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  1. 4 points
    This album contains Benchmark Six Sigma Training Photographs from January to March 2019.
  2. 1 point
    Some of tools that allow for customisation and enhancements in themselves are as follows - Kanban board - This provides endless opportunities for improvement in terms of breaking up of tasks, marking expedite lanes, adding tasks on kanban cards etc. Online Kanban board platforms provide even more methods of customisation and tool improvement. Future VSM - The extent and format of details that are to be captured in a future VSM have unlimited opportunities for improvement. Andon Boards - Andon boards have infinite methods of adding details in terms of who should get alerts of what kind with what kind of escalation and how will resolution feedback be re-circulated (etc) Kaizen - The way in which Kaizens are identified, planned, executed and the way feedback and efficiency is tracked provides continuous improvement opportunities. The Lean Champion needs to be on the lookout for methods and approaches that make Lean tools more effective and therein lies the opportunity of maximising the value generation for a Lean Enterprise.
  3. 1 point
    What keeps your business engine running amidst tough competition in today's environment? I strongly believe in 4 things that acts as a differentiator a. Customer Centric Approach - Have customer in focus in whatever you do. Historical studies have always shown it costs more to acquire new customer and effective management of existing customer assures you of continuous business which in turn benefits to invest in better ways to gain new customers. b. Productivity and Efficiency - Key mantra is to do more with less within committed timelines with the focus on better OpEx management. c. Drive a balanced scorecard - A successful organisation always drive a balanced scorecard, when it comes to cost, quality, productivity and customer satisfaction. It is not one at the cost of another. d. Motivated work force - who make a difference in driving the results for your organisation Organisations today adopt multiple buzz words (mapping to the mood in the market) to drive their organization business charter which some times can befuddle the very purpose of its existence and pull your objectives in different directions rather than supporting it. You need to have a "Pivotal Program" in your organisation which can give clarity to your business charter and help position all other programs around it. I see Lean Six Sigma as this pivotal program. Every organization today broadly categorizes its work into two parts - Run the Business and Change the Business. While Run the Business focuses on delivering day to day operational commitment, Change the Business acts as an enabler to support its customer and work force. For companies today to stay competitive, they need to be profitable. They need to ensure their Run the Business operates within the KPIs as demanded by the customers and the Strategic Initiatives of Change the Business should focus on addressing the root cause that is impacting my KPIs. A simple example is, giving better experience to your customer once he calls your customer care team (run the business focus) vs. enabling simple self help to resolve his query in few steps (change the business initiative). While it is rather easy said than done, an organization may have multiple programs, tools or professionals but if it is not structured, packaged and adequately blended, we will conveniently loose out on the core objective and digress from the goal which can lead to not only financial losses but also losing their valuable customers. Even a decision not to invest in any changes, still needs to go through a methodical approach to establish the fact on why not to make an investment. Lean Six Sigma - the pivotal program, not only fulfills all objectives as a metric, method, management and philosophy but also the 4 points I mentioned above. The outcome of a methodological Six Sigma effort can help reduce cost, improve profits, drive focus keeping customer requirements, create a knowledgeable workforce and above all use a data-driven scientific approach to arrive and sustain your results. I strongly see that other programs can be positioned around Lean Six Sigma as it opens up avenues like using a Project Management approach to implement a solution, Robotics to simplify tasks, Data science for advanced analytics etc., What is key to note is that these programs need to have a trigger and Lean Six Sigma is the trigger. Finally on my concluding note, for folks who are in a denial mode to accept the benefits of Lean Six Sigma, forget organizations, I personally see the existence of Lean Six Sigma concepts in our daily life. Be it to better time management, health management or wealth management, the concepts of Lean Sigma has its contribution.
