Summer Internship Report on Madura Garments

Project Report On Improving Service Level for Institutional Sales SUBMITTED FOR THE PARTIAL FULFILMENT OF POST GRADUATE DIPLOMA IN INDUSTRIAL MANAGEMENT (PGDIM) By Puneet Verma Roll No. 105 PGDIM – 18 Under the guidance of [pic] National Institute of Industrial Engineering (NITIE), Vihar Lake, P. O. NITIE, Mumbai 400 087 Date of Submission: _ _ _ _ _ _ _ Certificate of Supervision This is to certify that Puneet Verma, student of PGDIM, Batch No. 18 has successfully completed the project titled – “Improving Service Level for Institutional Sales”, nder the guidance of Mrs. Sadhana Ghosh (NITIE) from 11th Jan 2013 to 15th March 2013.

Based on the professional work done by him, this report is being submitted for the partial fulfillment of Post-Graduation Diploma in Industrial Management at NITIE, Mumbai Signature Faculty Guide Acknowledgement I wish to extend my sincere and heartfelt gratitude to my guide Mrs. Sadhana Ghosh(Professor, NITIE), whose Guidance and help constantly helped and motivated me during the entire tenure of the project. I am able to say with conviction that I have immensely benefited.

Puneet Verma PGDIM-18 Executive Summary The apparel companies cater to various channels such as Department Stores, Trade, Organized Retail etc. Institutional Sales is a nascent business channel that caters to the demand from Institutional customers i. e organizations. Sales to this channel are generally in the form of bulk orders at volume discounts. For example, a pharmaceutical company orders through this channel for gifting shirt to doctors. The majority of the business of apparel organizations comes in through Trade and Department store channels.

Orders for those channels come in during the Trade shows held twice a year 6 months prior to the launch of a season (Spring-Summer or Autumn-Winter).

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Sourcing and production plan for those channels so are essentially done against fixed orders. But for Institutional Channel orders are not predetermined and customers come in with orders with very short lead time. This makes sourcing and manufacturing strategy for this process completely different from traditional channels. Currently the company Madura Garments (for reference and data) is not able to service these customers at a satisfactory level applying the business processes in place.

This is contributed by the fact that the normal business model is significantly different from the requirements of this channel. The approach adopted was to first study the as-is business processes in place and review the past data to ascertain the capability of the current system in place. Next the problems in the current system were identified irrespective of whether the problem was a process or people related problem. A revised process flow was the proposed which will enable the company to service Institutional customers at a satisfactory rate.

Lean Six Sigma methodology was adopted to approach the problem using a DMAIC model. The final list of recommendations include changes in the current business process in the short time frame for immediate enhancement of service levels and long term changes to improve process capability to ramp up the business capabilities. Table of Contents Project Report1 Certificate of Supervision2 Acknowledgements4 Executive Summary5 1. Introduction8 2. Need & Significance of the Project11 3. Objective12 4. Literature Review………………………………………………………………………………………. 3 4. 1 DMAIC………………………………………………………………………………………………… 13 4. 2 Fishbone Diagram…………………………………………………………………………………. 15 4. 3 Cause and Effect Matrix…………………………………………………………………………. 17 4. 4 Failure Mode Effect Analysis………………………………………………………………….. 18 5. Methodology…………………………………………………………………………………………….. 4 5. 1: Understand the current market and business scenario……………………………….. 25 5. 1. 1: Market Scenario: ………………………………………………………………………….. 25 5. 1. 2: Agent Performance: ……………………………………………………………………… 29 5. 1. 3: Business processes: ……………………………………………………………………… 30 5. 1. 4: Key Points: …………………………………………………………………………………. 5 5. 2: Ascertain the current service level of the system…………………………………….. 36 5. 3: Identifying and Defining Problems……………………………………………………….. 37 5. 3. 1: Fishbone Diagram: ……………………………………………………………………… 37 5. 3. 2: Cause and Effect Matrix: ……………………………………………………………… 38 5. 3. 3: Failure Mode Effect Analysis:………………………………………………………… 39 5. 3. : Principal Issues: …………………………………………………………………………… 41 5. 4: Process Improvement Plan…………………………………………………………………… 42 5. 4. 1: Short term changes: ……………………………………………………………………… 43 5. 4. 2: Long term plans:…………………………………………………………………………… 47 5. 5: Process Control………………………………………………………………………………….. 1 6. References:……………………………………………………………………………………………….. 54 Introduction The Aditya Birla Group is in the League of Fortune 500. It is anchored by an extraordinary force of 100,000 employees, belonging to 25 different nationalities. In India the group has been adjudged “ The Best Employer in India and among the Top 20 in Asia” by the Hewitt-Economic Times and Wall Street Journal Study 2007. Over 50 percent of it revenues flows from its overseas operations.

