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Big Data Trends Urge Life Sciences Executives to Modernize Key Business Functions

A recent ransomware attack on a global raw materials production company forced the shutdown of its IT network systems. Many plants were isolated to prevent further infection, which obstructed critical interconnectivity and communication through the company’s network. Operations were severely crippled as production was either stopped or shifted to manual mode where possible. While these circumstances were due to a security breach, many life sciences industry companies choose to operate in a similar fashion by using outdated or poorly integrated technologies.

A new phase of the Industrial Revolution is ushering in new technologies and modernized operational strategies that no life sciences industry executive can afford to ignore. Viewing the industry through a wider lens reveals business opportunities that will come from interconnectivity and access to more data and information. 

#1 Quality Management

A long time trend in regulated product development was companies focused on satisfying compliance requirements, but not pursuing quality. This is derived from a sense of urgency regulated companies have to get products on the market fast due to intense competition.

This framework of regulatory approval is misaligned and no longer sustainable, if it ever was. Compliance with regulations does not ensure quality. Digital manufacturing and quality management solutions are available; there is no reason for quality gaps to exist anywhere in regulated products.

Implementing digital quality management technology is rapidly becoming the differentiating factor in developing regulated products. A digital quality management system (QMS) seamlessly integrates all quality processes, which unifies all departments and stakeholders. More confidence in your audit preparation accelerates compliance because there are fewer deviations and delays due to nonconformance issues, which ultimately moves products to market faster.

#2 Data Analytics and Reporting

At the heart of the digital transformation is data, or more specifically, greater access to actionable data. This can be a valuable resource to companies in identifying trends and making business decisions. Emerging technologies are generating enormous amounts of data, but it is not all equally useful for every organization. The data needs to be collected and effectively analyzed before it can offer any measurable value.

In order for regulated companies to create the number and types of reports they need, they rely heavily on data being up-to-date, comprehensive and accurate. Companies can get in over their heads attempting to employ traditional methods of manually reviewing, sorting and analyzing data. Implementing digital data analytics and reporting is the only way to prevent this aspect of developing regulated products from becoming a costly bottleneck.   

According to PricewaterhouseCoopers’ (PwC) 2016 Global Industry 4.0 survey, 69 percent of over 2,000 participants cite increasing in-house data analytics technology and skill levels as the single biggest improvement route to boost data analytics capabilities.

#3 Automate Production Processes

Technology has often been viewed as being a threat to humans in the workplace. Inevitably, many of the repetitive tasks currently performed by employees will become automated, which means fewer employees will be needed to perform those tasks. But that’s the scenario of the current workflow structure for most organizations.

Manufacturers have long expressed a desire to have their highly skilled staff devote more time to value-added tasks. In regulated sectors, staff commonly perform repetitive tasks necessary to ensure compliance with procedural guidelines. However, process errors and delays occur more often when employees divide their time across multiple tasks.

In a nutshell, automated processes, such as data collection, transcription, record management and document control, reduce errors and increase quality and productivity. More efficient production processes free up employees for more business-critical tasks, which leads to increased output, new market opportunities and business growth.

#4 Document Control and Collaboration

Wherever regulated products are developed, there will be documents — manufacturing documents, production records, batch records, history records, etc. Efficient and error-free product development is highly dependent on effective collaboration and document management. This is a tall order when organizations have offices scattered across the globe.

Different offices using their own IT systems, data centers and enterprise management tools is a recipe for data silos and errors due to stakeholders using varying versions of documents. Avoiding costly setbacks caused by miscommunication and outdated information is best achieved with interconnected technology that enables real-time collaboration.

#5 Security Measures

External cyberattacks are the leading cause of security breaches. However, companies that have detected a cyberattack or experienced a data breach may not realize that their employees could be partly to blame. Employees who lack security training and the right kind of preventive technology can jeopardize your company’s cybersecurity posture.Some employee-related vulnerabilities include:

  • Revealing login credentials through an email phishing scam.
  • Sending sensitive files to the wrong email address.
  • Clicking on a link or opening a document emailed from an unknown sender.
  • Connecting an infected mobile device to the company’s network.
  • Inserting a corrupted portable storage device into a network-connected computer.

Securing your company’s IT systems, data and intellectual property involves implementing digital quality and manufacturing solutions that include the latest cybersecurity features.

#6 Data Management

Regulated companies are tightly held to stringent guidelines for managing data. Outdated, missing or corrupted data is extremely difficult, if not impossible, to bring into compliance with regulatory data integrity requirements.

Data integrity compliance must begin with executive management. An executive needs to sponsor initiatives for obtaining the necessary resources; establishing organizational data management processes; and setting policies for properly reporting data integrity issues.

Technology constantly changes, which in turn changes the way data needs to be handled, stored, backed up and retrieved. To overcome the challenges of data integrity compliance, more life sciences companies are moving their applications and data to a cloud environment. Cloud service providers are better equipped to preserve the quality and integrity of data, as well as meet the regulatory guidelines for data security and disaster recovery.

Life sciences industries are becoming more technology-driven. In line with this transformation, many companies need to restructure their business models to account for rapidly advancing technologies, changes in workforce management, more diverse competition and a constantly changing compliance landscape.

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