Mona Bhandari

I feel that hiring for anyone for any managerial post is completely organization based. It totally depends upon the candidates caliber and the efficiency to convince the interviewer onto the project carrying or carried out by him.

Suppose the tolerance limits on the dimension are 5.000±0.012, i.e. 4.988 to 5.012. Data collected from the process during second shift indicates that the process mean is 5.000 and its standard deviation sigma=0.004. ±3 sigma fits inside the the tolerance because ±3 sigma= ±3x0.004= ±0.012. Capability Cp = Cpk = 1. The process mean doesn't remain constant. The process mean may shift 1.5 sigma to the right or 1.5 sigma to the left. If we assume a 1.5 sigma shift to the right, the yield is the area under the normal curve to the right of -1.5 sigma or about 0.9332. Suppose if the process variation is reduced so that sigma= 0.002. Now ±6sigma exist between the tolerance limits and the process can be called 6sigma process. To calculate the yield for the six sigma process, we allow the mean to shift ±1.5sigma. Suppose the mean shifts 1.5 sigma to the right so the yield is the area under normal curve to the right of -4.5 sigma which turns out to be 0.9999966. Defect level =1- 0.9999966= 0.0000034 or 3.4 ppm. The mean may not shift exactly 1.5 sigma on each side and no process is truly normal to the sixth decimal.

VOICE OF CUSTOMER: These are the needs, wants, expectations and what they prefer in both spoken and unspoken words. The voice of customer can be internal or external. VOC can be captured on reactive and surveys, interviews, research, evaluations, feedback and meetings. VOC metrics Customer satisfaction Net promoter score Performance Evaluations Help desk support calls. VOICE OF BUSINESS: VOB are the needs, wants, expectations and preferences, both spoken and unspoken of the people who constitute the business like the shareholders, officers or other involved in corporate governance. It can be obtained from financial market analysis, competition analysis. VOB metrics: ROI( Return -On- Investment), Percentage income from returning customers Shareholder Equity. CONFLICT BETWEEN VOB & VOC The company does business to make profit and accomplish greater goals but not at the cost of the customer. The customers prefer best products at cheaper rates. In order to synchronize between the VOC and VOB mapping of processes and correcting the system that deliver value to our customer.

Tribal Knowledge is an unwritten information that is not commonly known by others in the organization. METHODS OF UNLOCKING TRIBAL KNOWLEDGE: Shared desire to achieve state of operational alignment An effective and efficient management of information Cross functional organizational behaviors that form cohesive and comprehensive methodology Clarify information needs and develop models for information and activity flow. Identify integrated set of collaboration tools. To gain a deep understanding of the organization's nature domain. METHODS OF CAPTURING TRIBAL KNOWLEDGE: The purpose of capturing tribal knowledge is to raise awareness of the problem, symptoms, it's causes and outline of a solution. To outline a problem a problem statement is generated and 1. IDENTIFICATION OF POTENTIAL EMPLOYEES 2. IDENTIFY THE AVAILABLE KNOWLEDGE 3. DOCUMENT THE REQUIRED KNOWLEDGE 4. CONFRONT THE KNOWLEDGE GAP a. Minimize the knowledge gap between the old employee and the new employee of the organization. b. Benefits the new employees by updating the knowledge and make them more efficient. METHODS OF HARNESSING TRIBAL KNOWLEDGE: Harnessing tribal knowledge: 1. COLLECTION: GROUND WORK Incorporating concepts in context to issue from knowledge support centers. 2. SORTING: HOW TO DO: Segregate critical data from massive volume of information data. 3. ORGANIZATION: WE To put forward logical frameworks in place. 4. CODIFYING: FOR Mastered the collection Segmentation and storage of critical data.

In case the excellence operator doesn't utilize the concept of rational sub grouping than It would incorporate the variations from the different streams. Identification of corrective actions once an out of control condition cannot be done. their would be inconsistency of data from processes.

Sponsor's are high level or senior business leaders. QUALITIES OF SPONSOR Proactive motivator who helps in growth of the organization and his own self. Help in defining the team's objectives and articulating the problem statement. Validating business case in the project charter. Act as liaison between the team and senior management. Accelerate decisions at critical times of the project.

