Gopal Menon

Advantages of CUSUM chart over Individual, X BAR chart 1. CUSUM chart is used to detect smallest variation from target value. This chart is used where sub grouping is not required / feasible, however, there is a need to detect very small shift (less than 1.5 sigma). The biggest advantage is that the user can determine the degree of shift that needs to be detected This type of chart can also be used where the process average is expected to naturally shift, for e.g. chemical industries 2. This chart is a better choice when the objective is to control the data point to a target value by making necessary process adjustments than plotting an X Bar or Individual chart and then trying to identify special causes for variation Example using data (reference source from Cumulative Sum Chart (CUSUM) - Six Sigma Study Guide) Minitab or other SPC tools can auto calculate the upper and lower CUSUM for all values CUSUM chart shows that the process is deviating from target from sample 13, whereas, the below IMR chart shows that process is in control and is stable. Hence CUSUM chart is more useful to detect small changes in the process mean compared to X Bar and I MR charts

Platform economy is essentially an economy triggered through digital platforms where sellers and buyers can interact and conduct business, provide feedbacks and track delivery and returns The key drivers of platform economy are the following 1. Ensuring supply to manage the demand 2. Seller + Customer satisfaction 3. Global policies and regulations 4. Connectivity 5. Service 6. Pricing 7. Trust and goodwill 8. Positive impact on society and environment Application of Lean Six Sigma in improving profit for platform economy 1. Instill a continuous improvement mindset focused on driving process improvement while minimizing wastage / inefficiencies 2. Use data / simulation techniques to forecast, identify possible future trends and causes 3. Use techniques to confirm various hypothesis and uncertainties. Enable data based decision making 4. Use FMEA to reduce risk and build robust controls 5. Map the value stream and identify areas of improvement to better integrate platform with products, services, buyers and sellers

Chi Square Goodness of fit test is used to determine if the sample data of variable is a true representation of the population. For e.g., Cadbury's GEMS has chocolates coated with various colors. If one has to find out if the data distribution of green color in a sample (in this example let's consider it to be 20% of total count of GEMS chocolates in the sample) is a true representation of the population, the goodness of fit test can be applied. Here, the comparison is of distribution of one variable against the entire population is as per the expected distribution Chi Square test of homogeneity test is used to confirm if the distribution of two categorical variables is same as each other or not. E.g. This test can be used to compare if GEMS Mini crackers and normal GEMS have same color mix / distributions. In this case the variable distribution data for both the variables is not available and data has to be collected from 2 separate samples from 2 separate populations Chi Square test for Association or Independence is used to check if the 2 variables are associated in some way. In this example, let's take GEMS packet and pick green color GEMS to understand this concept better. There could be green colored GEMS that are whole and also broken. This test can be used to determine if the there is some association between green color of GEMS and whether it is whole or broken. In this case, the variable distribution historic data is not expected to be available. However, the sample is collected from the same population

Below is the explanation of Fractional, Decimal and American Odds with examples 1. Fractional Odds helps to calculate profit against the stake. In the fractional odds, the numerator is the profit and denominator is the amount against which the profit can be gained. For e.g. Let's take the stake to be $ 20 and odds is 1/5. This means to get a profit of $1, the person will have to invest $5. The total amount earned will be (0.2*$20)+$20 = $24. The break up is $4 profit + $ 20 stake 2. Decimal Odds makes it easier to workout the total return over any wager. Decimal odds helps to bring the actual price to two decimal points helping to accurately assess the returns to each penny. For E.g. If a person is betting $ 20 against an odd of 2.46, the total draw would be $20*2.46 = $49.20. The person can also break it down to the initial stake amount ($20) and winning amount ($29.20). 3. American Odds have minus value that indicates the amount to be staked to get a profit of $ 100 and a positive value indicating the amount that will be won if the person stakes $100. For. E.g. if the value is -200, it means that the person should invest $200 to get a total draw of $300 out if which staked amount is $200 and profit is $100. If the person is betting for the positive value, for. e.g. + 240, this means the person will get a total draw of $340 out of which the staked amount is $100 and profit is $240 Thank you

