We all know that quality is important. Assuring quality delivers an array of benefits – from utilizing less resources, promoting customer loyalty and brand satisfaction, and of course, overall savings when things get done right the first time.
According to Gartner’s 2022 Market Guide for Quality Management Systems, "The often-repeated but seldom-followed notion that 'quality is everyone's job' is now being realized at an unprecedented scale."
The job of “quality” does not solely lie in the quality department. The quality concern extends far beyond – and to some roles and departments you may not have considered. And, with the advent of cloud-based solutions, your teams and departments can collaborate and exchange ideas on shoring up your company-wide quality initiatives. Here are some examples of how different areas of an organization can leverage data analysis to improve quality:
- Customer experience: Do you really know what your customers want? When you start to ask “how can we make the customer’s experience better?” you might find some surprising insights like this top rental provider did. Learn more in this blog: Minitab Analysis Reveals Surprising Traveler Preferences for Top Vacation Rental Provider
- Warehouse/logistics: Optimizing inventory, like most problem-solving, requires a thoughtful process and a few steps. There are ramifications for not optimizing inventory. By overproducing and maintaining high of inventory levels, products could spoil or even decay. Excess inventory not only creates costs today, it also generates hidden costs later if you need to produce more goods to replace products that sat on the shelf for too long. Learn more in this blog: 3 Steps to Prevent Backorders and Optimize Your Inventory Levels
- Product development: There is a difference between design quality and manufacturing quality. Bringing quality into the design phase will reduce waste and resources in the long run. To see design quality in action, watch this webinar: Break habits, not your products: How Signify switched materials and processing without sacrificing reliability
MAKE SURE YOUR PROCESSES ARE IN CONTROL. WATCH STATISTICAL QUALITY TOOLS IN PRACTICE
- Manufacturing: Data analysis can be put to work to find new ways to cut costs and ensure quality products are produced efficiently. Here are some examples of how semiconductor manufacturers can use statistical process control, ANOVA, and other methods to achieve quality: 4 Steps for Semiconductor Manufacturers to Improve Quality and Output
- Human resources: It can be hard to attract best candidates for a job. Find out how simple statistical analysis can help your recruiters employ a scientific approach for recruitment to target the best candidates and onboard them quickly in this blog: Minitab for HR: Analyzing Recruiting Data to Hire the Best Candidates Quickly
- Marketing: The time spent brainstorming the next best strategy can be overwhelming. You can save time and resources on strategy planning and ensure that quality ideas come to the surface when you use Minitab Workspace’s numerous visual tools, process maps, brainstorming diagrams, and forms. Read how these tools will help your teams stay focused while creating solid strategies: Using Minitab Workspace in Marketing Part 1: Save Time on Strategy Development
Quality assurance should not just be left to those certified in Lean Six Sigma or driving lean strategies. As you can see, quality should be treated as a company-wide issue and Minitab offers proven solutions that will support your organization at every level.
