Difference between revisions of "ANLY482 AY2017-18 T1 Group2 Project EZLin Project Overview"
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2. To determine the most cost-efficient budget plan based on the criteria <br/> | 2. To determine the most cost-efficient budget plan based on the criteria <br/> | ||
3. To identify the clustering factors and determine their effects on each other <br/> | 3. To identify the clustering factors and determine their effects on each other <br/> | ||
| − | 4. To build a dashboard reporting system which helps with cleaning the data and doing exploration in the future <br/> | + | 4. To build a dashboard reporting system which helps with cleaning the data and doing data exploration in the future <br/> |
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Revision as of 15:47, 27 August 2017
In any company that delivers a physical product or solution, supply chain has always been a huge challenge in the operations of the organisation. There are many established companies in the market that operate the supply chain in silos and treat it as another cost center without clearly identifying what constitutes the cost in the entire supply chain ecosystem. Our motivation therefore is to not only determine the various costs that are inherent in the client’s supply chain eco-system but to also determine what are the possible indicators that will allow our client to better predict its cost.
Supply chain is not merely about transporting goods from one point to another. It begins from sourcing of the raw ingredients to manufacturing it in the plant and transporting it around, leading up to the final distribution with many intermediate contact points. With our background in Operations Management and Information Systems, we are keen to understand what are the costs involved in each stage and contact points of this supply chain through the huge amount of data available in the system. However, our motivation goes beyond just identifying the costs, as we believe cost is not just incurred from within an organisation. Many external factors such as the volatility of commodities has a significant impact on the overall cost incurred for an organisation such as our client, that relies heavily on raw materials. Therefore, we are excited to explore how the effect of external factors, coupled with internal factors, can possibly allow the company to have a better chance at predicting its cost and ascertaining its profitability.
All in all, we are keen to work on this project as it allows us to apply what we have learned to a real world business problem. As daunting as this is, it will be interesting to discover whether our analysis and recommendation has a positive effect on an actual business challenge.
The aim of our project is to help XXX's supply chain department, to identify any analytics trends and patterns in their current budget spending when they purchase raw materials of baby oil. We will identify any descriptive analytics patterns which helps to save on their budget. At the same time, based on the patterns, predictive analytics will also be conducted in this project. XXX will be able to foresee any inflation in the price of the raw materials from this project.
The objectives of this project are:
1. To summarise the information of the raw materials prices based on different criteria such as volume, flavour, percentage of ingredient and etc
2. To determine the most cost-efficient budget plan based on the criteria
3. To identify the clustering factors and determine their effects on each other
4. To build a dashboard reporting system which helps with cleaning the data and doing data exploration in the future
1. Deere & Company (brand name John Deere) is well known for the manufacture and supply of machinery used in agriculture, construction, and forestry, as well as diesel engines and lawn care equipment. Deere and company has a complex product range, which includes a mix of heavy machinery for the consumer market and industrial equipment which is made to order. Retail activity is extremely seasonal, with the majority of sales made between March and July. The company undertook a supply chain network redesign program, resulting in the commissioning of intermediate “merge centers” and optimization of cross-dock terminal locations. Deere & Company also began consolidating shipments and using break-bulk terminals during the seasonal peak. The company also increased its use of third party logistics providers and effectively created a network which could be tactically optimized at any given point in time. Deere & Company’s supply chain cost management achievements included inventory reduction of $1 billion, a significant reduction in customer delivery lead times (from ten days to five or less) and annual transportation cost savings of around 5%.
2. During 2007 and 2008, Starbucks leadership began to have serious doubts about the company’s ability to supply its 16,700 outlets. As in most commercial sectors at that time, sales were falling. At the same time though, supply chain costs rose by more than $75 million. Their challenges include: Fewer than 50% of outlet deliveries were arriving on time. A number of poor outsourcing decisions had led to excessive 3PL expenses. The supply chain had, (like those of many global organizations) evolved, rather than grown by design, and had hence become unnecessarily complex. To organize its supply chain better, Starbucks divided all its supply chain functions into four key groups, known as “plan” “make” and “deliver”. It also opened a new production facility, bringing the total number of U.S. plants to four. Next, the company set about terminating partnerships with all but its most effective 3PLs. The remaining partners were then managed via a weekly scorecard system, which was aligned with renewed service level agreements.By the time Starbucks’ supply chain transformation program was completed, the company had made savings of more than $500 million over the course of 2009 and 2010.
