Vastupal Vashisth

Six Sigma is a data driven approach: It is an easily appreciable fact that decisions should be taken based on data (to the extent possible) and should not be based on the gut feel or judgment. Six Sigma provides us with information on which and what type of data should be collected, how it should be collected and how it should be analyzed. Example - In a bank, the number of employees was increased based on the gut feeling of the senior management, while the biggest competitor of this bank analyzed the trends of work flow for future projects through simulation and created flex-profiles to reach very high service levels while maintaining the same manpower count. Six Sigma is a process focused methodology: Everything that you do in the workplace has a process behind it. For bringing improvements it is always good to study the underlying process along with the results, especially if we are looking for a long lasting improvement and not a temporary quick-fix solution. As Deming said - 85% of the problems are due to system and process deficiencies and not due to human errors. Behind most human errors is a weak process. Example - The chances of the wrong module being integrated into a software development can not be eliminated by just a reward or punishment mechanism. In organizations of any size or complexity, Six Sigma methodology poses the following questions repeatedly: Are we working at the best possible performance levels for our key processes? If the answer is yes, is it feasible to explore new processes that can set new benchmarks and give our company a bigger competitive advantage? If the answer is no, what is it that is stopping us from forming and supporting a team that can enhance the performance level in a manner that makes business sense. The age-old algebraic equation says it all: Y = f (X). If Y is the effect and the Xs are the causes, then putting all the focus on the Y or guessing which X is most significant are both bad ideas. One thing Six Sigma helps with is understanding these relationships statistically so work can be directed at the cause or combination of causes (Xs) most likely to change the effect (Y). This activity helps break the endless string of firefighting brought on by never really getting to the root cause of any effect. This equation is at the heart of the Six Sigma methodology and with the DMAIC and DMADV roadmaps drives a company through a logical, sequential process to efficiently find the significant Xs and act on them. This gives the highest probability of success and helps turn the tide of reactive behavior. Here are some reasons why we should be using Six Sigma to make process improvements: It is a structured approach - if we follow the process, people will not forget any important steps along the way before they implement the solution. It helps quantify the benefits and thus make it easier to sell the improvements to senior managers in the company. It uses facts & data and the rigor of statistical testing to arrive at the right root cause instead of fixing symptoms or putting band-aids. There is a greater likelihood of the solution being sustainable if we follow the Six Sigma process. Six Sigma focuses on solving the right problems using the project selection matrix. It has proven itself in a large number of deployments. Frankly, there is no better tool out there to make process improvements - especially when the root cause or the solution is not known. Lean Six Sigma provides you with world best methods of data driven decision making. If you are working in an organization or running a business, it is inevitable that you shall need to use data in decision making. Some pointers that highlight the importance of data driven decision making are given below. Even if one uses brainstorming techniques with teams, one can generate and use data. The use of basic cause-effect approaches for analysis like fishbone diagram get strengthened only by effective use of data. All functions in an organization generate data of various kinds. It makes sense to learn correct methods and techniques that help in decision making for business success. Analysis of wastes in a process requires data (like cycle times, takt times, value added time, non value added time, productivity, etc) Finding whether internal/ customer requirements (or regulatory requirments) are met requires data driven techniques like hypothesis testing. Forecasting methods are essentially a set of data driven techniques. Comparison of two or more sets of data( for comparing vendors, technology, techniques, materials, processes, customer types, teams etc) is a common need. Market research or R&D makes us of data all the time. Problem Solving is strengthened by usage of data. Project Management requires data driven decisions. Performance management cannot be considered fair unless data is capured, analyzed and used properly. There are two primary methodologies in Six Sigma: DMAIC DFSS The Six Sigma DMAIC methodology is for making improvements to existing processes. The second methodology DFSS stands for Design for Six Sigma. This methodology is used for new products and services or when the improvements that can be made with DMAIC is not sufficient. There are several approaches to DFSS: DMADV, IDOV, etc. The most popular approach to implementing DFSS is using DMADV (Define - Measure - Analyze - Design - Validate). More than 70% of the DFSS implementations use the DMADV approach. DMAIC can be considered to be reactive in nature, in the sense that a process already exists and is making defects. DMAIC approach is used to identify the root cause of the problems and then fix it. On the other hand, DFSS is mostly a proactive approach. A process does not exist yet and DFSS is used to truly understand customer requirements and then develop a process that provides exceptional levels of quality and process performance. Design for Six Sigma (DFSS) is a Six Sigma methodology that is used to launch new products & services on time, on budget, and on target gaining incremental revenues sooner, achieving greater market share, and ensuring that the company generates differentiated products & services that target customer & stakeholder needs. DFSS methodology is most commonly used in New Product Development organizations. If we see approaches to DFSS, the most popular methodology is called DMADV. DMADV stands for "Define - Measure - Analyze - Design - Validate". The Define phase consists of defining the project charter which includes the business case and the opportunity for the new product or service. In the Measure phase, the needs of the key stakeholders are identified and measurable CTQs are developed. The Analyze phase consists of subsystem design and generating and selecting the best possible