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Sheet1Sales Consultant IDOfficeRegionTax TypeTotal ContractsTotal .docx
- 1. Sheet1Sales Consultant IDOfficeRegionTax TypeTotal ContractsTotal SalesTotal Cancellations10/1/1435353356MANHATTANNORTHW210$30, 291.00110/1/1466464667ATLANTASOUTHW24$39,999.000Cri teriaWeight10/3/1457575758MIAMIFL/HI109911$92,829.001P aper identifies and explains sales consultants that indicate progression towards noncompliance What about the specific points for outliers, not meeting max/min in sales, too many cancellations, etc? - 20 15/3510/3/1475265980MANHATTANNORTHW24$44,255.002 Classified, grouped, and filtered data in spreadsheet I don't see your actuall classification strategy - 1025/3510/5/1483748200EL PASOSOUTH10990$0.000Highlighted sales consultants in spreadsheet that are noncompliant2010/10/1426354410MIAMIFL/HI10995$20,100.0 01Paper meets minimum page requirement510/11/1433407197ArkansasSOUTHWEST10990$7, 881.000Paper is APA formatted with references and citations without spelling or grammatical errors510/12/1440278386ArkansasSOUTHWEST10991$10,000. 000Total70/100%10/13/1441107218Tri- StateSOUTHWEST109911$83,641.00510/14/1426150025MANH ATTANNORTHW213$0.001310/20/1426354410MIAMIFL/HI10 990$0.00010/20/1426354410MIAMIFL/HI10997$44,242.00010/ 20/1426356778MIAMIFL/HIW21$555.00010/20/1426457518M ANHATTANNORTHW29$80,000.00010/20/1426520168MANH ATTANNORTHW210$45,000.00010/20/1426526109MANHATT ANNORTHW225$54,535.00010/25/1412658262MANHATTAN NORTHW29$24,222.00010/25/1426161204MANHATTANNOR THW24$14,344.00010/25/1426531823CHICAGONORTHW21$6 ,566.00010/26/1433011618LOUISVILLESOUTH10991$250.000 10/26/1433255099MANHATTANNORTHW216$50,000.00110/2 8/1433233704BRONXNORTH10990$321.00010/28/1443207148
- 2. ArkansasSOUTHWEST10993$600.00010/30/1426325752MANH ATTANNORTHW213$72,990.00010/30/1426621106NEW ORLEANSSOUTHW27$35,000.00010/30/1426621106NEW ORLEANSSOUTHW210$87,382.00110/31/1433135393LOUISV ILLESOUTH10999$21,222.000Classify and Analyze Data Outliers are data points that significantly differ from the other points in a sample. These data set alert statisticians that there exist experimental abnormalities or massive errors in the type of measurement taken. When such abnormalities are noted, it might be relevant to omit outliers from the data set (Gupta, Gao, Aggarwal, and Han, 2014). An examination of the fence points and data shows that these points exceed the upper inner fence as well as the lower inner fence hence standing out as mild and extreme outliers in my data set. Equally, the outliers are sales consultants that indicate a trend towards non-compliance are from the following regions namely: Arkansas 7881, El Paso 0, Manhattan and Miami 0, Miami 555, Louisville250, Chicago 6566, Bronx 321, Miami $92,829, Manhattan 80,000, New Orleans 87,382, and Arkansas 600. When I expressed these data in a graph in excel outliers were far away from the other values. These values scared far away from the other data and therefore could not be used as the other data in interpretation. Even though the majority of the data set do not form a straight line, the above-identified outliers cannot in any way play a role in constructing a line (Hodge and Austin, 2004). In summary, the outliers in the data set must be investigated because they often contain valuable information about the entire research process, data, or the process under investigation. Finding out the reason why such abnormalities exist is necessary before axing out outliers. They are of course lousy data points especially in a graph but are appropriate in speaking about the process or the techniques used. References
- 3. Gupta, M., Gao, J., Aggarwal, C. C., & Han, J. (2014). Outlier detection for temporal data: A survey. IEEE Transactions on Knowledge and Data Engineering, 26(9), 2250-2267. Hodge, V., & Austin, J. (2004). A survey of outlier detection methodologies. Artificial intelligence review, 22(2), 85-126. Total Sales 30291 39999 92829 44255 0 20100 7881 10000 83641 0 0 44242 555 80000 45000 54535 24222 14344 6566 250 50000 321 600 72990 35000 87382 21222 10 4 11 4 0 5 0 1 11 13 0 7 1 9 10 25 9 4 1 1 16 0 3 13 7 10 9 Total Sales Tax Contract Sheet2 Sheet3 Date Date ANALYSIS OF WEGMANS FOOD MARKETS 9 Operational Issues and Actions Location Management Wegmans currently operates over one hundred stores located mainly in the north-eastern part of the United States (Stevenson, 2018 p.33). Many of Wegman stores are massive, one hundred thousand square feet building that contains several unique departments for the enjoyment of the shopper (Stevenson, 2018 p.33). However, grocery stores are a competitive market and
