The modern digital era has given pharmaceutical manufacturers a multitude of tools and techniques to help optimize and streamline their operations. Predictive analytics is one of these.
Big data and analytics have given modern businesses the competitive advantage by improving key objectives such as customer acquisition, targeted campaigns, risk mitigation, product innovation, and supplier management.
The Challenges Faced by
Pharmaceutical Industries
The pharmaceutical industry is experiencing growth at a rapid rate due to an increased demand in products and services.
Ageing Population. According to the World Health Organisation, the aged population (those over 60 years old) will increase by 10 percent in the next five years, placing even greater strain on supply chains and production teams. New growth brings many new challenges with it.
Patient engagement and connection. A patient-centric approach is considered the best way to stay relevant and competitive. Research shows that pharmaceutical companies are using patient portal technology to connect with patients and to gather vital data. What they do next with this data is what could set them apart from their competitors.
Manual processes. Overburdened back-office teams, manual processes, a patchwork of unintegrated technology, and outdated systems; all of these cause frustrations, delays in delivery, and a lack of control and visibility for pharma companies. The move towards digitization is seeing more pharmaceutical industries embrace digitization in their operations. Integrated technology improves time to market, supply-demand match, workforce and resource optimization, and service and quality delivery.
Image source: mckinsey_industry_40_2016.pdf
Supply chain difficulties. The U.S. pharma industry has faced complex challenges since the global pandemic. The Asia Pactic market makes up 24.1 percent of the pharma production field, and India is responsible for 24 percent of the U.S.’s imported medicines and 31 percent of imported medicine ingredients. Closures since the pandemic is causing real challenges. China’s Life Science and Health Care Consulting Leader Andrew Yu said recently, "We see the COVID-19 outbreak, in the long run, as a catalyst for the transformation of China's healthcare system. It is imperative that ecosystem players anticipate such changes and grasp emerging opportunities." These challenges are opportunities for larger pharmaceutical enterprises to seek technology and solutions that can predict future outcomes and prepare them accordingly.
“It is imperative that ecosystem players anticipate such changes and grasp emerging opportunities.”
Andrew Yu - Life Science and Health Care Consulting Leader
The effect of the pandemic on all industries around the world, particularly pharmaceutical industries, allows a greater focus on the effective use of big data, artificial intelligence (AI) and analytics to monitor trends and develop solutions quickly and effectively.
Predictive Analytics for Today’s Decisions in Pharmaceutical Operations
Pharmaceutical analytics is not a new trend in the industry. These enterprises have used technology for some time to successfully process, analyze and contextualize information. Utilizing data-driven strategies helps organizations viably position drugs for entry into the market. Data gives pharma companies the information they need to ensure clinicians and patients are better off.
Predictive analytics leverages this data even further. Using technology to gather, sort, and process vast amounts of historical and current data, predictive analytics focuses on identifying patterns in the data. It then determines how likely it is for these patterns to reappear in the future. This is done through AI, machine learning (ML), data modeling, and more. Predictive analytics platforms give data analysts the tools they need to process data in a way that is fast, easy to use, and effective. They can then present these data-driven predictions to business leaders for better decision making.
Predictive Analytics in Pharmaceutical Operations
Predictive analysis helps pharmaceutical companies by taking the guess-work out of operations, thereby improving operations significantly. Predictive analytics can be used in everything, from improving aftermarket services to developing better products and services, from improving response times and customer experiences to ultimately staying ahead of the curve.
Predictive analytics can be applied across an entire operation - purchasing, marketing, production planning, consumer demand forecasting, supplier management, staffing, and more - with great effect.
A 2017 Society of Actuaries report on healthcare industry trends in predictive analytics revealed that over 80 percent of healthcare executives who use predictive analytics believe it will lead to a 15 - 25 percent or more of total budget savings over the next five years. An overwhelming 93 percent of healthcare executives believe that predictive analytics is vital to their business’ future success.
93% of healthcare executives believe predictive analytics is vital to their business’s future success
As competition within the pharmaceutical market increases, predictive analytics gives pharmaceutical companies the information they need ahead of time in order to improve product sales and optimize production.
The Benefits of Predictive Analytics for the Pharmaceutical Industry
Accurately Understanding Patient Needs and Consumer Demand
Pharmaceutical companies typically have decades’ worth of data from market research and expert insights, all in their efforts to understand patient domains. This information has been used by research and development (R&D) teams as well as manufacturing departments to calculate consumer needs and produce medicines accordingly.
Predictive analytics tools like SEDGE automatically empower pharmaceutical companies with compelling real-time insights on future trends. By mining historical data such as consumption density, geography, demographics, health index, patient records, etc, they are able to identify patterns and trends to accurately prepare for future needs and demands.
These predictions give manufacturers ample time to act, be it to produce the drugs according to the forecast, align their supply chain, and allocate resources timeously. This results in enhanced productivity, optimal efficiency, reduced risks, and greater speed-to-market.
Pre-empting Equipment Failure
The true cost of equipment failure can be devastating in a manufacturing environment. Predictive analysis uses stored equipment data to calculate plausible scenarios of equipment failure. This is known as predictive maintenance, and gives the production team fair warning of possible machine malfunction. This can be used for proactive maintenance.
Reduced Risk
Using advanced predictive analytics tools to recognize patterns not only prepares drug manufacturers for market opportunities, but for possible problems, shortfalls, obstacles, and challenges.
Predictive analytics tools and consultant talent automatically and immediately predicts risks, and can alert the business on a timely basis. For optimized operations and manufacturing longevity, risk mitigation is vital.
Accelerated Operations
Predictive analytics gives businesses the time and space they need to make critical decisions without being in reactive crisis mode. This creates greater agility as well as higher business velocity in operations.
Additionally, delivering drugs to the end customer at speed is becoming a key business objective for pharma companies. Predictive analytics gives pharmaceutical industries the ability to rapidly identify patterns, meet demands with greater ease, optimize manufacturing processes, and create accelerated operations across the business.
Predictive analytics tools like SEDGE speed up the drug-to-market process, reduce equipment downtime and stock outages, without
compromising patient needs
How Predictive Analytics is used in Pharma
Predictive analytics tools and talent provide pharmaceutical organizations with the competitive advantage, both financially and scientifically and removes departmental silos in the organisation providing predictions that can be used by R&D, medicinal teams and marketing staff to work towards a united outcome.
Ultimately, predictive analytics is effectively used to ensure that the right medication reaches the ideal target market at the best price, on time
Get the unfair advantage. Get accurate insight into what the future looks like
SEDGE is an innovative predictive analytics tool for the pharmaceutical industry today. Allowing employees to simply input data, the tool does the analytical predictive heavy lifting for you, with ease.
Take it one step further and utilise our expert consultation services, should your predictive analytics requirements be more complex. Whatever your data analysis needs, if you’re looking for effective, powerful predictive analytics in your business that keep you ahead of the curve, ask for SEDGE.
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