Kano Model has three requirements: Basic Needs: Allow an organization go get into the market. Performance Needs: Allows the organization to sustain in the market. Excitement Needs: Allows the organization to excel, power of excellence. BASIC NEEDS: Expected features or characteristics of a product or service. They are unspoken words which are expected by the customer/patient. If not fulfilled causes dissatisfaction to customer/patient. For Example: Cleanliness of the room. Bed preparation. Effective Communication Patient uniform. PERFORMANCE NEEDS: Are spoken needs that increase or decrease the customer/patient performance. For example: Admission and Discharge time. Waiting time in OPD Breakdown of equipments Average length of stay Healthcare Associated Infection Internet Access EXCITEMENT NEEDS: An unspoken and Unexpected feature that impresses customer/patients and earn an extra credit to the organization. For Example: Hospital integration like App for hospital wide services. Play area for the kids Online medicine indenting and dispatching Excitement Needs – Unexpected features or characteristics that impress customers and earn the company “extra credit.” These needs also are typically “unspoken.” Think of the Doubletree Hotels. Those who stay there are delighted by a freshly baked, chocolate chip cookie delivered to their room during turn-down service. Expected features or characteristics of a product or service

Statistically significant means that we are very sure that the statistic is reliable. It is a statistical term that gives the surety of a difference or relationship exists. For example: Suppose we give 1000 employee an IQ test, and we are ask if there is a significant difference between male and female scores. The mean score for males is 98 and that of female is 100. We use independent groups t- test and find that the difference is significant or the 0.001 level. The difference between 98 and 100 on an IQ test is a very small difference.., which is not important After finding a significant relationship, it is important to evaluate its strength which could be weak or strong; large or small. This depends upon the sample size. ONE TAILED OR TWO TAILED SIGNIFICANT TESTS: One tailed or two tailed significance depends on hypothesis. ONE TAILED SIGNIFICANT TEST: When the hypothesis states the direction of the difference it is said to be one tailed significant probability test. Example: females will score significant higher than males in test. Blue collar workers will not buy significantly more product than white collar. In the above mentioned examples the null hypothesis predicts the direction of the difference. TWO TAILED SIGNIFICANT TEST: A two tailed test would be used to test these null hypotheses. For example: There is no significant difference in test scores between females and males. There is no significant difference between blue collar and white collar workers. THE ONE TAILED PROBABILITY IS EXACTLY THE HALF THE VALUE OF THE TWO TAILED PROBABILITY.

In healthcare sector; our ultimate goal is to fix the problem, reduce risk, and keep our patients, patients' families and safe safe. Their is a specific correlation between the Incident and the related Causal Factors, the Root Causes for which corrective actions are recommended. Once we have the root cause, we can work on the corrective actions to fix the root cause problem. A cause that produces an effect, or that which give s rise to any action, phenomenon or condition for example: if a change in X produces a change in Y than the X is said to be the cause of Y. Every cause itself is the result of some prior cause or causes. Two variables may be found to be causally associated depending on the study. If two variables are found to be either associated or correlated, that doesn't mean that cause- and -effect relationship exists between the two variables. In conclusion, if we choose the corrective action first followed by a cause that justifies, in that their is a specific relationship between them.

The Voice of Customer is the process for capturing customer- related information. This process is proactive and continuously innovative to capture stated, unstated, and anticipated customer requirements, needs and desires. A mistake occurred on a small scale is acceptable by the customer. There are situations which aren't acceptable and are detrimental to the business. They are: Long waiting time. Long response time. Poor attention. Lack of orientation about the company. Unprofessional and impersonal interactions. For Example: Services generated in the hospital. Waiting for room allotment. Lack of timely response from nursing staff.

The confusion about continuous data and attribute data is the percentage data. In true sense, percentage data is discrete because the underlying data that the percentages are calculated from is discrete. For example: the percentage of defects is calculated by dividing the number of defects(discrete count data). In practice, percentage data are often treated as continuous because the percentage can take on any value along the continuum from 0 to 100%. Adding to it, dividing a percentage point into two or more parts. Discrete data are easy to collect and interpret. Continuous data senses variation. For example: Speeding of car at highway with a speed limit of 70 miles per hour. If we collect continuous data we have more information. If we use discrete data, we only know whether someone was speeding over the speed limit of 70 mph or not speeding i.e at or under 70 mph. For Example: knowing that travelling 70 mph gives a different understanding of their speed than knowing that they were travelling 90 miles per hour, even though both would be classified as speeding using is discrete data. It is advisable to collect continuous data in practice and convert it into discrete as per the threshold value. In the above mentioned example, we would collect: Continuous Data- how fast was the automobile travelling in miles per hour. Later determine whether the result is speeding or not speeding by comparing the actual speed to the threshold of 70 miles per hour