The several Group companies under Aditya Birla Group are Grasim, Hindalco, Aditya Birla Nuvo, Essel Mining, Aditya Birla Retail Limited. Aditya Birla Nuvo Limited is a diversified conglomerate and the platform that has launched many new businesses for India’s Premier Business house, the Aditya Birla Group. Aditya Birla Nuvo has a dozen businesses under its fold, ranging from textiles to telecom. As a leading player, Aditya Birla Nuvo ranks as
• The country’s largest premium branded Apparel Company : Madura Garments
• Largest Manufacture of linen fabric in India
• India’s largest and the world’s fourth largest producer of insulators The second largest producer of carbon black in India
• India’s second largest producer of viscose filament yarn (VFY) Aditya Birla Nuvo’s Business: Garments (Branded Apparel) Madura Garments, a division of Aditya Birla Nuvo is India’s leading apparel retail company. It enjoys market leadership in the branded garments business through its power and popular lifestyle brands – Louis Phillipe, Van Heusen, Allen Solly and Peter England. The company has also entered into a distribution agreement with the International brand Esprit and has opened exclusive brand outlets.

It has 2 successful store formats The Collective and PEOPLE. Madura Garments has exclusive showroom space which includes several large format brands outlets of world-class standards, providing top quality retail experience to the consumers. It also has a high visible presence in large department and multi brand stores. The thrust is on brand building through development of innovative new merchandise, exciting communication campaigns and enhancing the product portfolio. The overall marketing strategy has been move from a “Wardrobe Brand” to a “Lifestyle” Brand.

The company has won many coveted awards in the fashion world like the “Best Retailer of the Year, Best Apparel Company of the Year, Best Trouser Brand of the Year, Best Smart Casual Brand of the Year” etc. , at well known for a such as Reid Taylor Awards and Images Fashion Awards. To bolster its presence significantly in the exploding apparel retail sector, the company has started retailing its life style brand and affordable popular brands through two new formats- Madura Garments Lifestyle Retail Company Limited and Peter England Fashions and Retail Limited. Contract Manufacturing

Madura Garments Exports limited is a wholly owned subsidiary of Aditya Birla Nuvo focusing on garment exports. It is an integrated player in the apparel industry with interest in manufacturing exports of wovens, knits and Full Service Provider business. The company has modern manufacturing facilities and caters to customers like Marks & Spencer, Next, Blackberry, Arrow, Tommy Hilfiger and Menswear House. The organization delivers from design to delivery of merchandise at the customer warehouse. [pic] 2. Need & Significance of the Project Madura Fashion & Lifestyle has a fast growing institutionalized sales business.

In December 2011, institutional sales hit an all time high of 4. 43 crores for a month. For FY12 institutional sales will account for Rs 14 crores with a high profitability (CBA). This channel has grown by four times in terms of sales over the last four years. However, the on time in full order execution for this channel continues to be poor. Delayed deliveries and missed opportunities continue to limit the growth of this channel. In this context, there is a need to study the supply chain (planning and execution) of this channel to identify the root cause for service failures and define process and system changes to tackle these. 3.

• Mapping of as-is supply chain (planning process, order capture and order fulfillment process): The current business process that is being followed to cater to the customer demands
• Establish current service level for this channel: The order service level of the channel derived from the past data that has been obtained
• Identify root cause for service failures in institutional business: The major causes that leads to an unsatisfactory service level related to people, process, business issues 4. Literature Review Six Sigma Methodologies: Six Sigma is a business management strategy, originally developed by Motorola in 1986.

