Joshua Centner, Industry Solutions Group Manager, Pilgrim Quality Solutions, an IQVIA company
Quality Management has traditionally been an area of manufacturing that was slow to adapt and change to technology shifts in the market. Over the past few years, enterprise Quality Management Software (QMS) systems have stepped up their game and caught up to the market by bringing functionality such as 3rd-party secure access, advanced analytics, and proactive monitoring to their portfolio stacks.
What is very exciting is looking ahead to the near future as QMS systems bring the latest concepts, theories and functionality into their solutions. This blog explores three specific areas that are changing the Quality Management Landscape.
Quality systems of the past, typically, were simply large databases that housed documents and records for regulatory purposes. Today, with increased globalization and competition, companies are trying to get their products to market more quickly. They are uncovering that a high-functioning quality system can be an asset as it is an efficient way to organize, sort, and report on the opportunities and problems within their product portfolio.
Long gone are the days of searching through records and fields to find specific tasks or elements. Companies want users to log into the system and be presented a series of metrics and tasks based on their persona so that they quickly pinpoint their next task and move to the next issue. Quality systems are now enabling personalized quality management dashboards where users can choose which metrics, tasks, and searches they need displayed to make their life much easier.
Machine Learning, in short, is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is basically giving the user options based on historical evidence. Machine Learning is now being incorporated into QMS systems to help investigators determine root causes of issues based on historic trends, as well as to propose corrective and preventive actions to alleviate the root cause.
Imagine an investigator logging into a Nonconformance/Deviation and performing a root cause analysis. But in this instance, the system has read historical data and presents the user with potential root causes based on historical trends. The user can determine if those are the appropriate root causes and selects the option that fits the incident. Upon selection, the system will then give the users options for corrective and preventive actions based on historical performance. What traditionally could have taken the user days/weeks to perform, can now be done in a matter of hours. Machine Learning is an area that will greatly impact the future of quality management systems.
While Machine Learning can be applied to events that have already occurred, think of Predictive Analytics as the crystal ball that looks into the future and helps prevent events from ever occurring. Leveraging their years’ worth of historical and market data, Predictive Analytics are being used to warn or notify people of potential threats or opportunities in their market.
Imagine being told that “There is a 90% probability that in 30 days you will have a major issue against a particular product/process based on the past trends in your system.” You now have advance notice of issues arising in the business. This may help you to prevent those issues from occurring. Where traditional quality management systems have responded reactively, this technology shift is driving manufacturing organizations to deploy their quality systems more proactively.
The Future is At Our Door
The standard engagement of these technologies is not far away as most are already in practice today. What is exciting is watching the industry transform into this future state.
IQVIA offers your organization solutions with capabilities for next-generation QMS system success. SmartSolve® EQMS is based on best-practice quality processes that reduce organizational risk, increase efficiency, improve agility, and reduce cycle times by keeping tasks on track. With SmartSolve, compliance is built-in, so the focus can be on quality.
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