Vishwadeep Khatri

Hi Rajiv, Thanks for posting here and sorry for the delayed response. Do not know how I missed this one. It looks to me that Minitab is correctly used. However, in the calculator, the sample size is taken as 197 which does not seem to be correct. Please add the samples for all 91 instances in the column. The value should be 5444. Now if you use the sigma level calculator with 92 defectives and samples as 5444, you shall get Zlt same as 2.12 (as you got from Minitab) Hope this helps, Please feel free to ask further.

Hello Vinod, It is better to use Stat> Power and Sample Size> Specific hypothesis test (for which you wish to calculate the sample size).

Dear Vikram, You have options. If the client is looking for AHT, I do not know if they will be happy looking at median though it is a better representation of your data. You may transform the data for baselining purposes and calculate the Z value. For hypotheses however, it is better you consider non parametric tests with original data. Hope this helps.

Several decades ago, a powerful approach called Total Quality Management was introduced. The idea was - quality should not be confined to a department or function but should be all pervasive in the company. Everyone should embrace the concept of quality. Everything we do should show our commitment to quality - all functions - from security to administration, from hiring till exit, from order till delivery, we should work with a commitment to customer satisfaction. Seven Flaws noticed in TQM: Total Quality Management was a wonderful concept but had its flaws. Some of the notable one's were - There was no mechanism for structured training. Quality Management professionals conducted training which was sometimes not well received by other functions. Whenever operational urgency emerged, senior management was seen to be supporting operations and not quality. Quality was still seen as stopping the flow of money while functions like sales, marketing, and operations bring money to the company. At most places, TQM became a slogan or a training program. People were not engaged in real improvement work. People learned several methods. It was unclear how these quality tools connect with each other. People applied the methods in bits and pieces. There was no tried and tested organizational structure for TQM implementation. Data driven methods were used in a limited fashion and revolved around 7 QC tools and Quality Circles. TQM implementation did not link with strategic goals of the company. Lean Six Sigma (LSS) addressed the flaws: Lean Six Sigma succeeded in a large number of companies as it filled the above gaps in the execution of TQM philosophy. While the initial definition of Six Sigma mentioned it as an approach that increases first-time right output in production, today it is considered it as a full fledged business improvement methodology. If an improvement project has a business case, utilizes structured learning of best methods, engages cross functional teams, uses right data collection and analysis, and closes with sustainable gains, it is appreciated and encourages more of its kind. Evidence of Professional Growth with Lean Six Sigma: Click here to see senior professionals of leading companies who attend our Green Belt workshops. Click here to see how Black Belt trained professionals have grown. You are invited to share your views as a reply to this post.