concepts. In the Design phase, a detailed design for the product or service is developed and optimized. The robustness of the design is ensured to minimize the impact of variation on performance of the product or service. Finally, in the Validate phase, the generated designs are verified and validated using simulation and other approaches. Some of the tools covered in DMADV training are: Multi-Generational Project Plans (MGPP), Analytical Hierarchy Process (AHP), Kano Analysis, Kansei Engineering, Theory of Inventive Problem Solving (TRIZ), Quality Function Deployment (QFD), Pugh Analysis, Multiple Regression Analysis, Fractional Design of Experiments, Taguchi Optimization, and Discrete Event Simulation methods. DFSS is a powerful set of tools and techniques that can help you develop products and services that truly satisfy your key stakeholder needs. By adding this toolkit to your repertoire, you can demonstrate to your current or future employer that you understand how to not only reduce the bottom line costs using DMAIC but also develop robust products and services to increase top line growth using DFSS.

For organizations to stay competitive in today’s economy, it is essential for them to adopt and ingrain-in three important concepts of Kaizen (Change for Better), Kaikaku (Revolutionary Change), and Kakushin (Innovation). Organizations do benefit from these through continual improvement of their processes, transformation of their organizational culture, and becoming an innovative entity. Kaizen: It was about 40 years ago when the philosophy of Kaizen entered the western culture via automotive industry. Kaizen is the Japanese word for continuous improvement using small incremental changes. It translates as change for the better. Kai means change, Zen means for the better. It basically pointed out the fact that by elimination of non-value added work (Muda / 7+1 types of waste) in the work processes, companies will become more efficient and as a result be more profitable and competitive. This great philosophy of Kaizen that encourages incremental continuous improvement, in the last decade, has spread out among other service oriented industries, i.e. Healthcare, IT, Retail,etc. where the need for a more rapid and agile methodology was felt. It was realized as a necessity to be able to deliver products and services to the customer quicker, while maintaining the high quality and lower cost. Lean IT Kaizen is an approach for solving problems and forms the basis of incremental continual improvement in organizations. A problem is a difficulty that has to be resolved or dealt with. When applied to the workplace, Kaizen means continuous improvement involving everyone, managers and workers alike, every day and everywhere, providing structure to process improvement. Kaizen is about continuously improving: everyday, everyone and everywhere. Many small improvements implemented with Kaizen produce faster results with less risk. In IT terms, we can equate this to a minor update to a piece of software. Toyota Motor Corporation, who made Kaizen philosophy famous, has also started questioning how Kaizen could be improved upon to address the requirement of being able to implement changes more rapidly. And to respond to it, the concept of Kaikaku was born. Kaikaku: Lean also recognizes that there are moments that more radical, step change is necessary. This type of change is known as Kaikaku. This refers to a revolutionary change to the existing situation. Following the software example, Kaikaku would be the upgrade of an application currently in use from a release level to a new release level. Software providers will often substantially change both the technical basis of the software and its functionality. For both IT and the user community, this means a large step change. Kaikaku is Radical Change, where emphasis is on revolutionary change and big improvements. It allows organizations to reform and transform their culture and work habits into greatness via implementation of fundamental changes in the existing production systems. It is a large-scale and wide-ranging activity that is initiated and invested in by the executives and top management. To clarify this more, let’s look at different scenarios in an automotive manufacturing plant. When we perform projects to reduce the production time, implement 5S, or redesign the assembly line, we are implementing Kaizen. On the other hand, when we introduce a new lighter material to be used for the vehicle’s body or install robots to weld, press, or paint the vehicle, we are applying Kaikaku. So far we have explored making either small incremental improvement changes to better the production processes (Kaizen) or big revolutionary changes to reform existing production systems (Kaikaku). However, there are times that new revolutionary and breakthrough ideas, products, or services are desired and needed and thus we have to renew our way of thinking and doing and become innovative. This innovation and renewal is called Kakushin. Kakushin: The concept of Kakushin was mentioned by former President of Toyota, Mr. Katsuaki Watanabe; during interviews with Wall Street Journal and Harvard Business Review in 2007 as a Radical Innovation. He elaborated this concept by saying that if we could make simplified cars by cutting the number of parts in half and design more flexible production lines to manufacture many different car models rapidly, then we had made a new revolutionary reform in our production system and that is Kakushin. A third type of improvement known within Lean is Kakushin. The idea here is that some change will form a complete departure from the current situation. It is about innovation, transformation, reform and renewal. Again, in software example, this may mean replacing a complete application with a different application that support the process in a completely different way, for example a web-based application that fully automates the registration of orders, the submission of invoices and the generation of a picking order at order fulfilment. This kind of change will entail the disappearance of many roles and functions within a business. Both from technological and business process perspectives, this example represents a complete departure from the current way of working. Another example of Kakushin is where the organization standardizes a process and supporting software across the entire organization where previously various groups had different processes and applications to achieve similar goals. In conclusion, effectively applying these three essential concepts of Kaizen, Kaikaku, and Kakushin is the right solution for any organization who wants to deliver a sustainable high quality product or service and to ensure a steady growth in the global market.