  4. 1 point

    From the album: Jan-March 2019

    © Benchmark Six Sigma

  5. 1 point

    From the album: Jan-March 2019

    © Benchmark Six Sigma

  6. 1 point
    Benchmark Six Sigma Expert View by Venugopal R If the question had been “During which phases of DMIAC TOH (Test Of Hypothesis) is largely made use of?” then the answer would be very obvious. Having asked to identify the phase where TOH does not find an application, we need to put some thoughts on every phase. My discussion here is not to be taken as a counter for any of the other responses, but may be viewed as a thought inciter. TOH is a statistical tool that will help to compare a characteristic of a population with that of another population or standard and take a decision whether we have sufficient reason to believe they are equal or not…. The decision is based on evaluation of few samples that represent the population. The phases of DMAIC that predominantly use the TOH are Analyse and Improve, and hence I will keep these 2 phases aside and look at others. DEFINE phase is where the business case has to be evolved and the management buy-in obtained. For example, if we need to decide on taking a project on improving the market share of a product for a segment of customer across geographies; we may use TOH in the form of Chi-square comparison with a competitor’s product while trying to get a management approval for the business case. MEASURE PHASE is where the Measurements systems need to be finalized and the baseline measurements need to be done. An important aspect of measure phase is to carry out a Measurement Systems Analysis. MSA practices use ANOVA, which is built upon TOH principle, for determining the existence of parameters like linearity, bias etc. As indicated, I am skipping discussion on Analyse and Improve phases, which are most popular for use of TOH. CONTROL phase is where the focus is on monitoring & ensuring sustenance of the gains. The Control plans, Mistake proofing are very prevalent methods here. Control charts that would have been initiated during the Measure phase, continue to be used for monitoring performance in this phase. Usage of control charts is possible when we obtain sample data points periodically. There could be certain situations where we may have practical difficulties in using a control chart. For example, consider a project whose objective is to improve Training effectiveness. Here, we can monitor the sustained effectiveness, only as and when the training happens. Another example could be a project whose objective is to improve the cycle time to ‘go live’ for New Product Development Process. Here, we can monitor the sustained effectiveness only when the next new product is developed and launched. Wouldn't TOH find suitable application for comparing the performance indicators of an improved process with previous / or with a standard to assure sustenance, in such situations? Let me conclude this discussion with the thought…. “TOH is well known to be applied during Analyse and Improve phases – however, aren't there situations in other phases, where it could find useful application for practical decision making?” I look forward to see the views by others on this question.
  7. 1 point
    Six Sigma gains it's edge over other Quality Management System as it uses data driven approach for problem solving. Statistics forms an integral part of Six Sigma methodology as many of it's tools refers to statistics for logical conclusions. We essentially have two branches in Statistics - Descriptive and Inferential. Descriptive Statistics helps work on collecting, analyzing and presenting information as mean, standard deviation, variation, percentage, proportion etc. While Descriptive Statistics helps with description of data, it will not manifest itself with any inferences. Inferences about data is very important for decision making and it is Inferential Statistics which helps us with the same. To answer above question on the approach for decision making using few samples, it is Inferential Statistics that helps us analyze sample data and predict the behavior of population. Further, Inferential statistics helps us establish the relationship between independent variables (X, Cause) and the outcome (Y, Effect) and also help identify the critical X which needs to be focused to improve the Y. Inferential Statistics is strongly associated with Hypothesis testing. Hypothesis testing is performed on Sample and whenever we do a Hypothesis testing, we ask below questions on whatever we saw in the sample Is It True? Is it Common Cause? Is it Pure Chance? Let us see how to perform a Hypothesis testing which is key for Inferential Statistics. Step 1. Define the Business Problem in a data driven format i.e. Y=f(X) Step 2. Select and appropriate or apt Hypothesis Test that we need to perform on the problem. We will see this in detail in next section. What drives the selection of test is basis the type of data defining both X and Y i.e. if the data type is discrete or continuous. Step 3. Make the Statistical Hypothesis Statement ; H0 = Null Hypothesis = No Change, No Impact or Difference; HA=Alternate Hypothesis = New argument holds good basis the business case. Step 4. Run the test on Sample data using tools like Minitab Step 5. Calculate the "P" value - which will be an output from the tool Step 6. Compare "P" value with "alpha" [Alpha is called as Type I error and acceptable level is generally kept at 5% or 0.05] Step 7. Do Statistical conclusion i.e. if P is greater than alpha, your Null Hypothesis holds good else your alternate hypothesis will hold good. Step 8. Do a Business Inference i.e. if Null Hypothesis holds good than the input sample is treated as non-critical x. Alternatively, if your alternate hypothesis holds good, we should treat the input as critical x. W.r.t Step 2, on selecting the apt test, below inputs should serve as guiding pointers Output Y is Discrete and Input X is Discrete in 2 categories, we need to use 2 proportion test Output Y is Discrete and Input X is Discrete in multiple categories, we need to use Chi-square test Output Y is Continuous and Input X is Discrete in 2 categories, we need to use 2-sample t-test Output Y is Continuous and Input X is Discrete in more than 2 categories, we need to use ANOVA Output Y is Continuous and Input X is Continuous we need to use Regression Analysis. In summary, Inferential Statistics is used draw conclusions on the larger population by taking a sample from the same and also try to establish relationship between the input and output.