Six Sigma became well known after Jack Welch made it a central focus of his business strategy at General Electric in 1995, and today it is widely used in many sectors of industry. Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimizing variabilityin manufacturing and business processes. It uses a set of quality management methods, including statistical methods, and creates a special infrastructure of people within the organization (“Black Belts”, “Green Belts”, etc. ) who are experts in these methods.

Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified financial targets (cost reduction and/or profit increase). The term Six Sigma originated from terminology associated with manufacturing, specifically terms associated with statistical modeling of manufacturing processes. The maturity of a manufacturing process can be described by a sigma rating indicating its yield, or the percentage of defect-free products it creates. A six sigma process is one in which 99. 99966% of the products manufactured are statistically expected to be free of defects (3. defects per million). Motorola set a goal of “six sigma” for all of its manufacturing operations, and this goal became a byword for the management and engineering practices used to achieve it. 4. 1: DMAIC The DMAIC project methodology has five phases: ? Define the problem, the voice of the customer, and the project goals, specifically. ? Measure key aspects of the current process and collect relevant data. ? Analyze the data to investigate and verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered.

Seek out root cause of the defect under investigation. ? Improve or optimize the current process based upon data analysis using techniques such as design of experiments, poka yoke or mistake proofing, and standard work to create a new, future state process. Set up pilot runs to establish process capability. ? Control the future state process to ensure that any deviations from target are corrected before they result in defects. Implement control systems such as statistical process control, production boards, visual workplaces, and continuously monitor the process.

Some organizations add a Recognize step at the beginning, which is to recognize the right problem to work on, thus yielding an RDMAIC methodology. 4. 2: Operation Definition: Recall the quote in the “first step” section of this site, “You can manage, what you can measure; you can measure, what you can define; you can define, what you can understand”. Operational definition is the first step towards effective management. It helps us build a clear understanding of a concept or a phenomenon so that it can be unambiguously measured. Let us take a very simple example to understand the need and the concept of operational definition.

Let us imagine a situation that we wish to buy an all-purpose shirt with 50% cotton and 50% polyester. Would you accept a shirt whose front is made up of 100% cotton cloth and the back made of 100% polyester cloth? Surely not! Clearly we need to (operationally) define what we need. A better expression would be that we need a shirt made up of a cloth having even distribution of cotton and polyester fibers and their proportion by weight (or may be by number) is equal. So far so good, but we also need to have a mechanism to test it.

In this case, we can send the shirt to a lab where randomly selected two areas (say 1 cm x 1 cm) – one from the back and one from the front are examined for the contents. The lab reports that group of two fibers of each – polyester and cotton are interwoven to make this clothe. Did we mean alternate fibers of polyester and cotton or something else? We now discover that we even need to define “even distribution”. In a business management scenario, common words such as good, reliable, and accurate (etc. ) can have multiple meanings unless they are (operationally) defined in a specific context.

So how do we construct an operational definition? The process is explained with the help of an example in the following figure: [pic] Document the outcome of each process step and that becomes the operational definition. The operation definition must be tested before it is rolled out. 4. 2: Ishikawa’s Fishbone Diagram: The fishbone diagram is a graphical method for finding the root causes of an effect. The effect can be either a negative one, such as a process defect or an undue process variation; or a positive one, such as a desired process outcome.

Kaoru Ishikawa, a famous Japanese consultant developed this method in the 1960s. It is also known as “Cause-and-Effect Diagram” or “Ishikawa Diagram”. The balance chapter details the steps required to construct a fishbone diagram. The example effect to illustrate the concept is “high petrol consumption in a car”. Step I Identify the process effect to be analysed. Develop an Operational Definition to ensure that it is clearly understood. Write the effect in a box on the right side and draw a horizontal arrow from left to right that touches the box as illustrated in the figure below. [pic] Step II

Identify the main categories of causes resulting in the effect under consideration. These categories can easily be selected from the applicable six key process elements. These process elements are people, environment, material, method, machinery, and measurement. Add selected categories in the diagram as illustrated in the following figure. [pic] Step III Identify as many causes under each category and add them to the corresponding category. Detail each cause further (recursively) to the lowest level possible. [pic] Analyse this diagram to identify the causes that require deeper investigation.

