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Q46. Segmenting large sets of data into smaller segments is a common practice when analysis is done on data sets. In what different ways does segmentation relate to Root Cause Analysis? Segmentation is a useful technique used to understand the customer’s similarities and differences in the market. It will help you to understand the current and future prospects of the products and the customer’s requirements in the market, which will in turn make the organization to introduce new products or modify the existing ones and better communication to the customer who is interested to buy the product. It was traditionally used by the marketers in the market to get the close view of it. It is based on the principle of identifying the variables that can predict the customer’s behavior and the characteristics, using a mix of quantitative and qualitative approaches. Why segmentation is useful? 1. Segmentation provides us the deeper insight of the problems and help us identify the relevant possible solutions. 2. It helps us to understand the customer requirements in the market, so that the company can introduce new product or modify the existing one to meet the needs of the customer. 3. It will help you identify the real root cause by diving the entire fragment of business into categories defined. 4. Helps in decision making, once the real root cause is identified. When it is recommended? Segmentation is recommended to focus Customer Research on the most important customers: • Segmentation divides customers into groups with similar needs that value the same outcomes and look for the same solutions • Segmentation should be natural (the way the customers actually behave) and stable over time • Avoid artificial segmentations such as geographic location, price point, size, vertical industry or standard industrial code that mix customers with significantly different needs • Write a definition of each customer segment and representative customers in the segment and review them with the sponsoring business team Segmentation: There are basic 9 segmentations which can be clubbed into 3 categories and are as follows. 1. Industry 2. Company 3. Individual 1. Industry: It is grouping of similar businesses like healthcare, BPO, etc. the attributes identified and studied in this segment are type of business, growth & revenue, geographic and demographic locations of the company, etc along with deep dive into other important attributes like size, substitutes and sales cycle Subcategories Description Example Size Understanding the size of the spending budge twill provide inputs to the pricing model. It will also help in understanding the challenges and overcoming it. Some industries would be early technology adopters. In such case, the spending budgets by various industries like security software, application software, business software and internet software to be colleted and listed for pricing model. Substitutes Product manager should frequently communicate to the customer in terms of problem solving. If the product delivered does not meet the needs of him, then what is it he is expecting more and what alternative he is using. Such questions asked to upgrade the product or modify it within hte policy regulatory norms. Change is important but cost effective. If the new dress is torn which is bought from the retailer A, the product can be bought from the retailer B by the customer if he is satisfied with A vendor and if he doesn't try to improve / solve the issue. Sales Cycle once the product lifecycle is completed, then the product sales cycle starts. It is very important that the trends to be identified basis historical data and create patterns in sales considering future deals. If Company A sells 200 products last year, then they can study the market for product innovation and increase the sales if required. Relating Industry segments to RCA: Yes. It is related. By studying the segment of industry in terms of size, geographic location etc should really contribute to the root causes. Eg. If a company works in metropolitan city (lets say Chennai) the traffic is huge and the IT park is as well crowded. It the person is said to come at 9 am in the morning for completing the backlog of that day’s target(200), the person is held up in traffic. When the same company also works of moderately populated a semi urban area, the person would be able to reach office on time to complete the backlog. As earlier said, the root cause for not completing the backlog is coming to office late in metropolitan city. Tools used: - Pareto analysis - Win loss analysis 2. Company: Where in industry we would have looked in quantitative attributes and here we might look into qualitative attributes like how the company can create value proposition to the customer in terms of products or services given. Subcategories Description Example Purchasing Companies adopt different marketing strategies like cost optimization and innovation optimization. Understanding the company's strategy will help focus on the problem areas easily and understanding the company's business goals are also equally important A company focused on cost optimization will start focusing on the selling the products with different marketing messages which talks about the product's innovations and its effective usage. Process In most of the companies, the communication is top down and some has bottom ups. It talks about how effectively the business processes work and interlinked. How effective the management can solve the problems and make decisions. if the company adopts lean and agile, this means they need change. So the product also should facilitate the change and embrace it for 100% quality. People People in the company are directly involved in product life cycle and till it gets delivered to the customer. Hence it is important to understand their mindset since they are the ones involved in producing good quality products. When we sell medicines to the customer, it is also important that we need to tell them the risks involved in taking up the medicines. Hence it should be taken only under guidance. Relating company segments to RCA: It is obvious that the company segmentation is related to root cause anlaysis. The businsess processes involved in the company are studied using process maps and waste is identified. And process maps are used to convert it into value streams and root cause is as well identified. Eg. Step 1 Step 2 Step 3 Step 4 Step 5 10 minutes 20 minutes 15 minutes 10 minutes 10 minutes Value Waste - can be reduced to 5 minutes using SCAR (Simplify, Combine, Automate or Remove) technique Value Value Value Tools used: - Pareto - Process map - VSM 3. Individual: Individual is nothing but your customer who purchases the product or the receiver of the service provided. Quantitative factors like demographic information can provide insight into product adoption and qualitative attributes like demeanor and disposition can provide insight into the personal motivation for product selection. Subcategories Description Example Disposition It is important how the product add values to the customer and simplifies day's living. It is important the customer should be satisfied with their needs met by the organization when aligned with their organization’s goals, will definitely go a long way even if there are few short comings. if the mobile is used to make calls, the camera is an additional feature. Given with it, a clarity with high pixels will delight the customer at the same price. Demeanor understanding this focuses on the learning process of general guidelines and the principles followed. Some may value the change and some may not. It is as important the value should be imposed in all minds through multiple learning sessions. If the company adopts the Operational excellence, then person then strive for excellency in the products sold to the customer. It should be defect free and match the customer's needs as they fit in the organization's goals. Demographics Demographics like age, sex, education etc plays a major role in segmentation. Because, the roles performed In the organization also depends on the age of the generations. A mobile with additional feature like camera clarity, unbreakable feature, voice recognitions will delight the youngsters whereas the old people will only use the phone for calling others. Relations of individual with RCA: In a medical coding company, a person with BCA computers are hired and given some charts to code. After coding is completed, another BCA guy as auditor audits and finds no error and sends it to client. At the customer end, randomly they check 10 reports out of 100 reports submitted. They find all 10 reports to be erroneous and not acceptable. The prime root cause is education. This is understood if the proper segmentation is done. Tools used: - Customer feedbacks - Customer surveys / discussions Conclusion: This finite set of workable information provides a good insight of any problems arised. The short term goals are fixed to rectify the issues quicker. This 9 segments broadly explained will throw insights on the root causes and helps the management in decision making. When the product is not meeting the customer’s needs, then start looking into the segmentation to find the real root cause. Understanding the key is the only best way to hone the problem. But should we have to wait for the process to fail? No. Even if the company wants to innovate the segmentation is the best tool to identify which area to be innovated. Reference: https://measuringu.com/better-segmentation/ thanks Kavitha

