Vishwadeep Khatri

How many insect fragments or Rodent hair are permissible in food items. Just search for those terms here - http://www.fda.gov/Food/GuidanceRegulation/GuidanceDocumentsRegulatoryInformation/SanitationTransportation/ucm056174.htm Any comments?

Science can be bad. Data can be made to lie. Have a look - http://www.ted.com/talks/ben_goldacre_battling_bad_science

Dear Mahendra, One useful approach in fraud detection is the use of Benford Law. Here is a link that should help - http://www.statistics.gov.hk/wsc/CPS021-P2-S.pdf

Hi, Yes, it is just a rounding off error that causes the difference. The formula in excel uses normsdist and not normdist.

To state it simply, the more assessors you have, the harder it is to achieve an acceptable measurement system.

I agree to your points. Lean Six Sigma is not just about process improvement. It is also about process design. Designing a sales process for a new offering is an important challenge that companies face very often. This is area offers an immense opportunity for DMADV kind LSS projects. In recent times, I have worked with two well established organizations in digital marketing who found absolutely new opportunities while utilizing Lean Six Sigma.

Hi Syam, Hope you have benefited with your Lean Six Sigma learning. Do share your experiences

Hi Chandrasekar, I - MR chart is designed for continuous data but used often for discrete data as well. If one does not know which chart to use, I-MR chart is a good starting point.

Hi Rajiv, One option is to carry out a 5S audit and then have an internal brainstorming session to review the scores and worthwhile action areas.

Dear Pavan, Here are some answers. 1. Continuous data requires less number of samples as compared to discrete data in a similar sitiuation. 2. Sample size depends on the hypothesis that you are trying to test. Best Regards, VK

Dear Vaseem, Please note that Benchmark Six Sigma does not provide information on Industry Benchmark that you are seeking. We provide Business Improvement Programs of various kinds for which you can visit our website. Best Regards, VK

The difference with data analytics is highlighted by a very popular definition - by Michael L George. "Lean Six Sigma is 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" Lean Six Sigma provides an entire approach for business improvement including methods of identifying, defining, measuring, analyzing, improving and controlling. An "analytics" person may contribute in some of these phases (mostly (define and analyze) Hope this helps.

Hi Rajiv, Attrition is one of the most pressing problems in many companies. Here are some of my thoughts and suggestions. I presume that the exit interviews were done in a congenial atmosphere with promise of anonymity. There are sensitive causes that people will not expose unless they are comfortable. There should be multiple ways of doing Pareto's analysis (other than by causes - which you have done). For example you may do this analysis by tenure, by function, by job goals, by salary bracket etc. Please try some of those which you find meaningful. While doing Pareto's analysis with reasons, there are chances that the categories are not mutually exclusive - Someone may have left because of multiple reasons (though may have chosen to mention only one). Hope this helps. Best Regards, VK

Hi Srinivasan, I presume you are referring to something like productivity. If that is the case, it is not feasible to have upper control limit but you may not have an upper specification limit. Specification limit is a value beyond which the outcome is called defective. Hope this helps.

Dear Ashok, My email id is vk at benchmarksixsigma dot org. Best Regards, VK

Hi Srinivasan, good question. Your sample size to be audited shall depend on various factors, some of these are - Are you going to collect data for something like handling time (continuous) or for accuracy (attribute data) for calls? Sample size is smaller for continuous data and bigger for attribute data. How the performance has been in the past? If you have information from the past, it might help in reducing sample size. What is the objective if taking samples? You might be comparing the performance with an external standard, for example or you may like to compare different sets of data. Size depends on this. How much error you are willing to tolerate? Reducing error shall mean more samples needed. Finally, how much difference (from standard value or between sets of data) you wish to detect. If you are trying to detect smaller differences, you need more samples.

Hi Arun, a requirement not met is a defect. So, for Purchase Department, an incoming non conforming material is a defect, non-conformities missed in receiving inspection is a defect, good material rejected is a defect, not following the specified procedure is also a defect. It is hard to specify an action to reduce defects at this point as your action shall depend on the kind of defect and the surrounding information that you can gather when you are at the workplace. Hope this helps.

Hi Ashok, yes, that was a question posted in October 2013. It missed our attention and I responded it recently.

Hi Gopinath, I am not sure if your organisational circumstances provide an opportunity for customer to provide rating or appreciation for identified individual employees. If yes, is there a possibility of keeping it unbiased or beyond influence. Measurement of delight is highly dependent on perception and I feel we should get it from the horse's mouth. If the above is feasible, an "above expectation" feedback qualifies for customer delight while "met expectation" is satisfaction - I am just using hotel industry approach here. Hope this helps.

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.