"The Academy of Sales and RetailManagement (ASRM) has been privileged to be nurtured and incubated by Tata Teleservices Ltd. This has allowed us to build a strong foundation & pillars upon which we will grow. The first and most important pillar is trainer certification. The processes of certifications are built around a fundamental premise of maximizing participants learning. We have instituted three separate certifications, one on industry knowledge, the other on facilitation skills and the third on behavioral skills training. All our certifications are based on well respected global standards such as ASTD (American Standard for Trainer Development).
Retailing, one of the largest sectors in the global economy, is going through a transition phase not only in India but the world over. Retailmanagement system targets small and midsize retailers seeking to automate their stores as well as impact on the growth of the economy of India which shows the Indian Retail industry is a US$ 270 billion industry and is growing at over 13% per annum, Indian retailing industry has also seen phenomenal growth in the last six years (2001-2007). RNCOS’ “India Retail Sector Analysis (2006-2007)” report helps clients to analyze the opportunities and factors critical to the success of retail industry in India, which is a significant contributor to the overall growth of economic activity in India. IMRG reported that the top six cities of India, Mumbai, Delhi, Chennai, Kolkata, Bangalore and Hyderabad are the center for booming economy representing 6% of the population yet contributing 14% of the GDP and by 2010, organized retail is projected to reach US$ 23 billion. A survey conducted by KPMG in 2005 shows that Indian retail industry is on top in comparison to Japan, China, India, Thailand and Singapore. Other analysis done by KPMG shows training is a key for Indian retailers, availability of manpower and managerial skill sets also play a key role for retailmanagement. Analysis by retailyatra.com shows current and projected mall space which is 22 million sq.ft now and will be 90 million sq. ft. Retailmanagement not only impact on economic growth but there is a technology impact also which help the organized retailer score over the unorganized players, giving both cost and service advantages.
“I joined the Department in 1992 and led the RetailManagement Development Programme, which provided postgraduate courses for over 700 managers from major UK retailers, for 10 years. This provided valuable insights into the link between theory and practice. My current retail interests are in two broad areas. The first is how organisations operate in the US retail marketplace which is the world’s largest and most diverse. This has involved interviews and visits to Wal-Mart, Macy’s, and more specialist retailers in the convenience, pet food and ‘thrift-shop’ sectors. My second is how the rapid increase of smartphones has radically altered consumer buying behaviour which presents both opportunities and challenges for retailers.”
Are you comfortable about the idea of working in co-operation with Pacific RetailManagement, and do you accept that a number of disciplines exist in a franchise system, in particular working under the direction and guidance of the Franchisor?
This qualification provides the skills and knowledge for an individual to be competent in the first line management skills of those working in the retail and/or wholesale industries. It applies to those who are managing a small retail outlet, a section or department within a larger retail store, a small wholesale outlet, or a section or department within a larger wholesale business.
Students are not required to have prerequisites for this course. The skill set necessary to conduct a retail plan ranges across the spectrum of business and other disciplines. Student will depend on each other’s skills in areas to learn from their peers as well as from the instructor. The main prerequisite for this course is to have an interest in Entrepreneurship and/or Retailing.
Indian retailing industry has seen phenomenal growth in the last five years (2001-2006). Organized retailing has finally emerged from the shadows of unorganized retailing and is contributing significantly to the growth of Indian retail sector. RNCOS 9 “India Retail Sector Analysis (2006-2007)” report helps clients to analyze the opportunities and factors critical to the success of retail industry in India.
