating power of buyers and providers had dramatically increased, declining physician access is restricting the accountability of care organisations and increasingly stringent regulatory measures mean selling and marketing healthcare products has never been more difficult than it is today. This is just the tip of the iceberg.

To keep pace in such a fast-moving industry, stakeholders are being forced to deploy a variety of new tactics to maintain a competitive advantage. Some are embracing smaller drug launches to diversify and reduce sales attrition risks, while others are focusing on understanding patient needs and treatment providers’ expectations better, to reduce drug failures

>See also: Big data analytics: confidence in the cloud

Regardless of the chosen method, one thing has become crystal clear – improving operational efficiency and reducing costs is vital to counter shrinking industry profitability. While there is no one-stop solution to achieve that, pharma businesses worldwide are increasingly turning to data analytics for help.

The opportunities are endless

The opportunities for pharmaceutical companies to make use of analytics are manifold – from analysing patient demographics and medical histories to optimising drug launches, through to identifying physician behaviour and establishing their likelihood to adopt new drugs.

Yet, a recent survey by WNS DecisionPoint highlighted that of all the functions within a pharmaceutical company, it is the marketing and sales teams that use them most often. Seventy-one percent and eight-two percent of sales and marketing teams respectively use analytics either ‘extensively’ or ‘a lot.’ That’s in contrast to strategy (69%) and R&D functions (60%).

Data analytics being used so extensively in marketing and sales teams is unsurprising. Applications generally revolve around optimising sales force design and planning, as well as territory management, allowing pharma companies to work out how to improve sales and balance the workloads of their representatives.

Yet, given the significant opportunities for innovation and growth, there is still work to be done to ensure analytics is implemented more widely and evenly across the entire business.

For example, there could be great gains made if R&D teams used analytics to improve the efficiency of clinical trials by utilising data from a wider range of sources such as social media, and taking more criteria (such as genetic information) into account to make trials smaller, shorter and cheaper.

>See also: 5 ways data analytics will storm the stage in 2017

How to win with analytics

Although companies are waking up to the benefits, many are failing to extract the appropriate insights from accrued data. Below are three key steps to a successful analytics programme:

1. Identify your goals

Some organisations fall at the first hurdle. Before anything else, it’s vital to prioritise the areas in which they will deploy analytics. When this is carried out after a consideration of profitability and cash flow, as well as structural factors such as regulation, competition and supply and demand, analytics can be delivered in an efficient and timely fashion.

2. Prepare your analytics infrastructure

Just when you thought the planning was over, assessing the capability and maturity of the existing analytics model is also a crucial factor for success. Considering the strengths and weaknesses of how analytics is currently applied (if at all) allows businesses to create a properly defined strategy for the collection, ingestion and visualisation of data sets.

Furthermore, a thorough assessment of existing analytics infrastructure can ensure businesses are in a place to smoothly co-ordinate the analytics process across multiple departments.

3. Link analytics to business outcomes

Once data analytics has been integrated into a business’s infrastructure, it almost goes without saying that the insights garnered must be actively applied to inform business decisions. Embedding analytics within core business processes ensures alignment to specific business outcomes and enables measurement of the effectiveness of analytics related investments.

>See also: The 3 pillars of big data analytics potential

Analytics everywhere

Whether through a growing emphasis on healthcare in developing economies, the increasing prevalence of chronic diseases, or the promotion of preventative care by governments in developed regions, there is a big revenue generation opportunity in the industry.

The global market could be worth as much as $1.6 trillion by 2020, accessible to these pharma companies putting the appropriate strategies in place.

Analytics is an essential tool to harness available assets and circumvent existing challenges. It can help businesses take advantage of a growing revenue pool, mitigate the increasing negotiating power of buyers and stay ahead of in an industry on the brink of unprecedented change.

Sourced from Akhilesh Ayer, head – research & analytics, WNS Global Services