Used sometimes in a copy-book style and several times in an unorthodox fashion, Lean Six Sigma approaches have been bringing large scale business improvement across sectors. I have been doing training and consulting on Lean Six Sigma(LSS) since 2001. We started conduct of structured LSStraining in the form of Green Belt in the year 2005. I shall mention changes that I have personally experienced over the years. This article shall explore several perspectives using a then (2005-06) and now (2013-14) comparison. The book has changed and so has the meaning of copy-book: Copy book six sigma started in 1987- The original proponents of the subject had a copy book approach towards quality with a five stage structured approach to defect reduction. The original definition of Six Sigma referred to the ability of a process to generate a high percentage of the production output. This gained credence in many companies like Motorola (originator), Honeywell, and General Electric in a few years. GE developed methodologies that can be applied to services and to design. In 2014, there are large numbers of professionals promoting lean Six Sigma in a copy-book style but with an entirely different perspective. One look at the modern definition will explain how the meaning has changed. Lean Six Sigma is vastly regarded as a business improvement methodology that maximizes shareholder value by achieving the fastest rate of improvement in customer satisfaction, cost, quality, process speed, and invested capital. Quite clearly, Lean Six Sigma has moved from the perspective of Quality Management (which considered management of quality in a company) to a methodology that enhances the Quality of Management. The numbers then and now: When we started conducting green belt programs way back in 2005, we had an odd service sector participant sneaking in with a shy look as he saw all manufacturing folks occupying seats. This rapidly changed to 30 percent service sector participation by 2007 and finally to 85 % in 2014. The numbers in Green Belt programs have been changing over the years as well. In open enrollment programs, we trained about 100 people in the year 2005. It has swelled to 200+ per month now. In 2005, very few organizations in India had an internal Lean Six Sigma program. Today, a large percentage of managerial work-force gets trained in internal programs of leading companies in various sectors. Enhancement of cross domain expertise: One of the most prominent unchanged features of LSS in these nine years is that professionals with business excellence expertise are able to pursue opportunities across domains. This helps them grow across verticals as the business improvement skill-set is respected everywhere. This has been one of the reasons why senior professionals from various industry sectors have been nominated for these programs. In the 60+ Black Belt batches that we have completed, the career growth of at least one professional of each batch is highlighted at Applicability of Lean Six Sigma: The views on applicability were questioned in several domains initially. To be frank, there are a number of detractors even today, but the believers have been doing well all these years. Let us review various domains. R&D: One of the most vehemently opposed groups initially was the R&D function. This has changed to quite an extent. In recent times, we have worked with design teams of VoithTurbo, William Hare, Dr. Reddy's, Kone Elevators, to name a few. LSS is on the rise in this domain. Banking and NBFC: Having trained professionals from American Express, JP Morgan Chase, HDFC, ICICI Bank, ABN Amro, Max New York, HSBC and the likes, I can say that the methodology is here to stay in financial domain. BPO/ KPO: Due to severe productivity and cost pressures, outsourcing industry has been active with LSS. Another reason for BPO’s early entry into this domain was due to their perceived similarity with manufacturing. All large BPO’s in India and LSS implementers. Informational Technology: IT experts in India have been joining the LSS bandwagon for one more reason in addition to business improvement objective. Most clients happen to be from the US and are active with LSS practices. It became a client expectation that project managers in IT domain understand and use the philosophy during software development. Most large IT companies actively pursue DMADV and DMAIC approaches. Other Services: Like healthcare, hospitality, travel, and telecom have seen significant activity with leading providers putting LSS teams in action. LSS in healthcare is a big focus area in the US in last few years and we get to see healthcare focused professionals in almost every program nowadays. EPC (Engineering, Procurement, and Construction): This industry works on projects most of the time. The leading provider of project management body of knowledge, the Project Management Institute has been promoting process approach to project management for several years now. Operations, Quality and Supply Chain: Professionals from these domains form the majority of our participants. There has been a significant increase in service sector participants from these domains as highlighted earlier. Sales and Marketing: In the digital age, search engine marketing and social marketing with platforms like Google, Facebook, Linkedin provide great opportunities for enhancements in lead generation using LSS due to the availability of reliable data. Usage of CRM solutions in most large corporates has made it easier for LSS professionals to focus on projects that focus on the increase in revenue. LSS activity is increasing marketing domain, but not so much in sales. Unorthodox Lean Six Sigma on the rise: There are a large number of professionals who use the LSS methods for problem-solving and decision making although they do not carry out end to end projects of the DMAIC or DMADV kind. The usage of the approach needs modification to suit the culture of the organization. While mature organizations thrive with the new terminology and outlook, there are hundreds of organizations where our participants prudently avoiding usage of Lean Six Sigma jargon to ensure that colleagues and bosses are not intimidated. Unusual implementers of LSS include senior professionals from Naukri.com, IT service management experts from IBM, SAP implementation experts, Black Belts at HSBC, Business Excellence experts at TCS, Wipro, GE, and Risk Management professionals in Citibank and HSBC. The biggest set of unorthodox Lean Six Sigma implementers are the large consulting companies who have created consulting roadmaps that use most of LSS methods capsuled in a proprietary approach developed by them. These consulting companies do not conduct training but take up business challenges, convert them into projects, collect data from client processes, use LSS tools and provide recommendations. Lean Six Sigma Methodologies. Then and Now: The most popular methodology continues to be the DMAIC (Define – Measure – Analyze – Improve – Control) sequence where the objective is to identify an existing process that needs rapid improvement and take through a structured problem-solving rigor. The DMADV cycle (Define – Measure – Analyze – Design – Verify - akin to business process re-engineering) has grown in stature and every year there are more companies that are seen using it. We re-launched our DMADV Black Belt program last year it seems this program is likely to grow in next few years. The increase in the pace of change: The pace at which new products are getting launched, the time in which new concepts get tested and the rapidity with which customers accept or disregard a product is visible to all of us. This has led to LSS being made a part of the decision making on an everyday life in fast moving companies. As an example, when a regulatory change happens in a country, a bank initiates lean six sigma projects which focus on minimizing losses or maximizing gains from the specific change.Companies like IBM have developed a design sequence that ensures that the power of LSS methods is put to use whenever a new IT service is launched. This ensures more instances of “first time right services. To keep pace with rapid changes, Lean got integrated with Six Sigma a few years ago. This created a new terminology called Lean Six Sigma. While Lean focuses on efficiency (faster designs, faster operations, faster deliveries etc.), Six Sigma focuses on effectiveness (meeting customer requirements).The LSS assignments are done more rapidly at companies that are in a dynamic market place. This is natural as no one can afford to spend much time in improving a process that is bound to be revised soon. This has also created the case for DMADV projects being taken up more often as compared to DMAIC in fast paced sectors. The paradigm shift: The shift from Inspections at the end to First time right at source is becoming a powerful management driver in more and more companies. FMEA that ensures risk mitigation, Mistake proofing that eliminates the possibility of defects, SPC that provides early warning alerts is gaining traction. Companies are realizing more than ever before that need for scalability creates a need to build extra-ordinary processes. LSS methods are aligned to build such processes in organizations. I will be pleased to answer queries on the subject.

