Arunesh Ramalingam

The processes where, I understand, zero rework is impractical or undesirable are the process concerned with design (mostly related to product features) software design and development. Rework done to fix bugs /defects/rejects i.e. as a correction measure is a “waste”. The aim should be to produce “First time correct”. But Rework might be needed to: Add features and functionalities that were intentionally left out in previous versions. Sometimes it is recommended to get a base product (minimal features) out (to minimize “time to market”) and then go back and rework to add additional features that were left out. Enhance features and functionalities to satisfy the “Excitement needs” of customers. From a Business Excellence perspective, some of the rework initiatives could be driven by a understanding of the Voice of Customer, and Voice of Business. Example: (1) Car manufacturers constantly rework their designs to provide customers with new features better/more efficient engines and so on. A rework on the engine design to improve its efficiency is “desirable” ( it is more of a continuous improvement activity to improve the engine performance) , but a rework on the shop floor if it produces defective engines is a “Waste” (2) An initial version of an ERP software may be designed only with Financial Accounting & Controlling, Supply Chain modules. In the subsequent versions the architecture might be reworked to include other modules like Human Resource Management, Production Planning, Sales and Distribution and so on. (3) Based on business requirements, there might be a need to integrate and connect a software product with other software products. This would require an architectural rework. It should be noted that the amount of rework needs to be properly understood, the cost to benefit ratio should be analyzed before taking a rework decision.

Kano Model Summary: The KANO Model is a tool used to identify 5 categories of product features/services from a customer's perspective, to enable manufacturers and service providers to be competitive in the market. KANO Model Feature Categories Presence of the feature VOC Absence of the feature VOC Examples Basic Neutral Dissatisfaction 24hr. hot water supply at hotels Performance Satisfaction Dissatisfaction High Battery life in mobiles Excitement Extra Satisfaction Neutral Welcome drinks /complimentary chocolates at hotel check in Indifferent Neutral Neutral Material used in packing juices or milk, if the packets are durable and do not leak. Reverse Dissatisfaction Satisfaction Annoying Pop up help features in some software (*VOC-Voice of Customer) One important point to keep in mind is over time as the customers get used to an Excitement feature, the feature becomes more of an expectation and moves to become a Basic feature. In other words, a feature which was earlier not even expected, becomes a “must -have”. Earlier its absence would have been unnoticed, but now its absence causes dissatisfaction among the customers. Example: power steering in cars, camera feature in mobile phones. What would be your approach for putting these needs to good use? First, I would work towards developing the identified Basic and Performance features/services, so that it is maintained at a level where it continues to satisfy the customers. There should NOT be any decline in these features/services. Second, I would focus on developing the identified Excitement features. These would eventually transform to be “basic must – haves”. I would innovate new features /services which would continue to add the WOW factor. Third, I would work on cost optimization/cost cutting on the identified Indifferent features/services. Fourth, last but not the least, I would take the precaution of not overwhelming the customer with product features and services. More is not always great! The product features and services should be inline with the requirements of the target customers.

Process Stability refers to the consistency of the process to stay within Upper Control Limit (UCL) and Lower Control Limit (LCL). The outputs of any process will have a mean value. Then the control Limits for the process are defined as follows: Upper Control Limit (UCL) = Mean + 3 sigma Lower Control Limit (LCL) = Mean - 3 sigma If the process behaves consistently over time, i.e. the outputs fall within the range UCL to LCL called process width, then the process is said to be stable or in control. If the Outputs are spread across outside the limits, then the process is Unstable or Out of Control. Process Capability is a measure of the ability of the process to meet customer specifications. The measure tells how good each individual output is. An estimation of the ppm (defective parts per million) is a method to measure process capability. Capability Indices (Cp, Cpk) are metrics used to measure the process capability. It indicates how capable the process is in terms of meeting customer requirements. Customers provide Upper Specification Limit (USL) and Lower Specification Limit (LSL) within which they want the product value to exist. This is called the tolerance or Allowed variation. (E.g. A customer of a Building Management system may want his air conditioning such that room temperature is 20 +/- 2 (deg C) i.e. with USL =24 deg C and LSL = 18 deg C) The air-conditioning process may have its own Mean/Average temperature say, 21 deg. C Cp = Tolerance/ Process Width = (USL-LSL) / (UCL-LCL) Cpk = min(Cpu,Cpl) where Cpu measures the closeness between process mean and USL; Cpl measures the closeness between process mean and LSL. Cpk accounts for change is process mean. A simplistic example: In an exam if the passing mark is 40 (USL = not specified; LSL = 40) and a student if 5 continuous attempts get 30,30.5,31,32,30 then we can say he is Stable(consistent) but not Capable. Is Process Stability supposed to be a pre-requisite for all type of processes? Any manufacturing /production process should be stable before being released to the production environment. Many customers request that their suppliers submit process capability data to qualify the supplier process. Any estimate of process capability depends entirely on where the process happens to be when the data is collected. For an unstable process, the mean shifts about over time. So, stability would be prerequisite for such process, as the process capability can only be estimated for stables processes. But, I believe, processes involved in Research and Development, Innovation would be inherently unstable. These process may not need a Capability estimation , so stability will not be a prerequisite.

Correlation between two variables A and B does not imply causation (i.e. whether A Causes B or vice versa), but it reveals information about the relationship between the variables. It is used to understand: (a) If A influences B (b) If B influences A; (c) Strength of the relationship between A & B (d) If relationship between A & B is positive or negative Correlation is used for a few reasons: 1. To see whether two variables are associated, without necessarily inferring a cause-and-effect relationship. Example: If it must be inferred whether Marketing Expenses were affecting Sales of a company. Suppose, we are doing the RCA for Sales drop during a period and lack of Marketing is suggested as one of the reasons. We can calculate correlation between the two variables “Marketing Expenses” and “Sales Revenue” after collecting data for say,12 months. Value of Correlation Coefficient “r” Strength of relationship -1.0 to -0.5 or 1.0 to 0.5 Strong Negative or Strong Positive -0.5 to -0.3 or 0.3 to 0.5 Moderate Negative or Moderate Positive -0.3 to -0.1 or 0.1 to 0.3 Weak Negative or Weak Positive -0.1 to 0.1 None or very weak If we find “r” is moderate or Strong then we can look at improving Marketing as a solution to improve sales. In case we find that marketing budget has indeed been reduced during that period, then it would be a logical recommendation to increase Marketing Budget. Thus, we see that though we do not have a Cause-effect relation between Marketing and Sales, using Correlation we are still able to identify a critical X to improve our Y (Sales Revenue) If we find “r” is None or very weak, then we can conclude Marketing budget does not affect the sales. 2. Let us consider that 2 variables A and B do not have a cause -effect relationship, but have a strong positive correlation with each other. Now if the cause for either A or B is known then both A & B can be controlled. 3. If it has been determined that two variables are correlated, then given the value of one variable the value of the other can be figured out. 4. Testing hypothesis regarding cause-effect relation. If hypothesis regarding different quantities of a new organic manure “X” having different effect on plant growth level is to be tested, then the lab technician can vary the quantities of X and see if there is variation in plant growth. If there is a positive correlation then the cause -effect relation hypothesis is true.