  8. 1 point
    Benchmark Six Sigma Expert View by Venugopal R Let me attempt to narrate the unfolding of my understanding of control plan over past 3 decades…. Maybe, my first introduction to the term “control plan” was through ISO 9000 standards released during the late eighties. However, I had worked with an auto ancillary prior to that, where we had a collaboration with a Japanese organization for setting up manufacturing of an auto component, that I believe was for the first time in India. As part of the technology transfer, one of the key documents that we received was a lengthy, multiple folded, handwritten, tabulated document with all the process steps outlined, the quality characteristic for each stage of the process, the specifications, the method for evaluating compliance to the characteristic, and the sampling recommendations. I am not sure whether this document was named as “control plan” at that time, but I always remember this document, during subsequent stages of my career when I formally got introduced to control plan and whenever I associate with control plan. This only proves that this tool, whatever it might have been named in those days, was part of the good Japanese production practices, from very early times. And, more importantly, it found its place among ‘most important’ documents required for a technology transfer. Subsequently, the automotive industry came up with a set of QS9000 standards, along with which emerged the APQP (Advanced Product Quality Planning) standard. The APQP provides a good framework that gives clarity about the creation of Control plan and its linkages and sequence with respect to other methodologies. The APQP goes through five phases after a pre-planning phase 1. Plan & Define 2. Product Design & Development 3. Process Design & Development 4. Product & Process Validation 5. Feedback assessment & corrective action The Product Design & Development section includes DFMEA and Design verification plans. The Process Design & Development phase includes PFMEA and the proto control plan formation begins here. The Process and Product validation phase includes the Evaluation Methods, MSA, setting up Statistical Process Controls, all of which are inputs into the control plan. The Production Control Plan is an output of the APQP at Phase 4. It is evident from this approach that 'control plan' needs to have plan for: Systemic controls (for instance effectiveness of mistake proofing systems needs to be validated from time to time) Process controls (for example, a thermostat-based temperature control needs to be validated periodically) Human based controls Reliability of measurement systems Reaction plans for any non-conformances If we need to have dependable control plans for all the above, the inputs for the control plan has to evolve from the above-mentioned phases of APQP. Some of you may wonder why control plan should be seen only from the context of a Quality System associated with auto industry. It is for the conceptual clarity that may be obtained from the framework of APQP and how the control plan gets derived. The same concept can be adopted for any industry, including Information Technology services. The control plan will remain as a live document that will keep getting updated in line with the levels of knowledge maturity. I conclude by saying that although the concept of control plan has existed even several decades ago, we have many avenues that have brought very refined clarity on the pre-requisites, building and executing a control plan effectively.