- 4. with inflation rates surging the number of groceries bought are reduced. Competitors such as Costco and Sams Club gain the loyalty of big box shoppers and have locations all over the country. Meanwhile, Wegmans currently does not have very diverse locations, and a limited number of stores. If the company plans to remain as one of the most successful grocery stores they may want to think about where to expand their brand. With the economy continuing to improve, now is the time for Wegmans to invest in new diverse locations to introduce the Wegmans brand to new customers. Forecasting Wegmans current forecasting method is the Retek model (“Wegmans Selects, 2003). This program allows for the company to successfully forecast consumer demand and seasonal demand. However, each manager of each department in a Wegman’s store is held accountable for maintaining inventory to prevent loss, and as a result the managers need to understand what drives demand for products and why that demand may change. Variables, such as seasonal changes and weather predictions should be accounted for when forecasting demand for products (Stevenson, 2018 p.78) . Managers should study past sales records in order to make sure that they are not over or under stocking. Managers should also familiarize themselves with strategies for “product or service lifecycles” or PLM (Stevenson, 2018 p.151). While relying on a forecasting model, such as the Retek model, is beneficial to a company models may not always be completely accurate and obtaining a deeper understanding of forecasting trends in demand is necessary for continued success. Supply Chain Management As Wegman’s seeks to expand its footprint on the eastern seaboard, supply chain considerations become of paramount importance. Scalability is a concern as they increase the amount of locations they have. What is the capacity of current
- 5. warehouses? Is there room for further efficiency to support more locations? Are there sufficient local produce providers to meet the demand? Scalability is important because if the warehouse is near capacity on current facilities, expansion will be necessary to service more locations and adding those additional facilities command considerable outlays of financial assets. Scalability rarely keeps pace with growth, and frequently organizations are in a position where either capacity is stretched thin or there is excess capacity. In one situation, current operations are risked by lack of timely supply deliveries, and on the other extreme lack of return on assets due to excess capacity. Wegman’s already demonstrates a high degree of supply chain efficiency since they overturn their fresh inventory 100 times a year which is much higher than the 20 times of the average competitor (Teti, 2015). Wegman’s also adheres to a vertically integrated supply chain, where the corporation owns the warehouses, handles its own distribution, and even owns some of the suppliers (Teti, 2015). While this is beneficial to controlling costs, and minimizing supplier risk, it decreases the corporation’s ability to scale up their operations since they place a premium on the vertical integration. Wegman’s will need to increase the number of warehouses and distribution centers in a way that supports increased operations, without significantly harming their high efficiency. Another consideration is dual-sourcing where Wegman’s could develop relationships with suppliers so that they would have a low cost, long lead time supplier and a higher cost, low lead time supplier. This can allow the corporation to drive down costs by supplying the majority of their products at a lower cost, but still having the flexibility to obtain crucial products on a short term if needed (Tongarlak, Lee, & Ata, 2017). Distribution As Wegman’s seeks to increase the amount of grocery stores they operate, distribution strategies will become increasingly important. Wegman’s has focused on targeting affluent
- 6. suburban communities in six states, and as they spread out distance becomes of greater concern. Distance is a prime factor in the cost of transporting refrigerated goods, so distribution networks will need to be efficient and cost effective (Teti, 2015). Beyond obtaining more warehouses and expanding number of suppliers there are things that can be done to improve the performance of distribution centers. Wegman’s has already integrated recent technological innovations to improve performance including the use of RFID tags (Stevenson, 2018, p. 676), and global data synchronization with suppliers which improved costs for supplies and labor by one million dollars, and increased productivity by 7% (Teti, 2015). Wegman’s already practices cross-docking and cross-distribution, by which incoming shipments are routed on the dock directly to outgoing traffic to decrease “picking” activities, and decreasing task times (Stevenson, 2018, p. 675). An additional distribution strategy that can be further employed is a “picking” strategy improved by statistical data through studying warehouse flows (de Koster, Le-Duc, & Roodbergen, 2007). If Wegman’s were to align the product storage in their warehouses in order to place the items more likely to be loaded on an outbound truck closer to the docks and move less common items further way from the dock this would greatly improve the loading times and therefore allow them to move more trucks in and out of the warehouses than would otherwise be possible. Also, if they could automate some of the picking with robotics they could lower labor costs, and improve efficiency. Wegman’s needs to continue to integrate the latest technologies and statistical supply chain management methods to maintain their competitive edge. The key to success in the technological age is not size, but agility (Woldt, 2015). Resolution Technique, Application, & Evaluation Appendix