Voice of Customer (VOC) is a description in the customer's own words about a product or service, regarding the need/requirement/importance the cost to benefit appeal performance Vs expectations. In other words, it is a customer feedback that communicates to the product/service provider “what value the customer is willing to pay for”. It is one of the main factors that drive continuous improvement initiatives. Listening to VOC helps in: Tailoring the product and services to customer’s need. It enables focusing and improving items/aspects of the products/services which current and future customers care about most. Identifying gaps in the services provided to the customer Identifying potential improvement opportunities and the associated priorities from a customer viewpoint Identifying and decommissioning services that are of little or no value to current or future customers Getting in-depth insight into the psychographic dimensions of the target customers. Designing advertisements and other promotions that communicate those aspects of products and services that are most important to customers Developing the right pricing strategy so that customers feel they are getting value for the price they are paying. Can overemphasis on VOC be detrimental to business? Though VOC is critical, I do feel that overemphasis on VOC can be detrimental to the businesses that are mainly working in cutting edge innovation and in the service industry. VOC cannot drive the creation of breakthrough innovative products, like the iPod or the first car. Steve jobs words – “A lot of times, people don't know what they want until you show it to them.” and Henry Ford’s famous words - “If I had asked people what they wanted, they would have said faster horses.” underlines this fact. Customer’s feedback will mostly consist of the current ideas prevalent in the market and what the other popular companies are doing. The business cannot trust them to tell what the next new product should be. An "overemphasis on VOC" mindset would limit a company’s creativity. Once a product is developed and introduced, then VOC becomes critical for its sustainability. At the end of the day, a business (product/service) cannot exist without satisfied customers. Only if a business hears the customer’s voice, can it work towards satisfying them and creating a brand loyalty. Also, no matter what ever efforts a business might take to strengthen its Customer survey methodology, sometimes customers are may lie in their responses. So, a product oriented business needs to understand WHEN TO and WHEN NOT TO listen to VOC and how much to rely on it. VOC should take a backseat when cutting edge innovation is the primary objective. In the service Industry, the two aspects of VOC that a business should be careful about is the price negotiations and scope of project. For any project, the business should strategically plan the costing and decide on a firm rock bottom value. If the customer tries to negotiate below that price, then the sales team should either convince them or politely decline. If the sales team accepts the price, the customer wants because of an overemphasis of VOC mindset, then the execution of the project could greatly suffer and the business might make losses. Similarly, in many cases, the customers keep adding on to the scope once the project starts. The service provider should keep track of the scope and decide objectively what changes/additions can be accommodated and what cannot, what can be done free of cost and for what change orders need to be issued. An overemphasis on VOC mindset could result in accepting all that the customer wants and could result in never ending projects and demotivated teams because of the scope creep.

The process mapping techniques in increasing order of difficulty that I would recommend are as follows: Difficulty Level Process Map Technique Sub-categories within a Technique Level 1 SIPOC/ SIPOC -R Level 2 Process Mapping Top-down Flowchart (or) High Level Process Map Deployment Flowchart with Relationship Map Detailed Flowchart Level 3 Swim Lanes Level 4 Value Stream Map or Material and Information Flow Diagrams Current State Mapping Future State Mapping Gap Mapping & Action List Level 5 Key Process Input/Output (KPIV/KPOV) Mapping A brief explanation of each technique: 1. SIPOC/ SIPOC -R: Supplier Input Process Output Customer – Requirement Simple layout that shows what the process accomplishes while identifying the key players proving a starting point for discussion. Shows a few high-level process steps, required Input and Providers(Suppliers) and process Outputs and recipients (Customers) SIPOC-R is a variation on the SIPOC in which the requirements (or specifications) for the inputs and outputs are listed 2. Process Mapping a. Top-down Flowchart (or) High Level Process Map It is the expansion of the centre “process” from the SIPOC into six to seven more detailed boxes. Depicts the process in just a few steps providing quick and easy insights into what the process does (the major clusters of activity are) without getting into the details of how it’s done. Useful when communicating to leadership who do not need the details. b. Deployment Flowchart The deployment chart shows both "what" the process does and "who" are the people involved Relationship Map may be drawn to show the participants and how materials, paper or information flows between them. It is a combination of the top-down flowchart and relation map. It helps answer questions like – if right people are involved at right time, or if there are a lot of people and hand offs or if there are barriers between people who med to collaborate. c. Detailed Flowchart This provides additional details regarding the process like – each process step actions in detail to identify redundancies and wasted efforts and result of non-standard events. This can help understand process that has built up needless complexity, but is time consuming. 3. Swim Lanes A Swim Lane Map is used to better understand a process that crosses organizational, or departmental boundaries. It is at the same hierarchical level as the process map. It is used to show the flow of information/material between different organizations. This type of map is essential in showing “handoffs” between organizations, thus helping to understand failure points. It should contain all communication path, decision trees or handoffs, as these causes disconnects and failures. 4. Value Stream Map or Material and Information Flow Diagrams It is used to display the current state of the process including material flows, information flows and other information. This Value Stream map is used to better understand the value created, as well as “not created” – VA, NVA, ENVA in each of the process steps. It includes performance metrics from the individual processes and steps. a. Current State Mapping – “AS IS” mapping of the process. b. Future State Mapping – mapping the future process as per strategic planning. c. Gap Mapping & Action List - The Gap Map identifies the gap or distance in the performance metrics from current "AS IS" state to future planned state and shows the course of actions to be taken to improve the metrics. 5. Key Process Input/Output (KPIV/KPOV) Mapping Using the Process Flow Map or Swim Lane Map, per key strategic objectives, the area for improvement is identified. Once the target section of the process flow is identified, a standard block flow diagram of the supporting steps in that process is created. Critical Inputs (KPIV) needed for and critical outputs (KPOV) delivered by the steps are documented. The KPIV would contain potential root causes of an issue identified through RCA tools. Like “5 Why” analysis, Pareto diagrams, Fishbone diagrams and so on. References: 1. https://www.processexcellencenetwork.com/lean-six-sigma-business-transformation/articles/process-mapping-with-flowcharts 2. https://goleansixsigma.com/6-process-maps-know-choose-right-one/

Some examples that I could think of are as follows: 1. Delivery time in days: If you are tracking actual times (4.321 days for example) then it is continuous…. If you count entire days (4 days) then it is discrete…. 2. Height: If measuring actual height of people then it is continuous. But if we are categorizing as small, medium, tall the it become discrete data. 3. Calls coming into the Contact Center on a daily basis: Though Call count of each day is discrete, if there are a large numbers of calls over the days then it can assumed to be a continuous data.