According to Dr. Deming , it is most important that top management be quality minded. In the absence of sincere manifestation of interest at the top, little will happen below. He elaborated more in his book Out of Crisis(1986) , below are points said by him on his view on management : Create constancy of purpose for improving products and services. Adopt the new philosophy. Cease dependence on inspection to achieve quality. End the practice of awarding business on price alone; instead, minimize total cost by working with a single supplier. Improve constantly and forever every process for planning, production and service. Institute training on the job. Adopt and institute leadership. Drive out fear. Break down barriers between staff areas. Eliminate slogans, exhortations and targets for the workforce. Eliminate numerical quotas for the workforce and numerical goals for management. Remove barriers that rob people of pride of workmanship, and eliminate the annual rating or merit system. Institute a vigorous program of education and self-improvement for everyone Put everybody in the company to work accomplishing the transformation On other hand if we see Peter Druker point of view about management , he has given 6 major contribution in defining management . 1. Nature of Management 2. Management Functions 3. Organisation Structure 4. Federalism 5. Management by Objectives 6. Organizational Changes. Nature of Management: Drucker is against bureaucratic management and has emphasised management with creative and innovative characteristics. The basic objective of management is to read towards innovation. The concept of innovation is quite broad. It may include development of new ideas, combining of old and new ideas, adaptation of ideas from other fields or even to act as a catalyst and encouraging others to carry out innovation. Management by Objectives:Management by objectives (MBO) is regarded as one of the important contributions of Drucker to the discipline of management. He introduced this concept in 1954. MBO has further been modified by Schleh which has been termed as management by results’. MBO includes method of planning, setting standards, performance appraisal, and motivation. According to Drucker, MBO is not only a technique of management but it is a philosophy of managing. It transforms the basic assumptions of managing from exercising cattalo to self-control. Therefore, in order to practice MBO, the organisation must change itself MBO has become such a popular way of managing that today t is regarded as He most modern management approach. In fact, it has revolutionalised the management process.

Root Cause Analysis is for a problem solving. approach to be follow according to four possibilities: A cause may be necessary but not sufficient for a problem to occur. for example customer found a wrong Door assembled in a car because a wrong variant part has been assembled to another child part in welding jig. in this, wrong variant part supplied and welded with child part in welding jig is necessary cause for wrong assembly but not sufficient because system is not so effective that it can stop assembly of wrong variant parts to child parts and stop delivery of those wrong assembled door in car. we can do why why analysis/brainstorming and can do Poka-Yoke to error proof so that wrong variant will not be assemble with child part in welding jig so that it customer will not get wrong assembled door in the car. A cause may be sufficient but not necessary for a problem to happen. let me tell you this with a example, if a part is rejected then to have crack in part is sufficient to reject it but its not necessary to have only crack because there are other factors also due to which part can be rejected. So in this case we can use Why Why analysis to find out root cause. A cause may be neither sufficient nor necessary for a problem to occur. For example we have rejection of different parts due to different factors because one cause is neither sufficient nor necessary, so we should do initially brainstorming, affinity diagram followed by Pareto Analysis for prioritization and then do why why and fishbone analysis accordingly A cause may be both sufficient and necessary for a problem to occur. Parts not delivered to next customer because of non availability of parts due to non production that is sufficient and necessary condition. in this case we can for JDI( just do it), we can produce the parts and can deliver the parts to next customer because we know both cause and solution.