DEFINITIONS OF CORRECTION; CORRECTIVE ACTIONS; PREVENTIVE ACTIONS CORRECTIONS: Action to eliminate the detected non conformity. It's taken immediately. It addresses to short term need. For Example: In case of fire. It would be ludicrous to go for RCA. Once the initial correction is implemented,there is time to do RCA and implement corrective action and follow with verification of the effectiveness of the RCA. CORRECTIVE ACTION: Action to eliminate the cause of a detected non conformity to prevent the recurrence of the non conformity. It addresses to long term solution. For Example: Administration of chemotherapeutic drug on hold as the transcription of the dosage was not correct. PREVENTIVE ACTION: is avoiding the initial occurence of the non conformity by proactively implementing improvements. It may result i.e from trending of a process data, of analytical data, of audit findings, trending of root causes for non conformists or complaints. For Example: Double check prior to transcribing the chemotherapeutic drug. Preventive action is taken to prevent occurrence whereas corrective action is taken to prevent recurrence. There are instances whenin correction is required over corrective action and preventive action. We need to make sure to qualify the boundaries for issues requiring informal, formal, immediate or long term actions. For Example: Maintenance department responsible for water testing and documenting of RO plant. Hospital staff admitting in the hospital due to consumption of water resulting in ill health. An immediate replacement of water prior to any further testing is done. A correction of issue is important.

A Check sheet is an easy custom designed for quick, easy and efficient recording of desired information which can either be quantitative and qualitative data. Check sheets are being replaced by modern Business Process Management Software which enables more complex data to be recorded automatically. The process is now neither dependent on human intelligence nor on check sheets. The data recorded is arranged in whichever manner required which are ready to use even in graphical format enabling convenience to the users.

Sigma Level and the Cost of Quality Sigma Level DPMO Cost of Quality as Percentage of Sales 2 298,000 More than 40% 3 67,000 25-40% 4 6,000 15-25% 5 233 5-15% 6 3.4 Less than 1% Assuming that the average performance of a company is 3 sigma, 25 percent to 40 percent of its annual revenue gets chewed up by the cost of quality. Thus, if this company can improve its quality by 1 sigma level, its net income will increase hugely.

Common Causes of Variance Referred to as ‘Natural Problems', ‘Noise' and ‘Random Cause' was a term coined by Harry Alpert in 1947. Common causes of variance are the usual quantifiable and historical variations in a system that are natural. Though a problem, they are an inherent part of a process. This kind of variance will eventually creep in, and there is nothing you can do about it. Specific actions cannot be taken to prevent this failure from occurring. It is ongoing, consistent, and predictable. Characteristics of common causes of Variance are: Variation predictable probabilistic Phenomena that are active within the system Variation within a historical experience base which is not regular Lack of significance in individual high and low values. This variation usually lies within three standard deviations from the mean where 99.73% of values are expected to be found. On a control chart, they are indicated by a few random points that are within the control limit. These kinds of variations will require management action since there can be no immediate process to rectify it. You will have to make a fundamental change to reduce the number of common causes of variation. If there’s only common causes of variation on your chart, your process is said to be ‘statistically stable'.When this term is applied to your chart, the chart itself becomes fairly stable. Your project will have no major changes, and you will be able to continue process execution hassle free. Examples of Common Causes of Variance Take, for example, an employee who takes a little longer than usual to complete a certain task. He is given two days to do a task and instead he takes two and a half days; this is considered a common cause of variation. His completion time would not have deviated a lot from the mean, since you would have had to consider the fact that he could submit it a little late. Here’s another example: you estimate 20 minutes to get ready and ten minutes to get to work. Instead, you take five minutes extra getting ready because you had to pack lunch and 15 additional minutes to get to work because of traffic. These would be Common Causes of Variance. Other examples that relate to projects are inappropriate procedures, as in the lack of clearly defined standard procedures, poor working conditions, measurement errors, normal wear and tear, computer response times, etc. Special Causes of Variance Special Cause of Variance, on the other hand, refers to unexpected glitches that affect a process. The term Special Cause of Variance was coined by W Edwards Deming and is also known as an ‘Assignable Cause'. These are variations that were not observed previously and are unusual, non-quantifiable variations. These causes are sporadic, and they are a result of a specific change that is brought about in a process resulting in a chaotic problem. They usually relate to some defect in the system or method. However, this failure can be corrected by making changes in a certain method, component or process. Characteristics of Special Causes of Variation are: New and unanticipated or previously neglected episode within the system This kind of variation is usually unpredictable and even problematic. The variation has never happened before and is thus outside the historical experience base. On a control chart, the points lie beyond the preferred control limit or even as random points within the control limit. Once identified on a chart, this type of problem needs to be found and addressed immediately so as to prevent recurrence of it in the project. It is not usually part of your normal process and occurs out of the blue. Examples of Special Causes of Variance An example to better explain Special causes: you are driving to work, and you estimate arrival in 10 minutes every day, but, on a particular day you reach 20 minutes later, since you encountered an accident zone and were held up. Examples relating to project management are if the operator falls asleep during the execution of your project, or a machine malfunctions, a computer crashes, there is a power cut, etc. One way to evaluate a project's health is to track the difference between the original project plan and what is actually happening. Use of control charts helps to differentiate between the Common Causes and the Special Causes of Variation making the process of making changes and amends easier.