As fishbone diagram identify only potential causes, it may be a good idea to use a Pareto Chart to determine the cause(s) to focus on first. 4. 3: Cause & Effect Matrix The Cause and Effect Matrix is a tool which is used to prioritise potential causes by examining their relationship with the CTQs. CTQ’s are placed on the top of the matrix and causes are place along the left side. The CTQ’s are ranked in terms of importance. The relationship between the causes and CTQs are ranked. An overall score is calculated and the cause with the highest overall score should be addressed first because they will have the largest impact on the CTQs.

Steps 1. List the CTQs across the top of a matrix. 2. Rank and assign scores to each CTQ according to its importance to the customer. 3. List the causes on the left side of the matrix 4. Determine correlation scores between each cause and CTQ based on the strength of their relationship (E. g. 1 – weak, 3 – some, 9 – strong) 5. Cross multiply correlation scores with priority scores and add across for each cause 6. Create a Pareto chart and focus on the causes with the higher overall scores. The following diagram is a C&E matrix template from ProcessMA. [pic] 4. : Failure Mode Effect Analysis: A failure modes and effects analysis (FMEA) is a procedure in product development, systems engineering and operations management for analysis of potential failure modes within a system for classification by the severity and likelihood of the failures. A successful FMEA activity helps a team to identify potential failure modes based on past experience with similar products or processes, enabling the team to design those failures out of the system with the minimum of effort and resource expenditure, thereby reducing development time and costs.

Because it forces a review of functions and functional requirements, it also serves as a form of design review. It is widely used in manufacturing industries in various phases of the product life cycle and is now increasingly finding use in the service industry. Failure modes are any errors or defects in a process, design, or item, especially those that affect the intended function of the product and or process, and can be potential or actual. Effects analysis refers to studying the consequences of those failures.

The pre-work The process for conducting an FMEA is typically developed in three main phases, in which appropriate actions need to be defined. Before starting with an FMEA, several other techniques are frequently employed to ensure that robustness and history are included in the analysis. A robustness analysis can be obtained from interface matrices, boundary diagrams, and parameter diagrams. Failures are often found from external ‘noise factors’ and from shared interfaces with other parts and/or systems.

Typically, a description of the system and its function is developed, considering both intentional and unintentional uses. A block diagram of the system is often created for inclusion with the FMEA, giving an overview of the major components or process steps and how they are related. These are called logical relations around which the FMEA can be developed. The primary FME document or ‘worksheet’ lists all of the items or functions of the system in a logical manner, typically based on the block diagram. NOTE: Above shown example format is not in line with mil. td 1629 or Civil Aerospace practise. The basic terms as given in first paragraph of this page are not available in this template! Step 1: Occurrence In this step it is necessary to look at the cause of a failure mode and the number of times it occurs. This can be done by looking at similar products or processes and the failure modes that have been documented for them in the past. A failure cause is looked upon as a design weakness. All the potential causes for a failure mode should be identified and documented. Again this should be in technical terms.

Examples of causes are: erroneous algorithms, excessive voltage or improper operating conditions. A failure mode is given an occurrence ranking (O), again 1–10. Actions need to be determined if the occurrence is high (meaning > 4 for non-safety failure modes and > 1 when the severity-number from step 2 is 9 or 10). This step is called the detailed development section of the FMEA process. Occurrence also can be defined as %. If a non-safety issue happened less than 1%, we can give 1 to it. It is based on your product and customer specification. Rating |Meaning | |1 |No known occurrences on similar products or processes | |2/3 |Low (relatively few failures) | |4/5/6 |Moderate (occasional failures) | |7/8 |High (repeated failures) | |9/10 |Very high (failure is almost inevitable) | Step 2: Severity

Determine all failure modes based on the functional requirements and their effects. Examples of failure modes are: Electrical short-circuiting, corrosion or deformation. A failure mode in one component can lead to a failure mode in another component, therefore each failure mode should be listed in technical terms and for function. Hereafter the ultimate effect of each failure mode needs to be considered. A failure effect is defined as the result of a failure mode on the function of the system as perceived by the user. In this way it is convenient to write these effects down in terms of what the user might see or experience.