MODULE 4 - SUPPORT INSTITUTIONS AND MANAGEMENT OF SMALL BUSINESS Unit 13: Role of Support Institutions and Management of Small Business : Director ofIndustries; DIC; SIDO; SIDBI; Small Industries Development Corporation (SIDC); SISI; NSIC; NISBUED; State Financial Corporation SFC; Marketing Management; Production Management; Finance Management; Human Resource Management; Export Marketing;
Trade Area Analysis – Size and shape of trading areas – Defining the trade area – Reilly’s law Huff’s Probability Model – Index of Retail Saturation Theory – Site Evaluation and Selection – Estimating the potential – Selecting the Specific Site. Objectives of a good store design – Creating a Store image – Creating a buying environment – Store Exteriors – Store Interiors – Store Layout Design – Types Grid – Racetrack – Free Form – Feature areas – Space planning – Location of department – Location of merchandise within departments : Use of Plano grams. Unit III
Scholarships awarded to full-time students who are juniors or seniors, majoring in retailing. Recipient will have successfully completed a retailmanagement course with preference given for on scholarship to a minority. Recipient must have a 2.8 minimum GPA with an ongoing record of excellence in the college or a single outstanding achievement within the major and future aspirations in pursuing a retailmanagement career. Three scholarships awarded each year. One scholarship of the three must be awarded to an underserved population.; Renewable: No; Major: Retailing; Minimum GPA: Minimum 2.8; Student Level: Full-time junior or senior; Financial need: Eligibility for scholarship is not based on financial need. The online scholarship application will be available on the College of HRSM Homepage in January.
Our paper yields some important insights for retailmanagement. By accounting for non- stationary demand in inventory management, retailers can reduce inventory holding, handling and stock-out cost substantially. Cost savings are higher for fast-moving items with high demand variability across review periods and low case pack size. Our numerical analysis with real life data indicates potential cost savings that are considerable for the retailing industry with its tight margins and rigorous focus on cost-efficiency (a reduction of up to 66.27% in optimality gaps). Large cost savings can be already achieved with a simple distinction between weekday and weekend sales, provided that the weekend is defined appropriately for each item (the optimality gap goes down to an average of 1.60%). Doing so improves the return on investment in automated store ordering systems that are equipped with the capabilities of accounting for non-stationary demand.
Page | 34 It is also important to make sure the employees keep working with the new procedures. This can be done by analyzing reports and by supervising employees. Due to the new procedures the workload of RetailManagement is more efficient, which results in time for analyzing the reports. The outcome of these analyses can be used for targeted guiding of the employees. Finally the procedure has to be evaluated and the change agent has to make sure the procedure remains up-to-date. Therefore the transformation group will remain to have a meeting weekly. In this meeting not only the procedures are discussed, but, due to this research, we also check analyses each week. Once a week a sample of products is counted for stock and the differences in stock are discussed in the weekly meeting. In that way we can study where differences come from, maybe products are incorrect in the system, employees do not follow procedures, or maybe there is another reason. To search for reasons, we also analyze negative stocks weekly, and we discuss how many and which products are damaged that week. By keeping analyzing these reports, we can say something about the inventory management, we can improve it and we can lead the team more targeted.
Successfully managing a worldwide network of contact centers requires coordinating thousands of agents with multiple skill sets to ensure calls are handled quickly, efficiently and expertly. With 22,000 contact center agents at 214 sites in 25 countries, optimizing agent work schedules was crucial to achieving that goal. EDS implemented its own forecasting and staff-planning applications, as well as the Blue Pumpkin work force management suite, which EDS reconfigured to operate throughout the enterprise. The solution’s powerful call volume forecasting capabilities let management predict call patterns, staffing needs and generate centralized schedules. Reporting tools analyze forecasting, planning accuracy and schedule adherence. Today, all contact centers share centralized processes, training and procedures that ensure consistency and excellence across the globe.
Talluri and van Ryzin (2004) use sales transaction data (records of purchase time and product choice for each customer) to estimate demand in the context of airline revenue management. If customer arrivals, purchases and no-purchase outcomes are completely observed, then one can estimate the demand parameters using maximum likelihood methods. However, in practice only purchases are observed, and hence it is not possible to distinguish between a period with no arrivals, and a period with arrivals but no purchases. To overcome this problem Talluri and van Ryzin use the Expectation-Maximization (EM) algorithm of Dempster et al. (1977) to correct for the missing data. This method starts with arbitrary initial estimates of the demand parameters and uses Bayes rule to estimate the missing data. These esti- mates are now used to compute the conditional expected value of the likelihood (the expectation step), and the resulting expected log-likelihood function is maximized to generate new estimates for the demand parameters (the maximization step). This procedure is repeated until it converges. Anupindi et al. (1998) use a similar approach to estimate demand and substitution probabilities for two products using sales transaction data from vending machines. Vulcano et al. (2009) use the EM algorithm to develop a procedure to estimate demand from sales transaction data, when the underlying substitution is governed by a MNL model.