Dear Ramanan, The units can be number of lines or can be number of pages or number of documents. As Sigma level is an internal metric, you are free to choose a metric that sets a good standard. In future comparisons are going to be made based on DPU, so it makes sense to discuss internally and decide logically. There is no global standard on what should be considered a unit. Hope this helps.

Defectives vs DPMO vs Yield vs Sigma Level Defectives as a data set does not make use of opportunities for error existing in a process. Defective is an entire unit while defects are the number of non conformities, which might be more then one in a unit. Customers generally prefer using defectives data to gauge the performance of a process. Yield (non defectives) is likely to be their prime metric. Process owners need to be detail oriented and generally prefer to use DPMO as their prime metric. A special case - If there is just one opportunity for error per unit, number of defects and defectives is the same. In such a case, DPMO method provides same sigma level as yield method and conversion is simple - if DPMO is 10000, yield is 99%. Hope this helps.

Hi. Mohini, Lean Six Sigma is a set of approaches that is used for business improvement. It commonly follows a DMAIC cycle and is a systematic sequence of problem solving. If you reword your question to highlight a business problem in a power plant, I shall be able to provide a more specific reply.

Please use the DPU method in this case. Errors are defects as there can be many of them in a single documents. You have correctly pointed out that the opportunities cannot be counted.

Interesting question. The flaw is - correlation and regression should only be used for variables that have a known cause and effect relationship. In this case we should not have used these tools.

Thanks for participating in this discussion. I agree with comments above in the context they are presented, but want to add a caution. And the caution is - we should just be talking only of occasional occurrences. An occasional false alarm is fine but too many of these can lead to loss of business or even closure of a company. As an extreme example, let us consider an automotive company that decides to do 100 percent inspections on all parts leading to high cost of product which finally leads to loss of market. We need to also consider that a false alarm can lead to process adjustments when none is required in an existing good process. Comments welcome.

With respect to complex process improvement projects - One argument goes like this - "Most of the times, it is not difficult to find a solution to a problem. The most difficult part is nailing the root cause. If the root cause is unclear or misunderstood, the attempts at solution do not work; it just seems that the solution is so hard to find. However, if the root cause is understood precisely, the solution shall just come and sit on your lap. (or you will know soon that there is no solution if the root cause is absolutely out of your span of control)". Another argument goes like this - "In most projects, the root cause of problems are found spending lesser time and effort. It is the sustainable solution that is tough to find. One needs to try various alternative solutions and this means some sort of trials/ pilots/ benchmarking/ brainstorming/ simulations are needed. More energy therefore needs to spent in evaluating alternative solutions so that we choose nothing but the best" If you dig into your experience and think hard on this, which point of view would you support over the other?