Examples of failure effects are: degraded performance, noise or even injury to a user. Each effect is given a severity number (S) from 1 (no danger) to 10 (critical). These numbers help an engineer to prioritize the failure modes and their effects. If the sensitivity of an effect has a number 9 or 10, actions are considered to change the design by eliminating the failure mode, if possible, or protecting the user from the effect. A severity rating of 9 or 10 is generally reserved for those effects which would cause injury to a user or otherwise result in litigation. Rating |Meaning | |1 |No effect | |2 |Very minor (only noticed by discriminating customers) | |3 |Minor (affects very little of the system, noticed by average customer) | |4/5/6 |Moderate (most customers are annoyed) | |7/8 |High (causes a loss of primary function; customers are issatisfied) | |9/10 |Very high and hazardous (product becomes inoperative; customers angered; the failure may result unsafe operation and | | |possible injury) | Step 3: Detection When appropriate actions are determined, it is necessary to test their efficiency. In addition, design verification is needed. The proper inspection methods need to be chosen. First, an engineer should look at the current controls of the system that prevent failure modes from occurring or which detect the failure before it reaches the customer.

Hereafter one should identify testing, analysis, monitoring and other techniques that can be or have been used on similar systems to detect failures. From these controls an engineer can learn how likely it is for a failure to be identified or detected. Each combination from the previous 2 steps receives a detection number (D). This ranks the ability of planned tests and inspections to remove defects or detect failure modes in time. The assigned detection number measures the risk that the failure will escape detection. A high detection number indicates that the chances are high that the failure will escape detection, or in other words, that the chances of detection are low. Rating |Meaning | |1 |Certain – fault will be caught on test | |2 |Almost Certain | |3 |High | |4/5/6 |Moderate | |7/8 |Low | |9/10 |Fault will be passed to customer undetected | After these three basic steps, risk priority numbers (RPN) are calculated Risk priority number (RPN) – RPN play an important part in the choice of an action against failure modes. They are threshold values in the evaluation of these actions.

After ranking the severity, occurrence and detect ability the RPN can be easily calculated by multiplying these three numbers: RPN = S ? O ? D This has to be done for the entire process and/or design. Once this is done it is easy to determine the areas of greatest concern. The failure modes that have the highest RPN should be given the highest priority for corrective action. This means it is not always the failure modes with the highest severity numbers that should be treated first. There could be less severe failures, but which occur more often and are less detectable. After these values are allocated, recommended actions with targets, responsibility and dates of implementation are noted.

These actions can include specific inspection, testing or quality procedures, redesign (such as selection of new components), adding more redundancy and limiting environmental stresses or operating range. Once the actions have been implemented in the design/process, the new RPN should be checked, to confirm the improvements. These tests are often put in graphs, for easy visualization. Whenever a design or a process changes, an FMEA should be updated. A few logical but important thoughts come in mind: ? Try to eliminate the failure mode (some failures are more preventable than others) ? Minimize the severity of the failure ? Reduce the occurrence of the failure mode ? Improve the detection 5. Methodology

A brief outline of the methodology adopted in the project is given below: 1. Understand the current market and business scenario a. Gather historical data from the system to analyze market condition b. Analyze trends and patterns in the sales figures c. Study the current business processes and map the material and information flow 2. Ascertain the service level that the system currently operates at a. Gather data for a specified period b. Ascertain the service level for that period subjected to constraints c. Interpret the data to assess system capability 3. Identify and define the issues a. Identify the principal issues currently affecting service levels b.