  9. 1 point
    Let me start with my assumption of what it takes to qualify as a Project in Project Management realm , a Project and a Process in Business Improvement or Six Sigma world. Project in Project Management Realm: In a one-liner , we can say a project will have an objective with a definite start date and a definite end date. Eg:1 Converting a meter-gauge rail(track) to a broad-gauge rail can be a project, for Railway engineers. Eg:2 Creating a software product can be a project, for an IT team. Eg:3 Constructing a shopping mall could be a project, for a builder Project in Business Improvement of Six Sigma context: A project will have a goal with a definite start and end dates. That will be accompanied by a strong business case explaining an explicit reason as why this project is needed in the first place and it will highlight the end dates for the various phases that a project might have. Process: In generic terms , we can say that it is a set of instructions/sequence of steps to achieve a particular activity/complete an event. Essentially , every process would have certain parameters which act upon as inputs and then there could be a set of actions or a sequence flow which would be necessary so that there is a tangible outcome which serves our need. That outcome becomes the output which will/can be consumed by other actors(could be another process /events/users/activities..) Eg:1 Setting up Continuous Integration(CI) is a key process as part of Continuous Delivery and Deployment(for delivering your IT delivery rapidly). CI includes multiple steps : 1. Check-out the latest code from the Code Repository (say GIT) and put that into local workspace(Developer's workstation). 2. Do your code changes on the local machine and unit test it thoroughly 3. Post a peer review (and after fixing comments, if any - unit test it again) 4. If everything ok, get the latest code from Code Repository, 5. If no difference found in the version of the code, then push the code to the code repository with proper comments 5. Automatically Build should be triggered (When a change is pushed). 6. If build succeeds, then ensure that your change is successfully working in the Integration box. Now as we see multiple steps are there. The sequence is important to get a successful testing of your functionality which is the outcome from this process. Eg:2 Code Review is a process - Steps involved: 1. Review the code. 2. Check if the code adheres to coding standards and guidelines. 3. Whererever the stds/guideline not followed, provide proper feedback comments. 4. Ensure the developer fixes the comments.5.Ensure functional misses are not there. 6.Ensure same mistakes are not repeated. 7. Ensure all comments are fixed. Now let us first compare and contrast a project in Project Management(PM) realm and a project in Business Improvement(BI)/Six Sigma world. We have compared and contrasted project in PM realm and in BI/Six Sigma realm. Let us now contrast a project and a Process in BI/Six Sigma context. Let me explain these difference with an example. Imagine an improvement project. An IT team's delivery quality is poor. They are getting multiple escalations and they are unable to meet their SLA of <5% defects in a critical application. This is happening for the past 6 months. Now team is doing an improvement project. It is trying to zero in the problem. It needs to fix the issue in 4 months time. Goal is to have <5% defects by 17th June 2019. Now it starts to check its flow from where it has to correct itself. It reviews the AS-IS process. It finds (after doing Value Add activity process) that it needs to improve upon Design Patterns(for Coding), Code Review, Automatate Unit and Functional Testing. These are processes which have their own steps which need to be done so that quality of the deliverable meets the defined SLA as per the goal statement. Now without the processes, the project goal cannot be achieved. At the same time, the processes can be independently achieved but if not tagged to a project, the chance of systematically finding the deficiencies in a process or a need for a new process(if old process is too bad to be modified) would be missed out. Conclusion: From the differences that we saw now, it is clear that process and project in a business improvement/six sigma world or different entities. Having said that there is always a bit of these two words conveniently interchanged especially in Business Process Outsourcing(BPO) industries. Many teams use process to represent what could be possibly called as a project. For instance, those teams might call HR Payroll system as a process, whereas an IT team might call that as a project. One reason it could be because of the fact that BPO bretherens could construe each of the steps in the system happening in a sequential flow. But in general, by and large as the definition says and based on the differences that i articulated above, my conclusion is process and project are two different entities.
