The manufacturing sector remains a sensitive area in business. With the advanced technology and mechanisms to achieve different forms of production, manufacturing industries continue to embrace the use of big data in the production process. The analytics feature characteristic of big data increases efficiency by increasing yields and reducing the costs in the manufacturing process.

Manufacturers are embracing data analytics to boost profits and improve productivity. Through integrated tools, manufacturers are capable of feeding the database with various data for in-depth analyzing for production efficiency, removal of waste material, scheduling of employees and overall performance monitoring, security measurements on the production floor, among other benefits that enable seamless execution of manufacturing processes and predictions of the market tendencies. Let us look at how big data improves efficiency in the biopharmaceutical manufacturing industry

Increased accuracy in yield and quality in production    

The purity of products in the biopharmaceuticals is critical. Most of the time the 100% purity levels are not achievable due to the vast variables to consider. However, the advanced data analytics enable the manufacturer to successfully track the different parameters concerned with production, hence ensuring purity levels are high and constant in line with compliance regulations.

A better forecast of production and demand    

Using the predictive data analytics feature, the manufacturers can get better estimates on their future sales taking into perspective the last sales.  The feature enables pharmaceuticals to increase the efficiency in production by knowing just what amount to produce according to demand to avoid wastage of resources.

Integration of data analytics into six sigma    

With the inclusion of data analytics into six sigma, production greatly improves, and the workflow made easier. With integration of DMAIC (define, measure, analyze, improve and control) mechanism of six sigma, the overall production process is more customer based than ever.


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