Correction Corrective Action Preventive Action It is the action taken to eliminate a detected defect/ nonconformity. Corrective action is taken to eliminate the cause of the detected defect/ nonconformity. Preventive Action is taken to prevent the occurrence of any potential defects/nonconformities. It is an immediate action like replacing the product or editing a document to make the customer happy. This is a follow up action / reaction once the nonconformity is detected. It requires some strategic thinking and is aimed at preventing the recurrence of the defect/nonconformity. This is proactive action done before the defect/non-conformity occurs. These are improvements in the system to ensure detrimental system gaps are addressed and fixed before a nonconformity occurs. It is done in response to a Customer complain. It is done after a thorough Root cause analysis of a customer complain or other QC observations. It is a 5-step process: 1. Identify the Defect/Nonconformity 2. Immediate Correction to fix the problem 3. Root cause analysis to identify the process/ the cause of defect. 4. Modify the quality system so that the process that caused non-conformity is monitored to prevent the recurrence 5. Review of the corrective action to ensure that the recurrence has been prevented It is like a Failure Mode Effect Analysis (FMEA) or risk management initiative. It involves the following steps: 1. Identify potential problems or non-conformances 2. Find the cause of the potential problem/non-conformance 3. Develop a plan to prevent the occurrence 4. Implement the plan 5. Review the actions taken and the effectiveness in preventing the problem Example: Say an automobile dealer receives customer complaints for couple of new cars delivered in the lot regarding oil leakage beneath the car, then the cars can be examined and corrected by the dealer in the workshop. These are isolated cases and are low risk in nature. So, Corrections may be adequate. But if the dealer receives multiple similar complains then a correction may not be adequate and the manufacturer might need to be informed for a corrective action. Example: Say the same dealer receives complaints of the new car engines getting overheated. The dealer may root cause the issue. The RCA may indicate that the overheating was caused by defective coolant tubing causing the coolant to leak, thus overheating the engine. The dealer may fix the car (Correction), but there are high chances that an entire lot of cars might have the same defective tubing and see similar problems sooner or later. An overheated engine could cause the engine to catch fire. This is a high-risk problem and the dealer informs the manufacturer. Multiple dealers might bring the same issue to the attention of the manufacturer. In this case, the manufacturer may decide on corrective actions to recall the entire lot manufactured (using a specific lot of coolant tubing) and get then fixed at the dealers' workshop. Subsequently, back at the manufacturer's assembly line the tubing of new cars would be rechecked and assembled cars would undergo further quality checks for the specific issue. Any defective tubing in stock would be rejected. All these actions taken would be monitored to prevent any defective tubing from going back into the assembly line and thus prevent recurrence. Example: For the same example under Corrective actions, the preventive actions could be as follow: The manufacturer might prescribe, to tubing supplier, special quality tests for the tubing and request Quality test document. If supplier is unable to oblige, then the manufacturer might find alternate sources. The manufacturer may establish comprehensive testing scenarios for performance and quality check. The manufacturer may install additional alarms to detect coolant leak. These are jointly known as CAPA (Corrective Action/ Preventive Action) In certain markets and industries, CAPA may be required as part of the quality management system, such as the Medical Devices and Pharmaceutical industries. Failure to adhere to proper CAPA handling is considered a violation of regulations on good manufacturing practices. Situations where both preventive action and corrective action are undesirable and correction is the only preferred action: If an identified defect/nonconformity is an isolated/ one-off incident and is low risk to business and customers then it is better and adequate to use Correction as a remedy. In such cases, investing time and resources for understanding the root cause is not a value-added activity.

The Quality Control check sheet is a document used to collect real time process data from the location of data generation. Traditionally, QC check-sheets were used to: Check the shape of the probability distribution of a process output Quantify defects by their type Quantify defects by their location Quantify defects by cause (man, machine, material) To keep track of the completion of steps in a multi-step process In high-end automated processes, with the advent of modern technology, many of the activities performed by check-sheets are fulfilled by other means, like: rapid data collection and real time analysis (Real time Statistical Process Control and Statistical Quality Control tools), Inline Nondestructive Testing (NDT) and high end sophisticated imaging technologies for defect identification BPM or Business Process Management tools ensuring steps of a procedural flow are followed in proper sequence But there is a lot of cost involved in implementing these technologies and tools. Also, in operations involving lot of manual steps, it may not be possible to implement some of these technologies and we may still need the traditional QC check-sheets to ensure Quality and identify/capture potential issues. Even in the case where modern tool are implemented, QC check-sheets may be required for communicating tests/checks for inspections or may be required as a compliance document for regulatory standards. So, In my opinion, QC check-sheets can never be removed completely as a QC topic in education. Their importance and criticality to ensure sustainability of businesses need to be understood and taught, but they would get modified as per changes in their functionality with technological advancements.

Background: Push Strategy – is one where an organization depends on its ability to forecast the demand to drive its production. It does not Limit the Work in progress, production continues and is stocked. In a push system, the production order is scheduled and the material is pushed into the production line. Advantage: production does not stop for want of materials. company is fairly assured that it will have enough product stocked to complete customer orders Disadvantage: demand is difficult to forecast accurately. So, this could result in shortage of products (lost sales) or excess inventory. Storing and liquidating inventory could be an issue resulting in dead stock. Pull Strategy – is one where an organization depends on the demand to drive its production. Finished goods are not produced without a specific customer order. It puts an upper limit on the Work in Progress (dictated by the demand) and intermediates and materials are not acquired /replenished before existing items have been used. In a pull system, the start of each product assembly process is triggered by the completion of another at the end of production line. Advantage: Since the customer order is in hand the exact quantity to produce is known. It prevents Over production and inventory management related issues Disadvantage: Production may stop for want of materials. If supply response is not quick enough to meet actual demand fluctuations, then there could be lost sales. Most organizations use a combination of the two i.e. a Push Pull Strategy. It uses a Push strategy to drive its Material Requirements Planning (MRP) process to ensure that it has enough materials for production while trying to maintain the minimum possible inventory. Then it uses a pull strategy (per customer demand) to produce the finished good. Example: A Coffee shop uses Push to stock up on raw materials – Milk, creamer, sugar, coffee powder, but uses a pull to produce a mug of coffee. Why the pull system is not practically better than push system in certain situations? There are situations where a Push system may be better than a pull system. Push System is better suited for Services and products that are at the bottom of the pyramid i.e. high volume consumption and meant for the masses. Example: Service Industry. An email service provider like Gmail or Yahoo forecasts its demand like number of users creating accounts or storage required by users to build up its storage capabilities, database sizes, servers accordingly. As soon as the usage reaches a level they would increase the capabilities solely based on their demand forecast but not on any actual demands. Pull strategy would help in case of customized software development scenario where a customer would place an order for development of specific software for his need. Manufacturing Industry Push method is more suited when one is manufacturing complex, high variety products which tend to have a lot of work in progress (WIP). Also, products produced for the masses like FMCG goods (toothpaste, soap, shampoo, Demand forecast based push strategy would be better. Pull strategy would help niche product development like customized cars, laptops and so on.