  10. 1 point
    The following Japanese words related to “handling of manpower” in production process according to the organizational requirements; Shojinka: This is the Japanese word that originated from the lean manufacturing principles of Toyota. When we translate from Japanese to English, it gives direct meaning of “Various people”, shortly it can be “Vary people". i,e Flexible manpower lines maintain productivity with fluctuating demand. Shoninka: It means “Manpower saving”, by providing machines / equipment in order to free one or two operators: Shoryokuka: It means “ labour savings” partial removal or combining two operations by automation to support the process Productivity = outputs/ inputs i.e it is a measure of efficiency of production line. More often the Shojinka is defined as having to main categories; first, the workers are multi skilled and they can perform in multiple workstations at a time in a production line. The second is, the line should be designed in a way to accommodate or vary people based on the fluctuating customer demand. In simple words; Shojinka can be defined as “ability of a production line can be balanced when the production volume goes up or down" Demand Vs Supply: Shojinka techniques developed based on the Demand Vs Supply and no excess production as they considered as an inventory by deploying flexible machines and man powers. Capacity planning is the process of determining the production capacity needed by an organization to meet changing demands for its products. The capacity is normally developed based on takt time: Takt time: Available production hours per day / customer demand per day (Generally it is calculated on annual basis with full speed of line capacity). When the demand fluctuates, the organizations have some broad questions; · How to absorb the fluctuations in demand that will occur over next 12 months? · To what extent should inventory be used for this purpose · Can demand fluctuations be met by varying size of workforce (Shojinka?) · Why not absorb the fluctuations by changing activity rates and varying work hours( overtime) · Why not outsource to maintain a stable work force and let suppliers change activity rates to absorb demand fluctuations? · Will the organization lose orders if doesn’t meet all demands? Should the organization adopt this policy? Each of these choices determine the moves of the organizations. The organizations will adopt basically three strategies of planning to managing supply · Chase strategy: - when demand fluctuates, the organizations should adjust the capacity to match the demand as close as possible. E.g seasonal business demand like sale of apparels during festivals · Level strategy: - a firm maintain constant capacity over a period of time, irrespective of fluctuations in demand; e.g When more investment or skilled labour required, this strategy will apply · Mixed Strategy: Individual firms devise infinite combinations of the above strategies based on the situation. Shojinka is suitable to apply when organization adopts chase strategy. Flexible manpower line: The production line is designed in such way to meet the changing production requirements: Before designing of any production capacity, the following parameters to be considered; Takt time : Net production time / Customer demand Cycle time : Net production time / No.of Units produced No. of stations / Operators: Cycle time ( Work content) /Takt time In the competitive market, the organization has to prepare some strategy to prevent the business loss and shojinka is a solution for the flexible manufacturing; Calculating Manpower / machines: The following formula will help us to determine the manpower / machine requirements to meet the demand; Overall cycletime / Takt time = Manpower / machines Cycle time is the sum of the processing time to complete one unit of assembly Examples: Case: 1 Overall cycle time: 240 secs Takt time: 80 secs No of manpower = 3 So, we can use the manpower formula and assign no. of operators based on the demand Case: 2 When demand goes down, we can remove the manpower and he can be used in other machines/ assembly lines; Overall cycle time : 240 secs Takt time : 120 secs No of manpower : 2 When the demand low, we reduce 30% manpower and two manpower will produce the output to meet the low demand. Shojinka demands employee training, multiskilling to manage / operate different machines / practical standard operating procedure in place for flexible manpower line. Advantages of Flexible manpower line: · Avoid overproduction · Better usage of capacity · Smooth material movement · Kaizen culture Disadvantages of Flexible manpower line: · Design of production process is complicated as the forecast are not realistic · Require high skilled operator · Not suitable for small, medium size industries Conclusion in my purview: At the present time, most of the industries look for outsourcing when the demand peaked up. The peak demand may not be long-lasting, as the demand lows they withdrawn the order from the supplier. This will affect the supplier relationship in long term. However, organization should design flexible manpower line to the peak volume and if the demand is lower, the assigned manpower can be used in another production area, provided if they are competent. But practically it is complex in real time production situation. Industries, normally extend their work hours to meet the peak demand and cut off the extra hours if the demand goes down. If the forecast is realistic, the cell design is flexible to manpower, Shojinka is a best tool to apply.
