As a society, we’ve gotten used to the convenience of e‑commerce. We can buy almost anything we want online and find it at the lowest cost possible. We’ve no sooner made our purchase than we expect the vendor to deliver it immediately.\r\nThis expectation of instant fulfillment has moved from consumer goods to the B2B world, too. Whether a company makes beverages or electronics, pharmaceuticals or car windshields, manufacturers across industries are feeling the pressure to meet ever-increasing customer satisfaction benchmarks.\r\n \r\nBut traditional business models say you can’t have it all. Lower cost, faster delivery, and better products are mutually exclusive goals, right?\r\n \r\nThey don’t have to be—if you re-imagine quality.\r\n Meeting challenges and customer demands\r\nToday’s manufacturers face challenges and frustrations as they compete to fulfill the demands of customers who are used to having technology at their fingertips—and who expect more and more for less and less.\r\n \r\nAs a manufacturer, you can take two important steps to increase customer satisfaction while improving your bottom line: \r\nEnsure that the product you put in your customers’ hands will perform as expected. This is perhaps the easiest way to ensure demand fulfillment.\r\n Use consistent, repeatable manufacturing processes. There are many ways to reduce cost, but a consistent manufacturing process is the first step in reducing yield loss from scrap and rework, limiting equipment downtime, and improving resource utilization.\r\nCan quality really be at the heart of these solutions? Absolutely!\r\n \r\nIf your organization is like many, you probably think of quality as the last checkbox to be marked. Instead, think about it as a factor in every aspect of the process.\r\n \r\nYou’re mostly likely already collecting quality data at multiple points in your process. With a solid Quality Intelligence solution, you can get an aggregated, end-to-end view of production lines across the enterprise. This high-level view means you can not only stop a line when you detect a problem but also gain insight that drives continuous transformation in quality, process, and operations.\r\n Get more from your quality data\r\nThe first step in getting more from your quality data is to take the time to really examine your processes. Don’t just look at products that are flagged as out of spec. Instead, use statistical process control (SPC) trending rules judiciously to examine all your data and spot important trends over time.\r\n \r\nFor example, if you’re using a control chart with a normal distribution, look for:\r\na single point beyond the control limit, which shows large shifts;six consecutive points that are steadily increasing or decreasing, which shows strong trends; or15 or more consecutive points that are within 1 standard deviation of the control line, which shows a decrease in process variation.\r\nThen, in addition to tracking the performance of individual processes, use your data for comparative analyses. How do all your lines compare to each other? Is there a difference between operators, shifts, departments, lines?\r\n \r\nYou need both real-time and historic visibility into your processes to avoid problems—and to replicate what works well throughout the enterprise.\r\n \r\nIf your quality system can’t provide this information, you’re missing a big piece of the quality picture.