Shraddha Sequiera

Inventory turnover ratio is a financial ratio showing the number of times a company turned over its inventory in relation to its cost of goods sold in a specific period of time. Generally the annual year of the company is taken into consideration for calculation of inventory turn ratio. It can help businesses guage and aid in effective decision making on price, marketing cost, purchase of inventory. A low inventory ration would indicate weal sales or excess stock of inventory and a high inventory ration would indicate good sales however may lead to insufficient stock of inventory. The formula for Inventory Turnover Inventory Turnover = Cost of goods sold/ avg value of inventory The inventory turnover ratio measures the amount company generates sales from its stock. This helps the business identify how to increase sales or improve the marketability of certain stock or the overall inventory mix. It increases sales leading to higher profitability Higher sales will lead to fresh stock and new product offerings for the customers High customer satisfaction Increase in employee morale to enhance and boost sales Creates brand image and good reputation Enhanced customer loyalty Improves financial position of business Reduces cost of storage and warehousing Reduces other operating cost Excellent revenue and turnover

A waterfall chart help us identify how positive or negative values in a data series contribute to the total. It helps to visualize a starting value, the positive and negative changes made to that value, and the resulting end value. It begins with the starting value and the last column is the end value. The floating columns between them are the contributing positive or negative value. Waterfall chart is also known as bridge chart. Waterfall chart can be created using Excel or Powerpoints. We need to have the data points listed down in Excel for which the chart needs to be created. EXCEL Select the desired data Under Charts option Select “Waterfall” A waterfall chart is created. You will be able to edit the Subtotal and Totals. You will also be able to display or illustrate the data if there is negative impact but clicking on “Negative Range” It allows you to change the preset colors to the colors of your own choice Waterfall chart is an effective to display changes in the quantitative value over time and can help in Business Excellence in Quantitative analysis Quantitative data is objective in nature and can be measured. Qualitative data is further bifurcated as Nominal, Ordinal and Binary. Since Quantitative data focuses on measurement it helps identify patterns and accordingly make predictions. It helps in sampling and deriving results based on population and identifying variations and standard deviations in the data. Waterfall chart help in identification of these patterns through graphical representation of data.

Bayesian Test interprets probability as a measure of the belief or confidence that an individual might hold regarding the likelihood of an event occurring and the prior beliefs about an event will likely change when new information is revealed. It not only considers the likelihood of the occurrence but also consider the beliefs and experiences that an individual may hold which may be fair. This helps in arriving at a hypothesis basis historic trend and real life experiences and beliefs which is more practical. The Frequentist inference interprets probability as the frequency of repeatable experiments and the gathering of information. This may be used when we have existing data however the inferences may be close to the sample population and would be dependent on the current data sample that the person may have selected. Frequentist inference relies on P-value and it is assumed that null hypothesis is true however Bayseian approach is based on beliefs based on new information derived at the time of conducting the hypothesis. Lets take the example of tossing a coin As per frequentist approach the likelihood of heads on the coin will depend on the sample and heads being received as per sample data v/s actual hypothesis. Parameters remain fixed and data is random since its based on frequency of repeated events As per Bayesian approach the likelihood of heads repeating 90 out of 100 times could also mean that there is something to do with the flipping of the coin or the coin itself. Hence the parameters are random but the data is fixed and probability depends on degree of certainty about values. Whilst frequentist method may be used for hypothesis testing, Bayesian method can be alternative method since the inferences are not based only on sample data but it also takes into account observations during hypothesis and considers both the null and the alternate.

PMP DMAIC Comparision Project phase Typical artifacts Project phase Typical artifacts Initiation Business case Define phase Project Charter PMP uses various documents in the initiation phase DMAIC model uses a Project charter which covers business case, vision and team details along with emphasis on dollar saving or impact it would make for that specific project project. Project vision statement Value Stream Map VSM help us understand the entire process and understand the current process v/s future state that we anticipate it to be Project charter Roadmap Team charter Planning Assumption log Measure Process Maps Capability Analysis Pareto chart PMP may have a list of artefacts to be created but for DMAIC project the artefacts list is fairly simple. During the planning stage of PMP and Measure stage of DMAIC we create documents to record the activities performed, ability of the process to meet the client standard and record any variations Risk register Issue register Change log Stakeholder register Comms management plan Release plan Scope management plan Test plan Quality plan Logistics plan Work breakdown structure Analyse & Improve Root Cause Analysis Failure Mode and Effect analysis Variation charts Kaizen events The data gathers in the measure phase to used for further analysis to identify the main causes and assess any risk that could be mitigated or accounted for. We will aslo use the data to assess the level of variations in the X that we have which can be tracked through variation charts, and other data points dereived from baseline studies Product breakdown structure Organizational breakdown structure Risk breakdown structure Budget baseline Milestone schedule baseline Scope baseline Performance measurement baseline Gantt chart Requirements and requirements traceability matrix Execution Dashboard Flow charts or process maps as needed MOU, contracts and agreements (but could be earlier in the life cycle depending on the type of vendor) Monitoring and Control Quality report Control Control plan 5 S Poka Yoke Handover documents The control plan works hand in hand with the quality and risk reports that are shared during the Monitring phase of PMP. A step further to DMAIC will be how do we address these and pu the necessary contrls on place to sustain consistent performance. Once the process is capable and stable the project is decomissioned and handover to the relevant stakeholder is initiated. Risk report Status report Ad hoc stakeholder reports Closure Project closure document Handover documents