  11. 1 point
    "Great session..very informative." -Archana Krishnappa, VP, HSBC Data Processing India Pvt Ltd
  12. 1 point
    Six Sigma is a powerful methodology that can be used to improve business processes. It is a structured approach to problem-solving that can be applied to any process - manufacturing, sales, marketing, IT, BPO, accounting, purchasing, you name it. All processes have variation. Variation is the cause of all evil - it leads to defects and customer dissatisfaction. Six Sigma methodology can be used to reduce variation from any source and thus improve costs, quality, and hence customer satisfaction. The standard methodology that is used to improve existing processes is called DMAIC. The acronym DMAIC stands for Define - Measure - Analyze - Improve - Control. If you think about it - this methodology is common sense. Before we start working on a problem, we need to have a good definition of what is the problem, why we are working on it, where is the pain area, what is in the scope of the project etc. All of these are accomplished in the Define phase. Secondly, in the Measure phase, we are interested in ensuring that the data used for further analysis is free of measurement errors. Six Sigma is about making decisions based on facts & data. If the data is inaccurate, we would end up making the wrong decisions. Hence, the measured phase ensures good data. Before making any improvements, it is also important to establish a baseline so that we can clearly communicate the benefits obtained from our project to other key stakeholders. The next phase, Analyze, is all about making the hypothesis and using data to either prove or disprove our hypothesis. We make the hypothesis about what is causing the problem and then establish the real root causes. The fourth phase, Improve, focus on getting the best possible solution to solve the root cause of the problem. The solution is optimized and any potential failure modes are resolved before the solution is deployed in the real world. The last phase, Control, is all about ensuring that the solution is sustainable in the long run. Any financial benefits obtained from the project are also quantified. Finally, the improved process is transitioned over to the process owner. As we can see from this paragraph, any problem can be addressed using this structured approach. Here are some things that should come to your mind when people talk about Six Sigma: Business Process Improvement Methodology 3.4 defects per million opportunities Customer focused Uses facts & data Quantify financial benefits Structured improvement approach
  13. 1 point
    Dear Sandeep, Robotic Process Automation (RPA) is there in the industry for quite sometime now but more popularized in last 3 or 4 years. Considering the competition in every industry, every organization is trying to keep their operating cost low and provide the right product or service with right quality to the customers. It has become mandatory to every organization to search and implement new methods of production to improve the margins and quality at same time. RPA is becoming new buzz word or new method to talk and implement as every customer, organization, Industry are looking for change and a quick change. As a Lean Six Sigma Practitioner, our role has become more significant during initial stages of RPA implementations. In a simple way, A LSS Practitioner can identify and suggest the right opportunity to implement RPA by following structured method. Few debates are there saying that there is no involvement required from LSS Practitioners in RPA implementations as these would be pure technology driven. At the same time, I have observed that many projects are not able reach their end objective on time (Please read the line again... NOT ABLE TO REACH THEIR END OBJECTIVE ON TIME) due to lack of structured methodology during initial phases. A Lean Six Sigma Practitioner can support/add value to make the RPA projects success as below. 1) Understanding the objectives and preparing the business case for improvement 2) Establishing right metrics to measure the improvement 3) Preparing detailed VSM to identify highly manual repetitive time consuming process steps. 4) Estimating the benefits by performing cost vs. benefit analysis (All the processes may not yield greater ROI but many qualitative aspects to consider) 4) Design/Re-design the process to make it suitable for RPA (Please note that automating the process As-Is may not give desired results) 5) Standardize the input and handoffs 6) Support the RPA developers with suitable functional guidance 7) Tracking and Monitoring the projects with robust governance models (Depending on PMO structure in the organization) 8) Evaluating the outcomes (Metrics, Benefits) post implementation Depending on organization's project management structure, LSS Practitioner can have greater role to play in implementing RPA projects. Few organizations have started RPA consultant roles to manage all the activities mentioned above and few are managing with existing LSS teams. Fundamental method would be the same irrespective of organization structure however, LSS practitioners will have additional edge of LSS methods and concepts to get quick results. Hope this helps.
  14. 1 point
    There are two primary methodologies in Six Sigma: DMAIC DFSS The Six Sigma DMAIC methodology described in the post earlier 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.
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