Quality management analytics help you glean insights into ways to improve processes and business outcomes. The concept of statistical analysis is nothing new, but today, you will begin to notice a fundamental shift towards role-based quality management analytics. This blog post gives you a quick introduction to how this new paradigm of analytics in manufacturing benefits the enterprise and changes from the shop floor to the C-suite.
Role-based Analytics Contextualize Data to Improve Decision Making
Take a step back and consider how your quality management IT architecture could improve with a set of holistic software tools in place. The fact of the matter today remains that IT architecture in quality management is far too often a disjointed menagerie of disparate software "solutions" and (expensive-to-maintain) hardware platforms. As a result, your critical performance and process data become noisy over time and do not integrate well among different applications - if at all. Enterprise quality management software (EQMS) solves this issue by allowing you to gain a holistic view of your quality management system. One of the most attractive benefits of EQMS is its ability to break down walls between silos of data and allow you to begin to explore data in new ways. The downside is that this new capability can inadvertently inundate you with tidal waves of new data. As such, analyzing these data requires a role-based approach to place the right intelligence at the fingertips of the right personnel - and do this right the first time to lift total quality.
Role-based Analytics on the Shop Floor Opens Opportunities
On the shop floor, role-based analytics present operators and plant managers with a big opportunity to cross-analyze data and processes like never before. As Big Data continues to transform into a big issue in manufacturing, the ability to handle these exponentially growing data sets depends on deploying robust software tools. On the shop floor, EQMS helps by automating notification of trending issues by correlating seemingly disparate processes or events to total quality. Think of automated alerts sent to mobile devices as one example. EQMS gives you a means to correlate performance data quickly, which in the recent past was far too resource-intensive (i.e., far too expensive). As one example, consider the performance metrics of your supply chain. Today, you can correlate supplier non-conformances to data on new product introductions (NPI), or cost of goods sold (COGS), to see in real time which suppliers are allowing you to manufacture most profitably. The results of role-based analytics on the shop floor can be stark. It is not uncommon to pinpoint the root cause of "blind spots" in data to legacy IT systems, which were not visible without a holistic EQMS in place and role-based analytics to show where the problem actually begins.
What Does Role-based Quality Management Analytics Mean to Executives?
Without holistic software in place, data can literally drown your IT infrastructure and surpass your ability to analyze data sets quickly. For executives, this pain point means that you have to be able to see which data are key and which data are not germane to the issues at hand. Far too often, executives are missing critical information on how quality affects other functional areas of your company from finance to marketing. EQMS allows the C-suite to correlate and view key performance indicators (KPI) at a glance without having to perform complicated analyses just to "cleanse" data. Today, it is possible to fuse quality management KPI, NPI and COGS with data from marketing, sales and customer relations to explore data in new ways. Many of the top tier automotive companies around the world have already taken this approach and invested heavily in EQMS and advanced analytics to gain a complete, holistic, enterprise-wide view of quality management. Adopting a role-based approach to analytics gives you the opportunity to improve accountability in holistic EQMS. Giving executives an accurate, real-time snapshot of quality metrics places critical business intelligence at their fingertips. It is no longer par for the course to spend hours - if not days - collecting reports and creating spreadsheets that do not even analyze the right data. Role-based analytics can actually tell you which data are relevant if configured expertly the first time to glean the most value from EQMS. In short, role-based analytics contextualize intelligence to glean insights into exponentially expanding data. Manufacturers must understand that the Big Data phenomenon is real - and upon us all. As such, deploying EQMS and role-based analytics gives you a high-level strategy to stem the tide and gain a competitive advantage by revealing new ways to raise total quality.