ARC and TEL transactions share some risks with other ACH debit transactions, but differ in risks that are driven by the location at which the payments are initiated and the relation- ships among the parties to each transaction. 31 For ARC, retail lockbox processors convert checks sent by consumers to billers. Lockbox staff use high-speed equipment to capture coded information from the remittance slips and checks. The lockbox business is highly concentrated, mature, and controlled. In many cases, these processors operate as subcontractors to the originating banks, supporting the banks’ cash management product offerings. In contrast, TEL transactions rely on customer input of account information via telephone, a context in which the data and customer’s identity cannot easily be verified.
In , reinforcement learning (RL) techniques have been used to determine dynamic prices in an electronic monopolistic retail market. The market has been considered to consist of two natural segments of customers, captives and shoppers. Under certain logical assumptions about the arrival process of customers, inventory replenishment policy, and replenishment lead time distribution, the system becomes a Markov decision process thus enabling the use of a wide spectrum of learning algorithms. This model and methodology can be used to compute optimal reorder quantity and optimal reorder point for the inventory policy followed by the seller and to compute the optimal volume discounts to be offered to the shoppers.
Empirical research has provided clear evidence of the existence of inventory record inaccuracy in a number of contexts, including government agencies (Schrady 1970 and Rinehart 1960) and utilities (Redman 1995). In the retail context that is our focus, Gentry (2005) reports a discrepancy between recorded and actual inventory amounting to $142 million, or the equivalent of 21,000 ocean containers, at The Limited, a well-known apparel retailer. DeHoratius and Raman (2004) measure inventory record inaccuracy at Gamma. Ton and Raman (2005) examine the problem of misplaced products at Borders. Both papers identify several drivers of such execution problems and discuss their impact on retail product availability.
collected). According to our metric, less than 2% of the stores showed an adherence lower than 80%, with an aver- age and median across stores both equal to 89%. We ﬁnd these results to be quite compelling. In particular, they jus- tify that the inventory display policy based on major sizes can be used as a representation of store execution behavior. We next describe a stochastic model developed to answer the following question: Given the dependency between inventory and sales of different sizes introduced by the store inventory management policy based on major sizes, how many sales of each article should be expected between successive replenishments when starting from a given ini- tial proﬁle of inventory across sizes? As part of this ﬁrst modeling effort, we initially assume away the dependencies between inventory levels of different articles. That assump- tion is clearly not tenable in all cases because there may in practice be signiﬁcant demand substitution (e.g., gar- ments available in different colors but otherwise identi- cal) and demand complementarity (e.g., assorted vest and trousers sold separately) across articles. In §E of the online appendix, however, we discuss how our model may be extended to the case of products offered in multiple colors. 3.1.2. Model Description. Consider an article offered in a set of sizes = + ∪ − , where + denotes the
desirable to have a means whereby costs and performance of that pipeline flow can be assessed. One of the main reasons why the adoption of an integrated ap- proach to logistics and distribution management has proved so difficult for many companies is the lack of appropriate cost information. Conventional accounting systems group costs into broad, aggregated categories which do not then allow the more detailed analysis necessary to identify the true costs of servicing customers buying particular product mixes. Without the facility to analyze aggregated cost data, it becomes impossible to reveal the potential for cost trade-offs that may exist within the logistics system. Generally the effects of trade-offs are assessed in two ways: from the point of view of their impact on total costs and their impact on sales revenue. However, without an adequate logistics-oriented cost account- ing system it is extremely difficult to identify the extent to which a particular trade-off is cost-beneficial. The principles of logistic costing will be discussed in the next paragraph.
To show correct stock on hand both in the store and HO databases all stock related posting must be mirrored between the databases. This new functionality of the InStore Mgt. will do that for Transfer, Purchase and Purchase Returns Orders. Stock requests are always transferred into either transfer or purchase orders which includes them in the mirroring functionality. Left is all other stock posting, like negative or positive adjustment. To mirror those transactions, the system uses the already present Retail Inter Company Transfer (ICT) functionality. This requires some minor changes to the Retail ICT module.