Background Cost of Quality (COQ) is a quality metric that denotes the ratio of costs involved in guaranteeing high quality products to the total revenue generated by those products. It can be understood to be a combination of two main components as shown: COQ = COGQ + COPQ COGQ is the cost of good quality, which denotes the cost incurred to prevent poor quality and assure high quality products COPQ is the cost of poor quality, which denotes the cost incurred in failure to produce high quality products i.e. scraps, defects, rework, rejects. The COPQ can be denoted as following: COPQ = IFC + EXC IFC is Internal Failure Costs consisting of Scrap costs, Defect costs and Rework costs. Some of the factors that affect IFC are weakness in quality resolution (CAPA/FMEA), Improper Resource and Material planning, Equipment downtime, Re-engineering and Re-designing. EFC is External Failure Costs consisting of Returned Product Costs, Warranty Costs, Product Recall Costs.Some of the factors that affect EFC are Poor service management, unresolved customer complaints, environmental non-conformances and so on. Analysis The COPQ metric can be useful for a product line or smaller systems, but I believe, it may not be a beneficial metric to track for complex systems and the organization as a whole. The effective scope of COPQ analysis is minimal and pertains mostly to the IFC components. It will be a challenge to accurately measure the EFC (External Failure Costs) component of COPQ. Measures should definitely be taken to produce high quality products, but a balance should be reached as to how much investments are done to improve quality. Over doing quality could actually result in over processing which is one of the wastes identified in Lean. E.g. A Six sigma process is good but for process related to aviation and flights it is not good enough while for processes such as apparel manufacturing it could be an over kill and may not be required. Moreover, Investments into innovation, new technologies and better production techniques could have a better ROI than investing in the bottom – up approach of COPQ.

Variation is the fluctuation in a process’s output. Every measured output may not be identically same and we may notice some variation between multiple readings. Statically it is denoted by Standard Deviation (σ) which indicates the spread of each data point in the data set from the mean/average value. Example: Consider a machine producing 3.000 mm. diameter bolts. But each bolt may not measure 3.000 mm. diameter exactly. Some can be 2.999 mm., while some can be 3.001 mm. and there are endless possibilities. The spread of the various measurements around the mean (3.000 mm) is called the standard deviation. Lower the Standard Deviation or Lesser the variation of the diameters indicates that the data points are closer to the mean and the process is better. Aim of a good process design is to minimise this variation. There are two types of Variations: Common Cause Variation Special Cause Variation This is a Random Variation and is natural for the process. As name indicates it is “common” to the process. Other terms : Noise, non-controllable variation, within-group variation, or inherent variation This is a Non - Random Variation or Assignable cause and is not part of the normal process. As name indicates it is “special” to the process and the variation can be assigned to a reason. Though the value of each point cannot be predicted, the range of this variation is predictable. This range is called the process width or the Control limits. This is unanticipated and sporadic. It is completely unpredictable. Common cause variation is introduced by intrinsic variation in the process - by the variation present in People, Information systems, Machines/Equipment, Measurement, Materials and Environment. Special cause variation is introduced by the external parameters such as Operator not available, Computer crash, Power Outage, Machine malfunction. Generally, the process remains in control i.e. within the control limits and no corrective action may be required. If process deviates the control limits, then corrective actions are required. The process goes out of control. Reason of variation should be identified, analyzed and corrected if possible. If unable to correct alternate solutions should be implemented. E.g. The average normal body temperature is generally accepted as 98.6°F (37°C). Per some studies the "normal" body temperature can have a range, from 97°F (36.1°C) to 99°F (37.2°C). So, if the temperature is within this range and the person is otherwise feeling normal, then he may not need any medication E.g. If a person’s temperature goes beyond this range then there are high chances that he has a fever and might need to take medication. Why they should be differentiated and how misjudging one of these as the other can create problems? Common Cause Variations may not cause a process to go beyond control limits and so corrective actions may not be required. If corrections are required, then it would be intrinsic to the process like checking on the Manpower, Material, Method, Measurement, Machine, and Environment, shifting the process mean, adjusting the variance and so on. It exists even after "Special Cause" is removed. Special Cause Variations always cause the process to go out of control. The reason for the variation or “what has changed?” should be identified and analysed. If possible to rectify then it should be corrected else an alternate solution should be implemented. Mistake 1: Attribute a variation to Special Cause, when it is actually a Common Cause. Impact – Over-adjustment when not required. If deviation from target is considered due to special cause and the mean is adjusted for the deviation, then the adjustment will become a cause for further deviations and will worsen the situation. Mistake 2: Attribute a variation to Common Cause, when it is actually a Special Cause. Impact – Ignoring the variation and not doing anything. A special cause actually shifts the process mean, but this was ignored and no action taken to correct it. This further increases the variability. Example: Consider a pizza delivery joint located in locality A and catering to locality A & B and running an offer of “delivery in 30 mins or free”. Pizza production time: 10 mins Delivery Boy travel time to locality A: 10-20 mins. (Common Cause Variation) Delivery Boy travel time to locality B: 15-25 mins. (Common Cause Variation) Issue: So, some of the deliveries to locality B are free of cost. Analysis: This is Common Cause Variation. If the manager considers this as common cause variation, he can either continue with a few free deliveries (if it is not heavy on the business) or try to improve the pizza production cycle time But, if the manager commits Mistake 1 (i.e. considers it a Special Cause while it is a Common cause) then he may consider excluding locality B from the offer, which would have a greater impact on the whole business. Now consider the same scenario but with a new temporary condition: The road connecting locality A and B is undergoing renovation and there is frequent traffic delay of 10-15 mins. (Special Cause Variation) Analysis: This is Special Cause Variation. If the manager considers this as Special cause variation, he can decide to temporarily excluding locality B from the offer (or) modify the offer for locality B to “delivery in 45 mins or free” and communicate the valid reason. But, if the manager commits Mistake 2 (i.e. considers it a Common Cause while it is a Special cause), then he may: put in efforts to reduce pizza production time which would not resolve the issues (or) land up NOT taking any corrective correction. This could lead to significant increase in pizzas being delivered for free in locality B and unsatisfied customers in locality B

SIPOC (or COPIS in reverse) denotes Suppliers – Inputs – Process – Outputs – Customer. When a team undertakes a process improvement activity it is essential to understand the whole picture and its relevance in the business. The team needs to develop a process map to decode and analyze each process step. To develop a proper holistic detailed process map, they need a structured framework that would help to understand the basics of the process and the various entities/actors involved in it. A SIPOC tool essentially provides this framework to record information about the process in an easy to view, understand and communicate format. It is high level process map full of information that allows the participants in a process to learn together about the process, under question. They can come to consensus about the make-up of the SIPOC and identify opportunities of improvement. Processes steps for potential improvement can be discussed and prioritized. It is a team exercise where business units participate in the discussion and rank/prioritize opportunities together. So, the SIPOC, in addition to capturing the “as is” state of the process also acts as a dynamic tool to create dialogue and acceptance (overcome resistance) of a new approach to change. It helps the participants to identify and build consensus on operating boundaries which in turn provides clarity in defining In-Scope and Out-of-Scope deliverables of the project. For any Six sigma project this clarity of scope is essential. Using the details of the SIPOC, the team can then develop a detailed process map for further analysis.