DOE is widely used in manufacturing sectors. However, the usage of the methodology is challenged in the non manufacturing / services sector due to the following 1. Dealing with people over machines - DOE in manufacturing / production sector deals with raw materials, WIP goods and machines whereas in non manufacturing / service industry process steps are performed by people and it is risky to experiment leading to challenging / changing the way people work as it can be counter productive 2. Multiple scenarios, non controlled environment - In a service sector, the guidelines are broad since the objective is primarily to solve the pain area for the customer. This means that the way in which services are provided can change quickly depending on the requirements. Most of the time decisions have to be made on the spot, getting creative but staying within the guideline. There are more noise factors and variables and most of this cannot be measured in statistical terms. 3. Cannot always involve customer - It is not always possible to involve customer as part of the experiment as it involves time and multiple interactions 4. Involves cost and time- Companies dont want to waste money and time on experiments 4.Culture is more human centric than data centric - The culture in the corporate sector, especially leadership is based on past experiences and intuitiveness and less data oriented Below are some practical suggestions to improve acceptance for DOE in corporate sector 1. Promote computer simulation which is more faster, cost effective and visual 2. Establish link between the result of simulation models and customer satisfaction and profit 3. Train all leaders and management staff on Six Sigma techniques, LEAN and basics of data sciences 4. Inform leaders of how competitors are using DOE to get ahead in the market. This might convince leadership to encourage application of DOE

Out of Trend, Cyclical and Seasonal components of time series, Cyclical variations is the most difficult to handle because usually the time period considered is for 3 to 8 years and in today's times, it is difficult to understand the regularity and variations. The rate of disruption is very high because of which it is difficult to rely on past trend (always) and predict how the respective industry will be impacted and to what extend Below are some of the applications of time series 1. Volume and time study 2. Headcount, sales, revenue forecasting 3. Risk forecasting

Human centered design is one of the approach used in creating products or services by putting customers physical, emotional and psychological needs at the center of the design. This approach is used in designing new product or services and also solving existing customer problems. Some of the salient features are 1. Use empathy to understand customers needs 2. Use creativity to build smart and user friendly designs 3. Review with customer, seek feedback and modify the design in multiple iterations Examples - Designing tooth brush, shopping cart / trolley, walker for old people, mobile apps etc. Regards, Gopal

Earned Value is a project management technique used to measure the performance / progress made at each stage of the project in comparison to the overall project schedule and cost basis project scope Below is an example of how Earned Value is calculated For e.g. let's assume Planned cost for a project is USD 20K, schedule is 6 months, estimated hrs is 200 hrs and actual hrs spent is 50 hrs EV at any stage of the project can be calculated as follows EV = (Planned Cost * Number of hours completed)/Estimated hours EV = (20,000*50)/200 which is USD 5K Limitations of EV - EV is effective only when the project plan, schedule and cost is mostly static and hence will not be applicable for Agile projects where the scope, time, cost and schedule can be very dynamic

Bodystorming is a technique that uses prototypes and role plays to simulate and understand the end user experience by observing how he/she interacts, feels, reacts and responds to features of the product or service. This technique will help to understand what are the opportunities to further improve the product / service proactively at the design stage rather than waiting for feedbacks after launching the final product or service. The approach is not costly since the prototype is not functional. For e.g. if team is designing a ticket booking mobile app, the prototypes can be made using paper and cardboard and can showcase the different fields that will be available on screen and simulate the entire process from user accessing the site to the actual ticket purchase. Also, since yesterday was Diwali, another example that is coming to mind is how Bodystorming technique can be used to better design lamps to ensure that light wind / rain does not extinguish the light

Explain card sorting Card sorting is a UX research technique used to organize the content in the most logical and user friendly way so that it positively impacts user experience when accessing a website or an application of a product or service. For. e.g. When building a mobile app, card sorting can help the UX team to determine what content has to be presented in each screen. The objective is to make the application easy for users to navigate and fulfil their expected outcomes by improving their experience. Use examples to show how it is different from an Affinity Diagram Though at a high level both card sorting technique and affinity diagrams focus on brainstorming and grouping / classifying inputs into various groups / themes, the usage context is different. Let's take a fashion / clothing website for example Card sorting as a technique, in this case, can be used to to understand the requirements from the users and categorize the requirements under various themes or headings. E.G. one of the main heading or theme (out of many) can be Men's clothing and the sub themes can be Jackets, Shirts, Trousers etc. Affinity diagram can be used to understand what did users buy at a competitor website, what are the items they could not find in the website, which other website would they visit to make a purchase etc. Affinity Diagram can also be used to brainstorm on solutions. However, one of the main difference between card sorting and affinity diagram is that card sorting also- focuses on structuring the content. E.g, "Home" can be the first heading (followed by sub headings), "Contact us" can be the last heading whereas Affinity Diagram only focuses on grouping and prioritizing of ideas