Segmentation.docx

Segmentation could be called as the process of dividing the population into distinct subsets or segments that behave in the same way or have similar features. As each segment is homogeneous, they are likely to respond similarly, within. For effective segmentation, segments need to be measurable (The very purpose is to measure effects within a segment and between segments), identifiable (This is mandatory if all data is to be correctly segmented), accessible (The efforts at segmenting should not become more than the benefits obtained by solving the problem), actionable (The segments arrived at must be practically feasible to work on) and large enough to be effective (Each segment should have a critical enough mass). The segments arrived at need to be based on a logic that can be related to the problem being investigated or business goals being pursued. These questions may help drive the analysis of the segmented data. · Is there one defect category that occurs more frequently than others? · What factors contribute the most to the variation in Project Y? · Do results differ across factors? Segmentation, sub-segmentation, cross-segmentation and matrix-segmentation divide the data population into homogeneous data segments. Multiple data segmentation can be used effectively to isolate problem transactions that give us a handle to work on solving the problem. The criteria for this segmentation can be the natural transaction categories in the process or specially created criteria. In the case of the former i.e. segmentation along transaction categories, the population is split into various segments and extent to which the transactions in each segment have been impacted by the problem is measured. This will help in identifying those segments which are most impacted adversely by the problem. Thus, the problem segment or segments have been identified. Then, by identifying the characteristics and features of these problem segment or segments that are significantly different from those of the other segments which are not impacted by the problem, it is possible to identify those characteristic or feature that are most impacted by the problem. These could be the immediate cause of the problem. This will then need to be root-cause analysed and appropriate controls implemented. This way, it is possible to avoid shooting in the dark when trying to find the root cause of the problem. Segmentation along transaction categories has helped to narrow down the areas to be root cause analysed, thus saving time, effort and money in the problem solving exercise. In the case of the latter, i.e. segmentation along specially created criteria, it is possible to formulate criteria along suspected or potential root causes. By segmenting the data population along potential root causes, the segment or segments impacted most by the problem can be identified and along with the segments, the root causes themselves can be identified. Here, by almost directly identifying the root cause, even more savings of time, effort and money can be achieved. Here, data segmentation is actually being used to verify root causes. Going further on root causes, Segmentation analysis also assists us in planning and implementing different corrective actions for different segments that contribute effectively to improvement. A repetition of the segmentation post improvements and measurement of the problem impact will reveal the effectiveness of the corrective actions implemented. Thus Segmentation Analysis supports preparation for, conduct of and verifying effectiveness of root cause analysis.

One of the very common method used for dealing with a large data is to “stratify” the data into groups. The stratification may be done in multiple ways depending upon the situation and purpose for analyzing the data. For instance, if we are studying national sales data to understand the areas having improvement opportunities, the data may be stratified into groups for each state. Other ways of stratifying may be on age, income levels, education levels, month wise etc. The stratification groups need to be decided based on the objective that is being pursued. Such segmentation will help us to represent the data using a bar chart and helps comparing the variation between the groups. It helps in narrowing our focus on areas that depict an abnormal problem, or areas of opportunity. During root cause analysis, such segmentation is one of the first steps adopted. It also helps in evolving a Pareto diagram and apply the 80 / 20 rule. Where deeper probing and analysis are required, it is a good idea to do the segmentation first, so that the efforts for such deeper analysis may be restricted to the volumes, shortlisted based on the segmentation. Sometimes when we have a large amount of data; say for instance a product failure data for a period of six months, it would help to segment the data for certain time period, maybe month wise, and week wise. Of if we know of certain factors that we suspect to influence the failure under study, the data may be appropriately segmented to see a comparison of the failure rates between those events. A good segmentation helps in optimizing the efforts spent for root cause analysis and facilitates arriving at the root cause faster.