Use Lean Six Sigma Methodologies to structure the analysis process 4. Propose a Process improvement plan that addresses the need of the system a. Structure all the issues in the current system systematically b. Propose solutions which can positively affect the major issues c. Propose solutions for current service level improvement and long term improvement of business capabilities 5. Propose metrics to effectively control the process once implemented a. Propose metrics that can capture the effectiveness of the system in place 5. 1: Understand the current market and business scenario 5. 1. 1: Market Scenario: Brandwise sales for FY11-12
• 85% of sales contributed by LP, VH
• 62% of LP sales contributed by December sales
• 31% of overall sales in December [pic] Overall Sales volume for FY ‘11-‘12
• Business runs on relationship based contacts. A client can take away a number of his contacts from a business.
• Period for gifting by companies: April ( June
• Companies want products by March
• So ideally order should be placed by November/December
• Educating customers about the functioning of the business is important to obtain feasible targets
• Customers generally specify the brand, but may also sometimes specify the colour to coordinate with an event A serviced customer will not look for an alternate source for subsequent orders
• A customer may order goods for gifting or internal use
• Price sensitive customers
• Currently Pharmaceutical is the major player, but new avenues can be explored (Essar Steel uniform order)
• Pharmaceutical companies generally demand a turnaround of 30 days
• Pharmaceutical sector generally not affected by downturns
• Delivery in correct time and correct order quantity
• If delivery is correct then a premium price may be charged
• Priority of delivery is low in this channel, the priority should be highest
• Customers may reject the order if delivery is delayed for a day. Events. Priority is low as the volume of business is low in comparison with overall business volume
• If service level is high then company bargaining power will also be high
• Market is susceptible to economic downturns (no order from IT firms for the past 3 yrs)
• Agents display a variety of goods to the customer. May sell a rival brand or a different product.
• Forecasting is difficult as a company may choose to give a different gift the next year
• Satisfied customers does not ensure return customer but provides base for word of mouth marketing
• Leverage on the firms brand names
• High profit business where the discount depends on the volume of products ordered. No returned goods.
• Dealings are made with top management, so client facing operations should be capably handled Customer |Sum of Quantity |Sum of Gross | | | |Total | |Mankind pharma ltd |107500 |55623750 | |Madhuram apparels |14019 |11155274 | |Lupin limited |10460 |9936990 | |Addon holding pvt ltd. |12781 |8356870 | |Supra garments pvt limited |9098 |7067832 | |Padma international corporation |10188 |6298490 | |Unichem laboratories ltd |6555 |5004589. 37 | |Biocon limited |4980 |3650530 | |M/S.

