That involves several important steps, starting with a statement of why you need process improvement and what you hope to achieve. To successfully merge Lean Six Sigma with data analytics, it’s important to create a culture of continuous process improvement. Creating a Culture of Continuous Improvement Once a detailed picture of how a process works is created, it’s then possible to determine where errors are being made and what steps do not add value to the final product. Value Stream Mapping – This Lean tool involves visually mapping out a process in detail, something data analytics can help enormously. Another core metric mentioned by Forbes, called Perfect Order Performance, measures how often a company produces a product that meets customer expectations and is delivered on time. The end goal is to reduce errors, meet schedule deadlines and improve quality. Here are two that can help make use of data analytics.ĭMAIC – This cornerstone of Six Sigma stands for Define, Measure, Analyze, Improve and Control. That said, the tools and techniques of Lean Six Sigma remain the same. The ability to quickly analyze large data sets also improves the accuracy of outcomes.
The vast amounts of data a company collects can enhance Lean Six Sigma tools and techniques by allowing them to work faster. Forbes reported that “nearly all manufacturers are relying on Six Sigma programs to troubleshoot specific trouble spots and problem areas of suppliers who may have wide variations in product quality in a given period.” Ways To Start Using Lean Six Sigma and Data Analytics In this area, Forbes reports that businesses are “applying Six Sigma to know process bottlenecks.”Īnother core metric is ensuring the quality of what is delivered by suppliers. Takt Time in Six Sigma measures the time between the start of production on one unit and the start of production on the next unit. How Six Sigma Can Support Data Analyticsįorbes also wrote about the core metrics businesses use to determine how analytics are impacting areas such as manufacturing operations, finance, accounting, supply chain management, procurement and service.Īmong them is manufacturing cycle time, which is similar to Takt Time. Ideas gleaned from data also have helped companies innovate production operations, inventory management, fleet management and customer service. Organizations are using data analytics to automate everything from manufacturing processes to handling the paperwork needed to comply with government regulations or audits. 32% of manufacturers said analytics can improve supply chain performance and increase revenue.69% of manufacturing decision-makers said analytics are crucial for success in 2020.46% of manufacturers said data analytics are necessary to stay competitive and grow.In an article on the importance of data analytics, Forbes reported on recent surveys that found data analytics and business intelligence are a priority for most organizations.
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The key to success is having the right people in place who have been trained on the details of Lean Six Sigma methodologies as well as how to apply them. Merging continuous process improvement with the power of advanced data analytics offers organizations a chance to improve operations, whether it’s a retailer looking to optimize a digital marketing campaign or a manufacturer that wants higher yield rates and better quality on the shop floor. Lean Six Sigma offers help in these areas. Questions now center on how to best leverage that data – or even what to analyze in the first place.
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The availability of advanced software systems has made the collection and analysis of data easier than ever.
Businesses face a key point as they move into a new year.