antara

Effective means doing the right thing and efficient means doing the things right. Example : Average of field visit count of two agents of an insurance company are coming 6 visit per day. Target is also 5 to 6 visit per day. Then both the agents will be considered as effective. But the average of conversion of each visit to sales of the 1st agent is 3 clients per day and for the 2nd agent is 1 client per day. Then 1st agent will be considered as efficient

FMEA is highly effective for risk analysis but this technique has few limitations. Rating of severity and occurrence are subjective and depends on users. Therefore analysis from different sources for same process may give different risk priority number. External influences that causes safety issue are often overlooked. Identification of failure mode is discussion based brainstorming activity. Any information unnoticed may cause failure.

Outliers are individual readings of data that differ very greatly in value relative to most other values in a set. Why they are important is because depending on just how different they are they might disproportionately bias the results of a statistical analysis of the data set as a whole. Identification of potential outliers is important for the following reasons. An outlier may indicate bad data. ... Outliers may be due to random variation or may indicate something scientifically interesting. example, consider this set of weight taken 10 times.15, 15, 16, 16.5, 15, 15.5, 25, 16, 15, 16 (kg). A simple average of the entire set of readings is 16.5 kg. That’s a straightforward mathematical perspective taken without questioning the validity of any of the readings. But considering them more closely, wouldn’t it seem odd that when all the readings hover around the 15 or 16 kg mark, there’s one reading of 25 kg? It’s a sudden spike. Do things like that usually happen? If we exclude that particular reading from our calculation, the average changes to 15.55 kg, which is almost a whole kg lower. A number of additional questions arise: Is it possible that the reading of 25kg is the result of a measurement error? A faulty weight machine perhaps? Or is it possible that the reading was real and correct, but that there were extraordinary factors that caused it to be so different that time? Should we include the reading of 25 kg while computing the average or should we exclude it? What if we had taken a 100 readings instead of just 10? Would we have had more readings of 25, or between 15 and 25? Is there a chance there could have been any readings of above 25? What if there was no reading of 25, but there were two other significantly different readings of 20 each? How different does a value have to be in order for it to be considered to be so different that it could distort the result of a statistical analysis? If we consider the 25 kg reading as an outlier, would other analysts also do the same with this set of data? If we were to use such data over time in a machine learning system would it delay or retard its achievement of maximum effectiveness? Is it possible to have a single generic method by which we can decide whether a value should be considered to be an outlier or not? The decision about whether or not a data value should be treated as an outlier is at least to some degree a subjective one. The decision may initially be based on some set of objective identification rules using a standard mathematical technique, but must then be reconsidered further in a subjective manner that questions the data (and also the entire data set) within the context of its business meaning. The same subjectivity would need to be applied in considering the results of any statistical analysis run on the overall data set, with an awareness of whether or not the outliers were included in the analysis. It is because of all the questions that arise that it is important to be able to identify outliers and evaluate them fully before deciding how to treat them. There are a number of various mathematical methods to identify outliers, starting with John Tukey’s IQR or box plot method, the simple z-score method, and going on to others that may be more robust in the face of various factors that might stress the analysis in any way. It is important to have both a statistical feel as well as qualitative business feel to the data so that the most appropriate choice of method is made to identify and treat the outliers.

Removing wastes always help to improve process. few examples: 1. Cross utilization of skills always help to reduce wait time where dependency of different departments are high. 2. Setting some alert like less digit while entering mobile no etc, always help to reduce rework. 3. Keeping a track on product and based on the requirements develop product always help to reduce over production.

I think when spread exceeds customers's specification limit, then controlling deviation become more important than central tendency.

Voice of the Customer studies typically consist of both qualitative and quantitative research steps. They are generally conducted at the start of any new product, process, or service design initiative in order to better understand the customer's wants and needs. But this is also true that overemphasis on VOC be detrimental to business. We have a diverse customer base, and if a client approaches us with a suggestion that hasn’t worked or won’t work for our other clients, we don’t take the bait. If we make changes for that client then there is possibility that we dissatisfy others and hence loss in business.

