1. How does poor data affect quality in your industry?
Poor data is really disconnected data throughout an enterprise. When data is disconnected, it becomes difficult to connect the dots which results in extended investigations and delays in getting to decisions.
This affects quality because decisions are made based on the information at hand. If the data is in different systems or locations, it makes it very difficult to find the root cause and identify the best solution to address a problem.
2. What problems arise in this type of situation?
The most common types of problems in this situation are recurring issues. Many times, quality events happen and the solution is known because “it happens all the time”. Quality professionals may take the actions necessary to solve a problem but don’t always remedy the issue everywhere, functionally and geographically for example. When the data is disconnected, people take care of things in silos instead of holistically or globally.
3. How can business intelligence and analytics solutions be used to address quality-related challenges?
These solutions provide decision makers the information needed in real-time to make critical decisions on a product.
In most cases, the cost of poor quality is measured using the 1, 10, 100 scale; costing the company 1x the cost of manufacturing if the problem is found during the manufacturing process. If the problem is found after the product is manufactured, it could cost 10x more to fix. If the product makes it to market, it could cost a company 100x or more the original manufacturing costs to identify and correct an issue.
Analytics will allow companies to set up real-time views of quality events, so on a daily basis they have visibility to the health of their manufacturing processes which will allow them to identify problems early in the process and can take action to remedy the issues quickly and globally. The faster a decision is made based on complete global data, the more positive effect quality will have on a company’s bottom line.
4. How can TrackWise Analytics be used to progress each role in the pharmaceutical industry?
a. Quality Executives
Quality Executives will have data visibility and reliability required to understand what is happening in terms of quality within their organization. With reliable information, Quality Executives can make more informed staffing and release decisions and interact with the sales and marketing teams delivering the product to the market on time and as expected. If there is a quality related delay, they have valuable time to plan for contingencies.
b. Quality Managers
Quality Managers are at the frontline; making decisions day-to-day regarding product manufacturing. Having a real-time analysis will allow them to identify and correct any discrepancies faster. It will also allow them to identify trends so future problems can be prevented.
c. Quality Analysts
Quality Analysts are depended on by quality managers and executives to make sure only the best data is delivered to make decisions. The information they pass on is critical. They will be able to gather, identify and analyze quality data more reliably using analytics with a quicker turnaround time.
d. IT/System Owners
Before analytics, staff would request that IT help gather and analyze data in a format that would be easy to use and understandable. Providing analytical tools to end users saves valuable time by allowing quality professionals to query and analyze quality data without burdening IT resources as well as decrease reporting and decision-making time.