Glaxo smithline ltd |3424 |3589379 | |Clairemont enterprises |8138 |3544110 | |Emcure pharmaceuticals limited |5395 |3426004 | |IPCA laboratories limited |3284 |2891923 | |Saffron enterprises (p) ltd. |4118 |2855504 | |Geno pharmaceuticals ltd |4200 |2520000 | |Government of India |3000 |1875000 | |Society of Petroleum Geophysicists |2028 |1817540 | |Pidilite industries ltd |2500 |1650206. 25 |
• 53 customers were serviced where ordered quantity was over 100
• 9 orders were serviced where the ordered quantity was more than 5000
• 17 orders were worth more than Rs 10,00,000 The revenue generated from these orders contribute to 88% of the overall revenue
• Orders exceeding 5000 contributed to 74% of overall revenue
• Revenue per unit from large orders generally lesser than that from medium/small orders 5. 1. 2: Agent Performance: Agentwise breakup of sales amount Proportion of sales made through agents as opposed to directly 5. 1. 3: Business processes: [pic] Current scenario of sourcing options:
• Sourcing not dependent on Core or Fashion, depends on how Core is defined
• Mills are large entities and Madura cannot consume their entire produce
• Sourcing time depends on overall demand for a fabric in the market
• Sourcing strategy dependant on individual Style Codes For a style code with constant Y-o-Y demand an buffer inventory of 1000 mts is maintained at either factory RM level or supplier level
• A fabric from the current season, brand checks whether they can sell the product at the full priced market , then they service the institutionalized sales customers
• No separate sourcing strategy for institutional channel
• Sourcing strategy fixed at the start of the season
• Products manufactured against fixed orders
• Fabric sourced to meet only the fixed demand
• Excess fabric stock due to customers cancelling orders
• ARS (Automated Replenishment System) not affecting sourcing
• Sourcing for one style code done only once Sourcing is done according to the preplanned production schedule
• Fabric is not allocated to any channel, the FG is allocated to a specific channel
• If fabric is not sold off to the specific channel then the stock is offered to the same/ different channel the next season
• Once the plan for the season has been made the plan is not subjected to any major change 5. 1. 4: Key Points: Plant Capacity:
• Plant capacity is allocated to various brands depending on their orders from trade shows/forecasts
• The allocated plant capacity is fixed for a year and is reviewed at the beginning of the season
• Excess fabric stock from previous season piled-up at factory (inventory build-up) Production Planning: No separate capacity is present to cater to institutional sales
• Brands utilize excess capacity or reschedule work orders to cater to Institutional customers
• Service level dependent on demand from other traditional channels Institutional Orders:
• Factory receives direct enquiry from the Institutional Sales team
• Factory check reserve stock and ready sourcing options for fabric and trims (lower lead time to source trims than brands)
• Schedule production plan according to excess capacity available i. e unutilized by the brands 5. 2: Ascertain the current service level of the system Data Collection:
• Data collected from mail records from Jan ( Mar 2012 Enquiries for less than 100 units neglected
• Orders divided into separate groups depending on ordered volume
• Overall service levels for the period is at 35%
• Current process can service only about 16% of the total volume of demand
• None of the 10000+ orders have been serviced
• Service level for orders between 2000-10000 is the highest
• Excluding the very large orders, the company serviced 40% of the total volume of demand |Row Labels |Accepted |Despatched |Enquiry |Rejected |Grand Total |Service Level | |500-2000 |7 |5 |1 |21 |34 |0. 6 | |2000-10000 |2 |4 |2 |5 |13 |0. 55 | |10000+ | | |2 |4 |6 |0 | |Grand Total |10 |15 |5 |47 |77 |0. 35 | |100-500 |225 |1725 | |3380 |5330 |0. 37 | |500-2000 |5240 |4050 |1000 |18400 |28690 |0. 34 | |2000-10000 |14380 |11500 |9500 |33500 |68880 |0. 4 | |10000+ | | |51000 |144000 |195000 |0 | |Grand Total |19845 |17533 | |High Turnaround Time |Fabric catalogue not provided for IS |567 | |High Turnaround Time |Information is decentralized |567 | |Unavailable fabric |Low clarity regarding reserve stock level |441 | |Unavailable fabric |Sourcing not done for Institutional Channel |441 | |High Turnaround Time |Low clarity regarding reserve stock level |441 | |Low Priority of Institutional sales |Volume of business w. r. overall business |441 | |Unavailable fabric |Volume orders |405 | |Unavailable capacity |No separate plant capacity for Institutional customers |245 | |Low Profitability |Discount margin offered |245 | |High Turnaround Time |Response time to get back on a query |245 | |Unavailable capacity |Volume orders |189 | |Unavailable capacity |Current utilization of factory for retail channels |175 | |Delayed Delivery |No separate plant capacity for Institutional customers |175 | |Low Profitability |Price sensitive customers |147 | |Delayed Delivery |Current utilization of factory for retail channels |125 | |Low Priority of Institutional sales |Price sensitive customers |105 | |Competitor Action |NOS range not always available |105 | |Competitor Action |Agents working for multiple companies |45 | 5. 3. 4: Principal Issues: Fabric Stock:
• Fabric catalogue is not provided for IS leading to lack of clarity for agents and IS team
• Reserve fabric stock at factory level is not visible to IS team
• Sourcing for fabric is not done for Institutional customers Process:
• Priority for Institutional orders are low
• Information is decentralized leading to a high turnaround time
• Bulk orders from Institutional customers leading to shortage of available capacity
• Slack information flow between brand and factory leading to delayed production Planning:
• Lack of planning and subsequent strategizing for achieving targets Problems with forecasting the sales of this channel
• Manufacturing for orders are done on an ad-hoc basis 5. 4: Process Improvement Plan The proposed solution has been broadly divided into short term actions and long term actions: Short term actions: a. Channel potential