Sequential series for process mapping: SIPOC : The importance of the SIPOC is that it shows, in very simple terms, what the process accomplishes while identifying the key players. High Level Map : High Level Maps typically don’t require a deep knowledge of the process, so we can often construct them with the assistance of managers. Detailed Map: We don’t normally need to see the entire process in detail, but there may be some parts of the process that require a Detailed Process Map. This is especially true if there are a number of problems with that step. Relationship Map: Relationship Maps are technically not process maps since they don’t detail the work done, but they do show the participants and how materials, paper or information flows between them. Swimlane Map: This Swimlane Map is especially helpful when establishing work instructions and training for the new process because it makes each participant’s role explicit. Value Stream Map: Value Stream Maps are typically used in Lean applications where we are interested in either showing pull scheduling or opportunities to do pull scheduling. They are often detailed and difficult to read.

A correction is any action that is taken to eliminate errors. Corrective actions are steps that are taken to remove the causes of an existing errors or undesirable situation. Preventive actions are steps that are taken to remove the causes of potential errors or potential situations that are undesirable. Repairing of any machine on a production line which has given error is correction. Timely maintenance of machine in regular basis is preventive action. Replacement of a machine that has a high error rate is corrective action.

The check sheet was designed to be very simple. Because it was meant to be a tool for data recording which itself is quite simple and the check sheet was meant to be used by the people on the shop floor. It would not be expected from them to be able to deal with complexity. Hence there was an inherent need for designing the check sheet the way it is. Check sheets have now become obsolete. They have been replaced by BPM software. This has enables more complex data to be automatically recorded. The process now depends neither of the intelligence of the human nor on the reliability of the check sheet. Data is now automatically recorder and can be sorted in whatever manner required within few seconds. Many software even produce the data in a ready to use graphical format enabling further convenience for the users. Other than very rural area where technology can work properly we can replace check list completely

False Alarm and Missed alert both have negative impact. False alarm may increase the rejection % and may increase the unnecessary rework just because of confusion. It may directly impact on cost as well as time. At the same time missed alert may increase the probability of accepting wrong or defect products. Which directly impact on customer satisfaction and brand value. For any low cost product, if we want to avoid any rework then certainly we will not want any false alarm. Similarly for any critical, high value process like banking or manufacturing of air craft etc, we will certainly not accept any missed Alert.

TAKT time is the maximum acceptable time to meet the demands of the customer. You can consider it as start time of any production to start time of another production. Also we can say TAKT Time is the speed with which the product needs to be created in order to meet the requirements of the customer. TAKT Time = (Net Time Available for Production)/(Customer’s Daily Demand). It will help to take the decision on what will be the expected speed of completing the task and also human resources details also. I believe it helps us to take strategical decisions as well as tactical decisions.

FTA helps to know the causes of failure. It is a top down failure analysis. In this analysis system, series of step by step events happen to test the system reliability. It also helps to identify the impact of human errors. The logical relationship of events are shown by logic symbols or gates. It is very useful in software development field, safety analysis etc. It is not very useful for multiple top events. Because for each top event, seperate FTA required. This increases the complexity.

Presence of process is never be roadblock in the effort towards creating any new design. Its true that innovation happens purely by accident. Six Sigma never restricts to think nonlinear. Once a nonlinear idea comes, It gives the scope to do risk analysis beforehand. It gives the scope of testing, verification etc to produce a reliable design. As it run through set process, hence help to produce capable product and hence chances of rejection from customer is less.

According to me measurement is important. It is very difficult to manage any abstract thing. It is necessary to define target or expected outcome. If Outcomes are defined then measurement is required to deliver it. I also believe everything can be measured, maybe we must define the parameters and at the time of defining parameters we should think nonlinear.

Personal Excellence is all about the excellency in our own life. It helps us to achieve more meaningful life in terms of making balance in our relationship, emotional intelligence, our professional career and to make our life more productive. Process Excellence is a continuous improvement process to increase productivity and quality and at the same time to reduce cost with minimum variation. It is all about effectiveness and efficiency of a process. Operational Excellence is something within the organization where all the activities follow some define process flow. It helps to control disrupt in operation or process due to any changes in some interlinked department or process. It ensures that employees of the organization understand the work flow and help to create the culture to practice the standard operational procedure (SOP) and the organization values. Here the focus is customer. So we can say end to end process for better customer satisfaction with low cost. Business Excellence is something where we consider the organization as a whole, consider all the stakeholders and it helps to achieve business goal of the organization. It starts with business strategy, communication between different stakeholders and departments, then to have define process flow, cascading it in the ground and then internalization and ope-rationalization of the strategy. A organization can have very effective and efficient process and operation but poor communication, weak strategy, loophole in the change management system will not help to achieve business goal and hence to achieve Business Excellence.