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Simplicity : the new competitive advantage in a world of more, better, faster
The greatest challenge that people and companies face isn't from the competition, the marketplace or anything else out there. It is from confusion within organizations. Simplicity, outlined here, is the disciplined use of one skill and one tool.
Book
Smarter Processes - Applying ChatGPT to Lean Six Sigma & Quality Management
Learn how to integrate ChatGPT with Lean Six Sigma and quality management processes. Discover how generative AI enhances data analysis, regression, process monitoring, and more for process improvement.Key FeaturesApply AI to perform regression analysis, control charts, and Pareto analysisUse ChatGPT as a conversational data analyst to interpret complex dataLeverage AI for process stability monitoring and quality improvementBook DescriptionIn this course, we explore the integration of ChatGPT with Lean Six Sigma and quality management practices to enhance process improvement efforts. Starting with the basics of generative AI, you’ll learn how to use ChatGPT to assist with various phases of Six Sigma, including Measure and Analyze. From performing simple and multiple linear regressions to logistic regression, ChatGPT helps you model and understand data relationships. Additionally, you’ll learn to create and interpret control charts, calculate sigma values, and conduct Pareto analysis to pinpoint the most critical factors impacting quality. As you move forward, we will show how ChatGPT can function as a Master Black Belt, offering insights, expertise, and guidance on improving processes. The course also highlights ChatGPT’s role as a conversational data analyst, capable of analyzing and interpreting complex data, including Voice of Customer (VOC) inputs. You will discover how AI can be used to transform raw data into actionable insights, driving quality improvements and more informed decision-making. By the end of the course, you will have the tools to leverage ChatGPT in Lean Six Sigma projects, enabling more efficient process monitoring, quality management, and data analysis. This course provides valuable techniques for enhancing your workflows with generative AI.What you will learnIntegrate ChatGPT into Lean Six Sigma and quality management processesPerform regression analysis and interpret control charts with ChatGPT's helpConduct Pareto analysis and calculate sigma values for quality improvementUse ChatGPT to analyze Voice of Customer (VOC) data and turn feedback into actionable insightsLeverage ChatGPT as a Master Black Belt to provide process improvement guidanceImprove data analysis and decision-making efficiency in quality managementWho this book is forThis course is perfect for professionals in Lean Six Sigma, quality management, data analysis, and process improvement roles. It is suited for individuals who are looking to enhance their workflow by integrating generative AI tools like ChatGPT into their process optimization efforts.
Streaming Video
The efficiency paradox : what big data can't do
\"A bold challenge to our obsession with efficiency--and a new understanding of how to benefit from the powerful potential of serendipity\"-- Provided by publisher.
Book
Analysis on Spatio-Temporal Characteristics and Influencing Factors of Industrial Green Innovation Efficiency—From the Perspective of Innovation Value Chain
Green innovation has become an important combination of high-quality economic growth and ecological sustainability. In this paper, the super-efficiency network SBM model was used to measure the two-stage green innovation efficiency of the industrial technology research and development (R&D) stage and achievement transformation stage in China (30 provinces and cities) from 2009 to 2019. The results show the following points. Firstly, in terms of temporal series, the efficiency of technology R&D and achievement transformation has experienced three stages of “upward-declining-revitalized period”. Secondly, in terms of spatial trend, the industrial green innovation efficiency gradually increases from northwest to southeast. The high-efficiency areas are still concentrated in the eastern coastal region, with a clear trend towards balanced development in the central and western regions. Finally, openness, industrial structure, government technical expenditures, enterprise scale, and environmental regulation all have different degrees of impact on the efficiency of green innovation in the two stages. Based on the above, this paper is helpful for the government to formulate laws and regulations and coordinate the level of regional economic development and clarify the spatio-temporal characteristics and influencing factors of the efficiency of green innovation.
Journal Article
Resources, efficiency and globalisation
\"International business for the modern firm has to compromise the need to use limited resources and achieve efficiency in the global marketplace. This book examines these issues from the viewpoint of the internationalized SME, the big multinational and the local subsidiary drawing on research conducted in different countries\"-- Provided by publisher.
Book
Challenges for Sustainable Water Use in the Urban Industry of Korea Based on the Global Non-Radial Directional Distance Function Model
Since water stress and industrial water pollution pose a huge threat to South Korea’s sustainable water use, it is an urgent task to assess industrial water green use efficiency (GUEIW). Based on the global non-radial directional distance function (GNDDF) model, this paper calculated GUEIW in 16 Korean local governments from 2006 to 2015 using two decomposition indicators: Economic efficiency of industrial water use (ECEIW) and environmental efficiency of industrial water use (ENEIW). The growth of GUEIW is mainly driven by ECEIW, and subsequent environmental problems are obstacles to achieving green use of Korean industrial water. The regional heterogeneity of GUEIW is so important that the downstream region outperformed the upstream region in all three indicators. The government’s efforts to ensure water quality inhibits industrial development in upstream areas, where incomes are much lower than in downstream areas, and downstream industrial areas have to pay upstream industrial areas extra for water. However, regarding upstream industrial areas, low prices easily promote water waste. Because of relatively high water use costs, downstream producers are encouraged to save water. To improve the economic efficiency of industrial water use in upstream areas, advanced water technology should be developed or introduced to make full use of water resources in industrial production.
Journal Article
The Impact of the Digital Economy on Industrial Eco-Efficiency in the Yangtze River Delta (YRD) Urban Agglomeration
Enhancing industrial eco-efficiency (IEE) represents an inherent imperative in the pursuit of green, low-carbon, and high-quality development. The burgeoning digital economy (DE) contributes to the digitization and intelligent integration and transformation of production and consumption, which contributes to enhancing economic efficiency and resource utilization efficiency while reducing carbon emissions and the environmental pollution associated with industrial production and providing important support for the ecological transformation of industries. In this context, using data from the YRD urban agglomeration and employing the Tobit model and the spatio-temporal correlation model, this study analyzes the impact of the digital economy on industrial eco-efficiency. The findings are as follows: (1) The correlation over time between IEE and the DE followed an inverted V-shaped trend, while the relationship between the DE and pure technical efficiency (PTE) exhibited a fluctuating W-shaped pattern. The spatial correlation revealed Zhejiang province as the primary concentration of positive correlation between the DE and both IEE and PTE. (2) The development of the DE had a significant positive impact on IEE, not only directly but also indirectly through promoting green technological innovation and advancing industrial structure. (3) The analysis of regional heterogeneity showed that the development of the DE in core cities played a catalytic role in improving IEE, whereas the impact of the DE on IEE was not significant in outer cities. This research not only offers new views on how to develop industry in more environmentally friendly ways, but it also sheds light on the real effects of the digital economy on high-quality urban development.
Journal Article
Modernism and the Culture of Efficiency
Cobley's close readings of modernist British fiction by writers as diverse as Aldous Huxley, Joseph Conrad, and E.M. Forster identify characters whose attitudes and behaviour patterns indirectly manifest cultural anxieties that can be traced to the conflicted logic of efficiency.
eBook