A p-value is a statistical measurement used to validate a hypothesis against observed data. It measures the probability considering the null hypothesis is true. It is used to determine the confidence levels in a hypothesis testing and is generally considered statistically significant. If P value is low then then null hypothesis is invalid but if p is high null will have an impact. High p-values indicate that that there is no strong impact on the population. Effect exist however the impact on population is not so high. the threshold for p-value is 5% The concept of the False Discovery Rate (FDR) was used when multiple test are conducted. The FDR is the ratio of the number of false positive results to the number of total positive test results. A p-value of 0.05 would mean that 5% of all tests will result in false positives. An FDR-adjusted p-value which is also called q-value of 0.05 indicates that 5% of significant tests will result in false positives. In other words, an FDR of 5% means that, among all results called significant, only 5% of these are truly null. We would use Q value when false positive it high and there is significant difference but in reality none exists. so if we set the cut off to 5% there is possibility that we may not choose the right decision. An FDR adjusted p value would mean that we are willing to accept 5% test of all false positives.

Grubbs' test is used to detect a single outlier in a univariate data which follows a normal distribution. If you suspect more than one outlier may be present, this test may not be helpful. It considers the min and max value when detecting an outlier. Grubbs test can be used to detect if the max or min data is an outlier. As a part of analysis, it is important to check the outliers as this may impact the mean and standard deviation. An outlier should be detected and corrected however Grubs test may not be a robust technique to determine an outlier. Box plot instead can be used a excellent tool for detecting location and variation in a data set. It helps in identifying the middle 50% of the data, Lower quartile (25th Percentile) and upper quartile (75th percentile). Hence it help identify the median and extreme points(outliers). A box plot help u in comparison between various data sets and identifies the significant factor. It will help you read the location and variation between different groups and identify variation. Multiple data sets can be compared hence it helps you work with large data sets.

Six Sigma expert specializes in efficiency and management as they would always look at maximizing output, minimizing cost whilst not compromising on Quality. A mater black belt acts as a leader and is able to develop and design the path of internal leaders, other six sigma specialist and management as a whole. He acts a guide in right selection of project until its executed and delivered with quantifiable impacts. The various roles that a Master Black belt can opt for Project Manager Strategy building & Management Business Excellence Quality Management Change & Transformation roles Process Excellence/Re-Engineering roles Risk and Compliance roles Re-Engineering and Transformation roles can be more challenging High Risk May not be replicable Each company will have their own challenges & shortcoming Different Priority for Leader in Management Resistance to Change Business Excellence & Quality Management can be more rewarding Not limited to a specific Industry Free Lancing is possible Helps in increased profits, CSAT levels, Employee satisfaction levels Encourage innovation

Lean accounting means aligning your lean practices with a value which will help you quantify your success. It not only focuses on cost reduction and control which was followed traditionally but also focused on company performance and overall position. Lean accounting measures performance rather than focusing on transaction-based cost analysis, reduction and control. A box score is a simple one page summary of the key performance metrics for each value stream. Box scores can be created and configurable easily and simple and easy to understand which requires very low maintenance as well. Benefits of Lean Accounting Lean accounting will continue to focus on eliminating waste which is one of the core Lean principles. However along with this it will also assign value like increase profitability, cash flow or enhanced customer value Lean accounting helps with real time information like identifying prices, highest selling items, comparing revenue with expenses so that the team can immediately understand the consequences Empowers people with better decision-making skills and promotes a culture of Lean and continuous improvements. Lean Accounting principles are in line with GAAP and external reporting and regulation which makes it a more reliable practice.

Process sigma for discrete data Defects per million opportunities (DPMO) of a process is the total defects / total defect opportunities, multiplied by 1 million Defect 7, Opportunity = 5, Unit : 3 Defect Per opportunity = Defect/(Unit X 1000000) DPO = 7/(5 x 3) = 0.46 Excel = normsinv(0.46)+1.5 = 1.399 If the Defect is 0 , then DPO = 0/(5X3) = 0 Process Sigma for Continuous Data For continuous data we need to know the Cpk Upper Specification Limit : 50 Lower Specification Limit : 25 Task needs to be completed with 10 sec Mean is 8 sec, Standard Deviation is 5 Cpk = USL – X/3 Sigma Cpk = 50 – 8/3*5 = 2.8 Process Sigma = 3X2.8 The main aim of Six sigma is achieve 3.4 defect per million opportunities. Its not possible to attain zero defects however we can minimize or keep the defects minimum to achieve process stability.

Lessons learned is the learning gained from the process of performing a project. It’s extremely important to as it mentions the positives and negatives of a project. It acts as a reference point for future projects which can help us manage projects in a better way, Unfortunately, capturing lessons learned and further sharing is often given least priority or considered optional. The reasons are mentioned below · Commitment from Top management · Lesson learned should be part of project management process and an expected deliverable and awareness for the same should be created for adherence right when the project begins. Unawareness among team member to capture lesson learned will lead to loss of important information. · Improper template to capture information · Turnaround Time/Deadline to complete the project may also lead the team to ignore the lesson learned activity · Improper software Tools/IT system to capture information · Inability to get meaningful report from data entered.