Concerning Barilla?s supply chain that shows in the Figure 1, Barilla?s CDCs and the production factory locate at the locations at the positions with the most variability in the supply chain. The distributors such as GD, DO and BD receives orders from the supermarkets and place orders to Barilla CDCs who then pass the productions orders to the factory (pull supply of products). GD, DO and BD merely used simple periodic review inventory systems to forecast the supermarket?s demand, which may inaccurately decide the order quantities. Having limited information for customers? demand data, they need to base on orders placed by the supermarkets to perform their forecast which fluctuated widely indeed---causing the ?bullwhip effect?. The same effect …show more content…
Such fluctuating demand add great burden on its manufacturing and logistics operation and forced it to have a huge inventory for the products that seemed to have more demand. Moreover, the production line of Barilla can?t afford the frequent changes in terms of order quantities due to the long and redundant setup process. It comes out that once the unreliable forecast exists, Barilla will wither need to accumulate huge inventory or lose the consumer fill rate which both of them are not favorable. Besides, with such extreme demand, the consumers will easily face the problem of stockout because of the low fill rate of Barilla and the ?Big Order? policy which makes GD/DO stockouts by ?purchasing the wrong products a lot? but ?having no more extra area or money to purchase the correct ones to meet the demand?. The inefficiencies in Barilla?s distribution system are mainly caused by huge fluctuations in demand and inaccurate forecast. The reasons for making the distributor?s order pattern look like this?increase in variability in its supply chain -- are illustrated below: LONG LEAD TIMES: it takes approximately 8-14 days for the receipt of items at the distributors end from the date placing the order and the average lead time is 10 days. Such long lead time contributes to variability and reduced service levels. LACK OF CENTRALIZED DATA: it does not keep a centralized …show more content…
could be eliminated and so as to reduce the demand fluctuations. Hence, the distributors could release more inventories space and cost and they will be more competitive to react to the variability like after season stock, new products etc. Improvement in customer fill rate for both Barilla and the distributors: the system puts emphasis on quick response. Since Barilla controls the inventory data and delivery pattern, the production and deliveries are then easier to be scheduled by the distributors to satisfy the consumers? needs. Therefore, with lowered inventory level, the flexibility and reaction speed from the distributors have been enhanced and both the customer fill rate and stockout rate could be improved as well. With less hurry orders interruption, both distribution and manufacturing costs could be reduced: Barilla has long changeover time to setup another product as mentioned in the case. The less disturbance, the more cost-efficient in the whole supply chain process. But it is only applicable for the bottleneck machines and it is true for the distribution cost too. With less fluctuation caused from unknown situations in the past, a better delivery schedule could be achieved by using integrated data from the
HMS needs to improve their cafeteria. this is because HMS has a serving size same as a first grader 's lunch, and needs more food options in the cafeteria plus food quality. Hms needs a better lunch for the kids and staff. Wouldn 't be nice for the kids to know they can eat some good tasty HMS Food instead of prison food?
If we supposed that the service level agreement states that the system would not be offline or unavailable more than 45000 seconds a month then the goal would be to stay away from exciding the stated time. In the data from the years 2009-2017 we can see that the average total downtown is 44151.24 and we can determine that for the most part we are keeping with the goal of not exciding the 45000 mark. In the histogram, we can also see that there was also a high number of occurrences were the system was offline or unavailable for more than 45000.
Month # 1 2 3 4 5 6 Total Forecast demand 600 750 1000 850 750 700 4560 Planned Production 771 771 771 771 771 771 4626 Planned inventory (50) 221 242 13 -66 -45
In 2011, there was a tsunami in Japan and this natural disaster can lead to instabilities in the cost of raw materials. And this will affect the profit. Additionally, these circumstances can also affect Target’s loss of inventory and it can lead to merchandise stock
Food is required in order to live as well as maintain a healthy lifestyle. Potassium, fiber, fat, calories, sodium, along with a bunch of vitamins are required for human body. Calories give us vitality to move around and do our day to day work. From past food industry in United States has grown so much.
Employees’ output is subpar and does not conform to the expected or stipulated levels. This has adverse effects on downstream automakers because they must contend with delays in the supply of side mirrors. It also results in missed deadlines, which erodes customers’ confidence in the organization. Sluggishness among employees also results in a general rise in overheads (Beer & Collins, 2008). For example, the organization must airlift completed parts to customers to shorten delivery times in the face of production delays.
This will have negative multiplier effect downstream supply chain. The implication of this is that, there will be a delay in Bose’s deliveries to its customers resulting in possible loss of customers and profit. To prevent this, Bose must have a strategic alliance with supplier. That ensures quality delivery of
Another external risk is a lost of a supply chain which is result in late or missed deliveries of inventory. A manufacturer of a product may discontinue making a popular item or cease business operations all together. Target can monitor external market conditions of its manufacturers however they cannot control their cash flows or business operations. Target should analyze and identify the potential consequences to potential risk situations (Popescu, Gherghinescu, & Ionete,
10. Forecast the demand for Woody’s products, throughout the project’s life. 11. Ensure that the current production activities are not hampered, while the project activities are carried out. d.
Fine Tuning the forecast The method used to forecast the expected sales lacks the input of external data like market condition (recession, boom etc), competitors, changing preferences, change in fashion, demographics etc. Only the internally available data has been used to estimate the demand for next period. The adjustments in the demand forecast can be made according to the following to reduce the chances of stock outs or over stocking: Market Condition:
The Value Chain 4 4. Operations Strategy Implications (Store level) 5 5. Inventory Management and Demand Forecasting 9 6. Supply Chain Management 9 7. Quality Management 11 8.
Kraft Heinz Case Study Executive Summary Problem Statement The focal problem that Kraft Heinz Company (KHC) faces is the decrease in demand of packaged-foods, while trying to increase revenue. Analysis This analysis studies Kraft Heinz Company’s strategy, competitive position in the market, problems being faced, and the company’s financials.
In case, the demand fluctuates suddenly we adjust the supply by transporting our excess inventory or take some inventory from other distribution centres where sales are comparatively less. Tesla faces a rush order situation mostly in around festival time. To decrease the lead time, transportation costs and the excess inventory company have decided to invest in efficient and cost effective warehouses.
Exercise 3 Introduction Push and pull are strategic supply chain decisions can that are as a results of the impacts of operational, product and demand related variables (Wanker and Zinn, 2004). The push strategy moves products based on planning or forecasting whereas the pull strategy moves products as a results of real demand (Ballou, 1992). Thus in a push system, the products are pushed through the supply chain channel right from production to the retailer. The manufacturer builds its production based on historical ordering patterns and forecasting. Due to this it takes a longer time for this system to respond to changes in demand which results in overstocking, bottlenecks and bullwhip effect in the system.
The health food drinks market is highly competitive with various heavy players like GSK, Cadbury, Nestle, Heinz etc. The health food drinks market is divided into white beverages and brown beverages. Horlicks with 36.2 % market share leads 5500 crore health food drinks market. Bournvita is leader is brown beverage category followed by Boost. Nestle Milo a relative new entrant to the market was launched in India in 1996.