Jidoka is providing a mechanism whereby a process detects when an abnormal condition has occurred and immediately stops work. It gives equipment the ability to distinguish good parts from bad autonomously, without being monitored by an operator. This eliminates the need for operators to continuously watch machines. Thus, one operator can handle several machines, often termed multi-process handling. and leads to large productivity gains. Jidoka highlights the causes of problems because work stops immediately when a problem first occurs. Automation is the use of technology and other control systems to operate equipment and processes without any human intervention. The entire process logic is programmed into special type of controllers called Programmable Logic Controllers (PLC) and it controls the process equipment such as motors, valves, pumps and so on. The operators have a real-time view of the process via a graphical user interface (GUI) system called Human Machine Interface (HMI). Process data is continuously captured via various sensors and instrumentation and communicated to the PLC for the logic to function and is also displayed in the HMI. In today’s world, Automation has gone to the next level where the automated process has built-in intelligence. In practice, it means that an automated process is sufficiently "aware" of itself so that it will: Detect process malfunctions or product defects Stop itself Alert the operator This combination of Automation and Intelligence is denoted by Autonomation. The inclusion of intelligence can be using Hardware or Software. Example 1 (Hardware): In a beverage bottling line while the bottle forming from pellets can be an automated process an ultrasonic crack detecting equipment is used to detect any defective bottles and immediately reject it. Similarly, the bottle filling, corking, and labelling process would be an automated process. Once labelled a Camera/laser equipment is used if the labelling is proper or if there are any defects. Example 2 (Software): Permissive and Interlocks are programmed in the automated system to detect problems. If some pre-requisite conditions are not met or an interlock condition is encountered then the logic halts execution and systems goes back to a safe state, while creating an alarm message for the operator. Permissive could be something like a drain valve needs to be open before the drain motor can run. So if the operator (in manual mode) /logic (in automatic mode) starts the drain motor without opening the valve then system alerts the user. If the drain motor is running the drain valve would not be allowed to close. This is an interlock. Example 3 (Software): Implementation of Alarm Management and Alarm Severity in Automation systems. Modern automation systems provide sophisticated Alarm management systems with customizable Alarm severity. A temperature/ pressure/ flow that is below or above configurable limits (High-High, High, Low, Low-Low limits) can trigger alarms of different severity (or priority). Based on the severity the alarms can be programmed to perform various actions ranging from – information only to system shutdown.

Value Stream Mapping is lean manufacturing tool used to document, analyze and improve the flow of materials or information from its beginning through till it reaches the customer. Each process step that the material/ information passes through is analysed to see if it is a: Value Add/ Non-Value Add Capable and Available Capacity is adequate Flexible A Pacemaker process in the value stream is a process that is the only scheduling point along the value stream that sets the production rhythm for the entire stream. The pacemaker process should be located such that a pull system is maintained upstream of the pacemaker step and First-In-First-Out (FIFO) pace is maintained downstream till Customer. The pacemaker process usually is near the customer end of the value stream, often the final assembly cell. However, if products flow from an upstream process to the end of the stream in a FIFO sequence, the pacemaker may be at this upstream process. The idea is to schedule the pacemaker process such that its cycle time is as close as possible to the Takt time, so that the transition from a Pull system (upstream) to a FIFO system (Downstream) is achieved. Fig. Selecting the “Pacemaker Process” [1] One thing to note is a pacemaker process (a concept of lean production) is different from a bottleneck process (a concept of Theory of Constraints). A bottleneck process is an overloaded or inefficient process step that limits the overall system’s production throughput. Bottleneck could be due to multiple reasons – excessive downtime, poor quality, long changeover times, and so on. The bottlenecks need to be analysed and fixed, but a bottleneck process need not be made the pacemaker process to set the flow rate of the entire value stream [1] https://todaysleanmanufacturing.com/learning-to-see/pacemaker-process/ [2] http://journals.sfu.ca/ijietap/index.php/ijie/article/viewFile/158/116

A Hypothesis is basically a thought or belief that a particular input might affect an output.Hypothesis Testing is a systematic approach of testing this belief statistically and deciding whether the hypothesis can be retained as reasonable and realistic or should be rejected as impractical or insupportable. A hypothesis is developed for the population and statistical tests are used to determine whether there is enough evidence in a sample of data (representing the population) to infer that a certain condition is true for the entire population. A Six Sigma Project is implemented using the DMAIC or DMADV Methodology. DMAIC: Define -> Measure -> Analyze -> Improve -> Control DMADV: Define -> Measure -> Analyze -> Design -> Verify Hypothesis testing is used in the Analyze phase. In this phase, potential Xs (Inputs) which might have a bearing on the defined Y (output) of the six sigma projects are listed. Out of the potential Xs, critical Xs, which are expected to affect the output the most, are identified and checked if the identified critical Xs are sufficient to improve the Output. An hypothesis test will help the team in cases like determining if a modified process B has “significantly” improved yield when compared to the original process A or if a quality parameter is independent of a given production condition and so on.

Poka -yoke or Mistake Proofing is about using a process or design feature and control mechanisms to prevent defects, detect them if there are not preventable. reduce the severity of the defects. The main motive is to: PREVENT a defect from occurring and if that is not possible, DETECT the defect every time it occurs. It is critical to prevent and detect errors/ defects as early as possible in the process because the later they are found the more expensive they become i.e. costs associated with them increases - more materials, labour, overhead, time. While implementing poka-yoke designs, care should also be taken that the implementation does not enhance any other issues or open new issues that may cause defects. Poka -yoke or Mistake Proofing has varying degrees of effectiveness. - Control Vs Warning Poka yoke. One must balance getting the most effective poka-yoke while keeping in mind the practical and economic feasibility of the solution. I feel all the interpretations provided in the question are all correct and validate the varying degrees of effectiveness. 1. The human error will not happen at all. Example: Rectangular design of 3.5” floppy disc so that the wrong side cannot be inserted. SIM card slot in cell phones is designed in such a way that user can insert SIM card in correct way only. There is no chance for user to make a mistake while putting SIM card in a cell phone or floppy in the drive. 2. Human error may continue to happen but the defect will not happen. Example: Validation check when creating new password to contain the required combination of Upper, lower case, numeric and special characters to ensure a strong password. The system does not accept a password unless it fulfils the criterion. Double Entry Box: Most websites & software where one needs to enter a critical bank account number, or a password create option, users are asked to enter the same value twice (with paste option disabled). This is to ensure people haven't made a mistake while entering the value, and that both boxes hold the same value 3. Human error may happen, the defect is less likely to happen. Example: Some of the email software pop up an error message like “there is no attachment, do you want to send it anyway?”, if they find the key words “Find attached” (or other variants of the same) and do not see an attachment when the user tries to send the email. Some Email software pop up a message if the subject is missing when the user tries to send the message. Car Seat belt Warning indicator beeps to warn that the user has forgotten to put on the seat belt, if he drives without putting on the belt. 4. Human error may happen, the defect will also happen but will be detected and corrected automatically. Example: Microsoft word, Google search automatically corrects typographical spelling error. Auto logout functionality in websites (especially Banks). When user forgets to logout before closing the website and reopens, then he has to provide the credentials and log back in.