• Dispel value chain image
• Communicate benefits of the channel
• Change accounting standards for brands for catering to IS b. Fabric stock visibility
• Catalogue of reserve stock in factory
• Swatch set, inventory record of current stock made visible to IS team c. Process capability
• Sourcing done on a limited scale by the IS team
• Book order for a limited quantity of core range during trade show Plant capacity set up to cater to Institutional customers exclusively Long term plans:
• Revamp Order Interface
• Integrate sourcing solutions
• Create and maintain a database of mills
• Create an online portal for centralized information storage from the brand, factory and IS team
• Formulate ramp-up strategy
• Target a service level of 100% for orders within 5000
• Process should be capable of handling 5000+ orders with a lead time of 45 days
• Target new segments to increase business volume
• Create a low price point brand, Byford, to cater to demand for price sensitive customers 5. 4. 1: Short term changes: Channel Potential:
• Apprehension of brands regarding profitability and quality of products offered Demand from this channel is an additional demand (basic difference from value channel)
• Quality assurance according to brand standards
• Adhering to predetermined discount slabs (PC:MRP ratio)
• Potential to facilitate fabric stock liquidation (AS has already prepared swatch set) Process Capability:
• NOS stock not always available leading to business loss in Core range
• IS team should form some sourcing capabilities by using the standard mills
• IS team can also book a certain range of core products during trade shows (brands currently identify 5 styles that will sell in IS)
• Separate plant capacity based on past year minimum demand per month for the past year Fabric stock visibility: Swatch set of reserve fabric stock to be made and sent to the IS team
• A basic database of current stock from traditional channel that the brand can offer for IS
• Information clarity between the stake holders for fabric stock to be centralized Key Changes:
• Central repository of information regarding reserve stock from factory and excess fabric stock from all national mills adhering to quality standards
• Repository periodically updated for fabric from current stock (dropped order) that can be offered to Institutional customers
• Agents have an upstream visibility regarding fabric on offer, therefore enabling queries to be addressed on first contact IS team and agent have stock visibility to reply to queries better, shortening the order capture time
• IS team itself explores sourcing options if fabric not present with brand
• Interaction with brand minimized regarding the fabric stock information
• Interactions between contact points in the whole process flow reduced Non-Availability of capacity:
• Plant capacity not allocated to Institutional sales
• Delay in order delivery due to lack of capacity
• Separate line to cater to IS specially during peak season (Aug/Sept)
• Line can be used for traditional channel in case capacity unutilized
• Factory to have the capability to manufacture 7000 units for IS per month 5. 4. 2: Long term plans: Strategic goals: Target a service level of 100% for orders within 5000 units
• Aim to serve 12 very large orders (revenue over Rs. 50,00,000 every fiscal year)
• Service an order with volumes larger than 5000 in 45 days lead time (considering fabric sourcing is required) Expansion:
• Pharmaceutical sector contributes to 90% of the current business
• Decrease dependency on one sector by exploring new avenues
• Actively ask agents to promote business to new customers and provide incentive if a new sector is breached (volume orders) Brand development:
• Byford currently caters to Institutional customers
• Make Byford capable of servicing parallel industries like uniform orders, that are not being serviced by LBRDs Byford can service internal requirement for manufacturing industries that cannot be serviced because of price point issues (accept orders only beyond a certain volume) Key Changes:
• Interface is created to capture the entire information in an accessible format
• Interface provides information about style code, fabric properties, swatch, quantity available, estimated manufacturing capacity and price of product
• Processes typically addressed after an enquiry is expedited to be processed beforehand
• Customer driven ordering system which minimizes the unstructured interaction between the various stakeholders
• Customer has ready information regarding the quantity available, fabric availability and tentative delivery dates Price, fabric and plant capacity issues are dealt with in a structured manner to avoid unnecessary delays n the system
• Information is centralized successfully and the interface can be further utilized by other channels (e. g: a Trade customer wants to order a Core range) 5. 5: Process Control Auditing Measures:
• Brands feel it is not profitable to sell to Institutional channel because of the 67. 3% transfer price between MFL & MGLRCL
• Monthly targets are affected as brands service IS orders
• Separate auditing for sales made through Institutional channels Process Capability:
• Measure of defects in delivery (quantity & quality) for orders accepted
• Measure to be Defects Per Hundred Opportunities
• Service level: the number of accepted enquiries

Process Dashboard: a. Historical:
• Data for the past quarter
• Revenue
• Selling price
• Orders accepted
• Orders served
• Monthly plant utilization b. Exceptions:
• Data outliers in business process
• Largest enquiry by volume
• Largest order accepted
• Longest delay c. Current status:
• Enquiries under process
• Enquiries potentially worth over Rs 10,00,000
• Actual sales vs target sales d. Future:
• Current orders under process
• Utilization of plant capacity by IS
• Scheduled vs expected delivery dates 7. References: Toyota Kata: Managing People for Improvement, Adaptiveness and Superior Results by Mike Rother
• The Toyota Way by Jeffey Liker

Cite this page

Summer Internship Report on Madura Garments. (2016, Dec 10). Retrieved from

Summer Internship Report on Madura Garments
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