I assume that you have carried out these tests one by one (also called OFAT - one factor at a time). Due to feasibility of interactions (combined complex effects), it is not advisable to combine these results to reach a generalized conclusion. To be able to find a combination in a candidate that has the highest probability of passing, it is advisable to design experiments that use various combinations. Also, in such an experiment it is better to take the output as exam score instead of just a pass/fail outcome. Hope this helps.

Thanks for your response. Discussion in a forum is likely to have some risks of misunderstanding. To be sure that I understand clearly, I request you to provide details of the process and the explanation of categories.

Hi Ashish, A p value of zero indicates that the two extreme categories (the one with lowest success rate and the one with highest success rate) have a significant difference. You may like to remove one of these and run the test again to see if others show a different result. If you again get a zero p value, you can continue removing an extreme value and re-run the test one-by-one and draw conclusions. Hope this helps.

Hello Nagarajan, Here is some useful material to go through -http://globalnews.benchmarksixsigma.com/category/new-to-lean-six-sigma/lean-expert-basics/ Best Regards, VK

There has been no question so far on this article, here is one for the writer - "If data is used less frequently for decision making in a company where processes are mature and self adjusting in nature, the company may survive for a longer period. Comparatively, a company that uses data very frequently for decision making but the type of data is not forward looking or provides limited information, this company may be worse off." What is your comment on the above?

Dear Tarun, good article. Do you think there are situations where decision making should not use data? Are there situations where data analysis may be considered detrimental? Provide examples to support your view.

Kongkan, good work. Here is my question for you. If data driven decision making is so suitable for complex situations and it takes time to build intuition, why did Deep Blue - IBM's chess computer lose several games with Kasparov? After all, it had the capability of evaluating 200 million positions per second and more man years behind it as compared to Kasparov. http://en.wikipedia.org/wiki/Deep_Blue_(chess_computer)

Nachiketa, this is a very good write up. One query I have is this - You have mentioned that " D3M does not save time or money, at least not in the short term." Is this statement data driven? How?

Hi Suhani, very good article and good responses so far. Referring to your examples of stock markets, why is it that mostly those with deep pockets survive in markets? Why is it that most of the stock advisers/ experts like to spend their time making recommendations for others while the money at stake is not theirs? Don't you think that the data crunching experts should ideally be busy in higher value activity of multiplying their own existing money?

Hi Vignesh, Yours is a well written article. If you were involved in creation of a new product (in an entirely new category) where past data and predictions using past behaviors seem irrelevant, would you still recommend use of data in some way or just go with gut feel of the business leader?

Excellent article. I have a question - How do you suggest use of data in decision making when the product belongs to an entirely new category with no antecedents? Forecasts are unlikely to work and gut feel probably reigns supreme. The question is important as the biggest profits in the corporate world are derived from innovations. A response with examples will be appreciated.

Hi Raghavendran, If you do not have support or control in an area, it is better to look at other areas. So taking up a project in operations should be explored. Is there a pain area in operations that needs to be tackled, has good support and creates a good business case? Once you find one, you can progress further. Doing a project with a shop keeper is also fine. The lean six sigma methods do work for identified pain areas and here you have found a business case. Regards, VK

Tanmoy, How did team leaders or managers reach those positions? Many of them have been callers initially. I know several people who have risen from callers to the position of AVP. No one gets to a managerial position unless someone notices his aptitude. Aptitude shall not be noticed unless one thinks, communicates and works differently. Developing and demonstrating managerial aptitude requires some hard work. If learning and demonstrating managerial aptitude does not seem to help very soon, will not having it help at any time? It requires perseverance, patience, dedication and hard work to get to some hard goals. You have already taken the first step. Have a look at this - http://forum.benchmarksixsigma.com/page/media.html/_/ites-bpo-and-kpo/six-sigma-in-bpo-asad-siddique-r29