Background and Concept: False Alarm and Missed Alert are better understood with the two types of errors that are possible in statistical Hypothesis testing. Dealing with them with reference to test of hypotheses will provide more insights than otherwise. Any hypothesis test is begun with the assumption that the null hypothesis is correct. Null hypothesis is the default position and corresponds to the idea that "one is innocent until proven guilty". False alarm or Type I errors or False Positives (α): They happen when we reject a true null hypothesis. Missed alert or Type II errors or False Negatives (β): They happen when we accept (fail to reject) a false null hypothesis. Which error will you prefer over the other? The answer to this question depends on the problem and the worst that could happen if either a Type1 or Type 2 error was committed. Example 1: Person accused of Murder awaiting Death Sentence. Null Hypothesis: Person did not commit murder. Type 1 error: Person did not commit murder but pronounced guilty. (Rejected true Null Hypothesis) Type 2 error: Person committed murder but pronounce Not guilty. (Accepted false Null Hypothesis) In this example, though Type 2 error is not favorable to society, but hanging an innocent person is far worse. So Type2 error or a Missed alert is preferable. Example 2: Person being screened for a disease to prescribe further tests. Null Hypothesis: Person does not have the disease. Type 1 error: Person does not have the disease but recommended for further tests. (Rejected true Null Hypothesis) Type 2 error: Person has the disease but recommended for no further tests. (Accepted false Null Hypothesis) In this example, Type 1 error might cause the patient to undergo further tests but might finally reveal that he does not have the disease. A type 2 error would prevent a legitimate patient from undergoing further tests. But a legitimate patient can re-do the test if the symptoms persist, and it is fine for a person to do some further tests even if he does not have the disease. So Type1 error or False alarm is preferable. Example 3: Person being screened for a disease (presence of which has a good rate of survival and normal life) to prescribe a delicate specialised surgery that has poor success rate. Null Hypothesis: Person does not have the disease. Type 1 error: Person does not have the disease but recommended for surgery. (Rejected true Null Hypothesis) Type 2 error: Person has the disease but not recommended for surgery. (Accepted false Null Hypothesis) In this example, Type 2 error might cause the legitimate patient to not have the surgery which is bad, but it is much worse to have a person without the disease undergo the delicate critical surgery. The legitimate patient may re-do the tests, if he still feels the symptoms of the disease and may be re-diagnosed to undergo the surgery. In this case, a Type2 error or a Missed alert is preferable.

Takt time production is a concept that helps the production line to produce products at the rate that the customers need them. It can be calculated as: Takt Time = Estimated Production Time / Customer Demand Qty Are the decisions driven by Takt Time Strategic or Tactical in nature? Before we analyse the decisions driven by Takt time production, we need to understand the difference between “Strategic Decision” and “Tactical Decision” Strategic Decision Tactical Decision Strategy involves planning a company's next move. (long term perspective) Tactics involves the activities for the implementation of the plan. (short term perspective) It is about doing the right things. It is about doing things right. Deals primarily with planning for the future direction and growth of the company, in accordance with its stated mission and goals. Deals with real-time (or very near future), actions to handle company’s current operating environment and identify opportunities. Concerned authority is the upper management who have a better understanding of the company, as a whole. Concerned authority is the lower level management who have a better understanding of the day to day operations and planning E.g. Recognising future trends or foreseeing results of projects and developing Counter/fallback plans. E.g. Making the most efficient use of resources (people, time and money), both for achieving objectives as well as handling any risks and challenges involved in carrying out strategic plans. Takt time production ensures that all the capacity in a production line is planned and utilised and still meets overall customer demand. It helps to deliver the right product at the right time in the right quantity to the customer with reduced waste of man and machine – Reduced Over production, Manage operator overtimes, easier planning of shifts and schedules, , Fewer defects, better price management as right quantity is produced and inventory is minimised. It creates a constant pulse across the processes, which will immediately highlight capacity issues, synchronisation issues among processes, quality issues and many others. Tact time production ensures the production line is operating more efficiently and production would be more predictable. The decisions driven by Takt Time production is related to capacity planning, production quantity and inventory management, manpower/resource planning , scheduling. With the understanding of Tactical decisions, that we obtained earlier, we can conclude that all these decisions are tactical in nature.

Central Limit Theorem (CLT) states that, as the sample size tends to infinity the distribution of sample means approaches the normal distribution i.e. a bell shaped curve. So, in other words, this theorem talks about the shape of the distribution of sample mean, as sample size tends to infinity. The Law of Large Numbers states that, as the sample size tend to infinity, the centre of the distribution (mean) of the sample-means becomes very close to the population mean. So, in other words, this theorem talks about where the centre (maximum point) of the bell curve is located. Example: Consider a large population and you need to measure the average height of men in the whole population. i.e. we need to calculate the population mean(µ). It may not be humanly possible to measure height of each men to compute the average. So, we can consider creating "N" sample sets (s1, s2, s3…sN) of “n” men each. i.e. sample size is “n”. These sample sets should be independent and identically-distributed which means it should be random and occurrence should be independent. A sample should not be taken , say, of just Basketball players, whose height would be above that of average men. If Basket players are considered, then they should occur in every sample set. (just argument sake). Usually, if we know that people were selected randomly, then we can assume that the independence assumption is met. Sample 1: s1(height of “n” men) Sample-Mean (i.e.mean of Sample set 1) : x1 Sample 2: s2(height of “n” men) Sample-Mean: x2 Sample 3: s3(height of “n” men) Sample-Mean: x3 . Sample N: sN(height of “n” men) Sample-Mean: xN [Total number of such samples “N” required depends on the population size and is a separate topic of research.] Per Central Limit Theorem, as “n” --> ∞ (infinity), the plot of Sample-means x1, x2, x3…xN forms a normal distribution or Bell curve. Per Law of Large Numbers, as “n” --> ∞ (infinity), the centre (maximum point) /mean of this bell curve would be close to the population mean (µ) that we need to calculate. i.e. (x1+x2+x3+....+XN)/N is close to µ As sample size “n” is increased (“n” --> ∞), the bell curve becomes narrower i.e. the standard deviation between sample means reduces and sample-means get closer to the population mean. Why not get rid of Non-Normal data? Most of the sample data or data sets available for analysis may not be normally distributed. Data obtained from overlap/combination of two process may not be normally distributed even if, the individual process data may be normally distributed. Round-off errors or measurement devices with poor resolution can make normally distributed data look discrete and not normal. Collected data might not be normally distributed if it is a subset of the total output data produced from a process. This can happen if data is collected and analysed after sorting. So more than often we must deal with Non-Normal data. Using the CLT to get a normal distribution uses the following assumptions and conditions: Random Samples: The data must be sampled randomly. Independent and Identically-distributed samples: The sample values must be independent of each other. This means that the occurrence of one event has no influence on the next event. 10% Condition: When the sample is drawn without replacement (usually the case), the sample size, n, should be no more than 10% of the population. Sample Size Assumption: The sample size must be sufficiently large. The Central Limit Theorem states that a Normal distribution model can be used to think about the behavior of sample means when the sample size is large enough, but it does not specify how large it should be. If the population is very skewed, then a pretty large sample size will be needed to use the CLT. However, if the population is unimodal and symmetric, even small samples would work. The sample size should be decided (i.e. whether large enough) in terms of information that can be obtained regarding the population. In general, a sample size of 30 is considered sufficient if the sample is unimodal (and meets the 10% condition). These assumptions and conditions make it difficult to apply CLT under all circumstances. Depending on the population size and sample size the approximations may give inaccurate results. So it is not a possible option to get rid on Non Normal data completely.

Fault Tree Analysis (FTA) is a graphical technique for Reliability and Safety Analysis of Systems. It is used: to investigate potential faults its mode and causes and quantify their contribution to system unreliability in the course of product design. The basic constructs in a fault tree diagram are gates (conditions) and events (causes leading to failure). Fault tree diagrams are logic block diagrams that display the state of a system (top event) in terms of the states of its components (basic events). An FTD is built top-down in term of events. It begins with the foreseeable, undesirable loss event (or a fault condition). Subsequently, it attempts to determine the specific causes (events) by constructing a logic diagram using a graphic model of the pathways within a system that can lead to the failure. Each cause is further broken down till a basic fault: human, hardware or software is reached. The pathways connect contributory events and conditions, using standard logic symbols (AND, OR, etc.). Example of an FTD – The Root Causes of Hazard to Patients during surgery [1] The two most commonly used gates in a fault tree are the AND and OR gates. OR Gate represent Logical Addition. Even if one of the Inputs to an OR gate is “1” or “TRUE”, then the Output is “1” or “TRUE”. If all the inputs are “0” or “FALSE”, then the Output is “0” or “FALSE” AND Gate represents Logical Multiplication. Even if one of the Inputs to an AND gate is “0” or “FALSE”, then the Output is “0” or “FALSE”. If all the inputs are “1” or “TRUE”, then the Output is “1” or “TRUE” The main purpose of the fault tree analysis is to help identify potential causes of system failures before the failures actually occur. It can also be used to evaluate the probability of the top event using analytical or statistical methods. These calculations involve system quantitative reliability and maintainability information, such as failure probability, failure rate and repair rate. After completing an FTA, efforts can be focused on improving system safety and reliability. Situations where FTD is most effective: It works well to identify possible causal relationships in cases where Output has a Boolean (True/False) relation with inputs, especially in small and medium sized systems where all causes /events can be conceived. It can be used in situations where specific data regarding known failure rates of components is known. It is used to supplement Root Cause analysis on engineered systems, by reviewing assumptions and design decisions made during initial system design. Situations where FTD is least useful: It is not effective in large complex systems as it is difficult to conceive all possible scenarios leading to the top event. The construction of fault trees can become very tedious and are prone to have errors. It does not function well as a Root Cause Analysis tool because FTD does not work well when some of the causes could be Human actions. This is because wide variance of possible human failure rates prevents FTD from providing accurate results. FTD is not very effective when there is event dependency or load sharing i.e. the occurrence of each event (cause) affects the probability of occurrence of the other events. [1] http://asq.org/quality-progress/2002/03/problem-solving/what-is-a-fault-tree-analysis.html

“Value” for any product/service is defined by the customer. It could be the quality of product/service (or) the price that the customer pays for (or) the on-time delivery and/or a combination of all three. But sometimes “Value-adding” activities of an organisation may not directly translate to an additional cost paid by the customer. It could result in acquisition of more customers (i.e. increase in market share) whereby the organisation recovers its cost of the “Value -adding” activities. For such “Value-adding” activities, I feel, the 3 universally accepted checks for “Value -add” activities may not be sufficient. In today’s rapidly changing world, some activities which might have been “good-to have” , in the earlier days, are becoming quintessential for organisations. Below, I have identified a few checks and activities which, I feel, can neither be categorised as “Non-Valve Add” nor as “Essential but Non-Value Add” today. Check 1: A value added activity is one that provides a competitive edge or differentiation to the current service compared with competition. Activity: Signing a new supplier relationship agreement or collaboration agreement with another company. Explanation: The main objective of Collaboration agreement with another company or Supplier Relationship Management is to establish two-way, mutually beneficial relationships between organisations or an organisation and its suppliers. The collaborative, relationship building is aimed at providing a greater added value to the end customer or a differentiation factor which provides a competitive edge. Another benefit is access to new customers belonging to the other partner/supplier and joint business development activities. This may or may not result in an increase in the cost for the customer, but will result in acquiring more customers. Once in place, this could act as a new starting point for creating more Value-added services. Check 2: A value added activity is one that helps to sustain and enhance the quality of product/service. Activity: Identify, Enable and encourage the workforce to undergo relevant training and certifications. Explanation: A trained workforce enables to deliver better (efficient, cost effective, sustainable, innovative) products and solutions to the customer. At times the customers request for certified people. Check 3: A value added activity is one that helps to improve the organisation's public image. Activity: Implementing and getting certified/audited and becoming members in boards associations dealing with Environmental, Health and Safety standards and policies (other than those dictated by government policies). Explanation: In the modern world, the social responsibility of organisations plays a very critical role in its existence. These activities project a positive image of the organisational culture and give a feeling that their products and services are more trustable and will be of better quality. Check 4: A value added activity is one that provides customer an additional choice. Activity: Adding a new item to the menu in a fast food restaurant.. Explanation: Providing the customer more choices is critical especially in fast food business. Chances of a customer visiting a restaurant offering more choices in the same price range say under the Value Menu section, is higher than he/she visiting a restaurant offering fewer choices. Here it may be seen that the though the customer does not essentially pay more but it is still a “value add”. Instead of being a linear value add to a product, this can be seen to be more of a lateral value add to the menu which could result in an increase in the customers.

‘5S’ is a lean management concept which stands for 5 Japanese words beginning with the letter S. these are: Seiri (organizing or arranging things): Sort Seiton (putting things in order): Set in Order Seiso (cleaning): Shine Seiketsu (standardization): Standardize Shitsuke (discipline): Sustain It basically emphasises good house keeping techniques to enhance productivity and reduce wastage of Time, Material, Money and resources , thus, enabling cost saving. The 3Ms of waste in Lean Manufacturing: MUDA – Waiting, Overproduction, Rejects (defects), Motion, Over-Processing, Inventory, Transport and Resource, Talent MURA - waste of Unevenness or Inconsistency. MURA drives MUDA. Inconsistency leads to other wastes- defects, over production and so on. MURI - cause Overburden, i.e. to give unnecessary stress to employees and processes. This is caused by Mura and a host of other failures such as lack of training, unclear or no defined ways of working, the wrong tools ill thought out measures of performance. This in turn causes MUDA. These Wastes are not only found in manufacturing, but are prevalent in Service sector, as well. Lean is about removing the 3 Ms. Concentrating on solving Mura and Muri can prevent the creation of Muda. Just in Time (JIT) principles with Heijunka, Kanban and other techniques enable production smoothing and flow; removing inconsistency i.e. the causes of MURA, unevenness. Lean tools such as 5S and TPM help to remove MUDA other causes of overburden removing MURI. For Example: In Technological services sector implementing 5S techniques could have various benefits like Matching right work force (correct skill set) with the right work (project) Planning on the correct and required training. Setting up SOP (Standard Operating Procedures) to avoid confusions Evaluating and implementing proper performance indicators.(KPI and performance appraisals) Reducing Paper work, errors in filled in forms, Inventory of supplies of unused forms. Increasing productivity This would result in significant reduction of MURI and MUDA and increase savings. For Example: In Hospitality Sector implementing 5S techniques could result in : Increased room occupancy Reduction in customer wait time Floor space saving Increase in service line efficiency Improvement in customer satisfaction with efficient workforce having high morale. Thus, with a disciplined 5S approach I feel there could be significant money saving, even in the non- manufacturing sector.

In today’s world, with increased globalisation, constant technological advances and competitive pressures, Innovation is on the top of any CEO’s priority list. But, for many companies, innovation opportunities are limited and mostly invisible. Also, the success they have, has been sporadic/accidental either because of fallacies in the identified opportunity (innovation does not produce necessary business result) or inefficiencies and wastage in the innovation process (expensive, unsustainable innovation). An organisation not having a proper Operations Strategy would lack the processes, discipline and organisational climate to foster sustainable meaningful innovations on a continuous basis. Lean Six Sigma, while helping achieve process excellence, provides a means to conduct measurable fact based analysis of the present conditions (process, product, service and market). This kind of analysis facilitates the team/ management to discover innovation opportunities not just in operations, but in services, products, markets and the core business model itself, which otherwise may not even be visible. This enables a much deeper and broader transformation which would significantly help enhance operational and financial performance of the business. “Lean” focuses on reducing cost by process optimisation. “Six Sigma” focuses on meeting customer expectations by improving the quality by measuring and reducing defects. However, in the current competitive marketplace the ultimate aim of “Lean Six Sigma” is not just cost cutting and improve efficiency, but growth and effectiveness. So, it drives organisations to inherently innovate to do “Better things” rather than just do things in a better way. By applying Lean Six Sigma concepts, the Innovation process itself could be made more efficient by reducing waste and performing factual data based analysis of the results. The right Operations strategy can help companies make innovation a regular occurrence. An organisation using Lean Six Sigma as an operations strategy inculcates the discipline and lean thinking from top management to bottom of the workforce creating an organisational climate for innovation to flourish. Innovation has a Domino effect ie. Innovation in one area drives innovation in another. As a result, the organisation would be able to surface significant innovation opportunities that have far-reaching impacts on the businesses. Case Study Examples [1]: Caterpillar through a 6-sigma initiative developed a strategic vision and created a road map of change based on fact based analysis. This lead to product innovations like its phenomenally successful low-emissions diesel engine and to redesigned processes including a streamlined supply chain. Posco Steel: Using Lean Six Sigma’s relentless focus on customer demands, POSCO developed process and IT innovations that dramatically reduced finished steel inventories and cut lead times from 28 to just 14 days by 2003. But, POSCO found that filling orders faster left too many partly used steel slabs, which hurt margins. Determined to meet customer needs profitably, POSCO developed sophisticated production scheduling algorithms that allowed it to pack multiple orders on a slab. This allowed the company to optimize slab utilization (and profitability), while still responding rapidly to customer demand. Other Innovative companies and big time Lean Six Sigma practitioners are GE, Motorola, Toyota...to name a few. References: [1] https://www-935.ibm.com/services/us/gbs/bus/pdf/g510-6331-01-leansixsigma.pdf [2] http://imtuoradea.ro/auo.fmte/files-2007/MIE_files/Sunhilde_Cuc_1.pdf

KAIZEN KAIKAKU KAKUSHIN continuous improvement revolutionary change innovation Focuses on eliminating Muda (waste) by small incremental changes for the better over a period. Focuses on a radical change (big improvement) in a limited time. Focuses on innovation, transformation, reform and renewal. Each Kaizen activity involves only certain parts of the production system individually, but can be extended to all processes including purchasing, logistics crossing organizational boundaries into supply chain. Involves the entire Production system. It is more of a System Wide Kaizen and can be seen as a series of Kaizen activities completed together. Involves implementing innovative breakthrough ideas or products and services in a completely new way which makes a complete departure from the current situation. Sometimes small improvement of current situation may not help and a different way of doing things might need to be adopted. This revolutionary reform is Kakushin. Kaizen activities could then be initiated to improve things further. Involves all employees from the CEO to the assembly line workers and involves activities that continuously make small improvements to all functions. Initiated by the Management as it would have a significant impact on the business. Initiated by the Management as it would have a significant impact on the business. It might require companywide trainings and so on. The cycle of kaizen activity can be defined as: "Plan → Do → Check → Act". (PDCA). Along with PDCA, the “5Whys?” technique is also used. This is a form of Root Cause analysis where user asks a series of five "why" questions about a failure that has occurred, basing each subsequent question on the answer to the previous. 5 is just a guiding number indicating that multiple questions need to be asked and user cannot just stop with 1 question. KAIKAKU projects may be necessitated by new technology or market conditions and may involve introduction of: new knowledge (or) new strategies (or) new approaches (or) new production techniques (or) new equipment. KAKUSHIN projects may be necessitated by new ideas or innovative products /services to enable/sustain business growth. E.g. Implementing 5S, redesigning assembly line and so on E.g. Changing to a new Raw material for a product, Introducing CNC lathe machines or robots to a production or assembly line. E.g Introduction of a web portal for application processing removing a manual process. What would a company lose if one of these as a concept was not utilised? Kaizen is about continuously improving: everyday, everyone and everywhere. Many small improvements implemented with Kaizen produce faster results (accumulated over time) with less risk. Without Kaizen initiatives, a company would be unable to make such small improvements and the risk to improve would be high. Waste (Muda) would significantly increase reducing ROI and causing a drop in OEE Overall Equipment Efficiency. Kaikaku is about making a revolutionary change to the existing situation. When Kaizen (Continuous Improvement) efforts stagnate, and do not produce necessary or expected results when compared to the efforts put in, then Management may decide for drastic improvement Project or Kaikaku. This is also taken up as a project. Once completed this provides a new starting place for future Kaizen continuous improvement efforts. Without utilizing Kaikaku concept a company may be unable to go to the next level. Kakushin is about making innovative changes for transformation and reforming the current situation. Without innovation, it would be very difficult for any company to sustain and grow. Innovative products, services (Value added) help a company to differentiate itself from competition and remain significancant. Kaikaku projects can be of four different types: [1] 1. Locally innovative - Capital intensive E.g. an installation of robot automation in a factory is not new to the industry in general, but may be new to the company. The decision is strategically grounded and could mean higher costs 2. Locally innovative - Operation close E.g. the introduction of conventional methods Six Sigma or TPM may be new to the company. The direct cost is relatively small 3. Radically innovative - Capital intensive E.g. the introduction of a new and innovative production technology 4. Radically innovative - Operation close E.g. the introduction of new and innovative production solutions that are new to the industry [1] Yuji Yamamoto; et al. (2010). KAIKAKU An inspirational and Introduction [In Swedish]. Eskilstuna, Sweden: Malardalen University. https://en.wikipedia.org/wiki/Kaikaku https://en.wikipedia.org/wiki/Kaizen https://www.linkedin.com/pulse/3-essential-ks-organizational-success-kaizen-kaikaku-mogharei-pmp https://www.pinkelephantasia.com/kaizen-kaikaku-kakushin/