NMIT-SUPPLY-CHAIN-MANAGEMENT-Lesson4

Introduction to Supply Chain management(Lesson 4)

Edited By JQuek

Logistics Methodology Aggregation Validation

Objectives for today’s lesson

Suppliers must accurately forecast demand so that they can produce and deliver the right quantities at the right time and at the right cost.

Suppliers must find ways to better match supply and demand to achieve optimal levels of cost, quality and customer service to enable them to compete with other supply chains.

Problems that affect product and delivery will have rippling effect throughout the chain.

The fact…

a group or mass of distinct or varied things , example - persons

What is the meaning of aggregation?

Aggregating Customers

Customers located in close proximity are aggregated using a grid network or clustering techniques. All customers within a single cell or a single cluster are replaced by a single customer located at the centroid of the cell or cluster.

We refer to a cell or a cluster as a customer zone.

Why do we want to Aggregate?

The cost of obtaining and processing data (managing the data is expensive) The form in which data is available (raw data is just a bunch of meaningless numbers) The size of the resulting location model (Without aggregation, the diagram is HUGE) The accuracy of forecast demand (We are unable to correctly estimate)

Impact of Aggregating Customers

The customer zone balances

1. Loss of accuracy due to over aggregation

2. Needless complexity What affects the efficiency of the aggregation?

1. The number of aggregated points, that is the

number of different zones

2. The distribution of customers in each zone.

Recommended Approach

Use at least 300 aggregated points

Make sure each zone has an equal amount of

total demand

Place the aggregated point at the center of the

zone

Testing Customer Aggregation

1 Plant; 1 Product Considering transportation costs only Customer data

◦Original Data had 18,000 5-digit zip code ship-to locations

◦Aggregated Data had 800 3-digit ship-to locations

◦Total demand was the same in both cases

Comparing Output

Total Cost:$5,796,000Total Customers: 18,000

Total Cost:$5,793,000Total Customers: 800

Cost Difference < 0.05%

Explaining the diagram

The aggregated data allows a supplier to actually pin-point 800 customer zones rather than the total 18,000 customers.

The supplier will now off-load the goods to the 800 customer zones

Smaller, cheaper transport companies will now deliver from the 800 zones to the 18,000 customers.

The efficiency of delivery is now more efficient for the main transporter.

Product Grouping

Companies may have hundreds to thousands of individual items in their production line

1. Variations in product models and style2. Same products are packaged in many

sizes Collecting all data and analyzing it is

impractical for so many product groups

A Strategy for Product Aggregation

Place all SKU’s (Stock Keeping Unit) into a source-group◦A source group is a group of SKU’s all sourced

from the same place(s) Within each of the source-groups, aggregate the

SKU’s by similar logistics characteristics◦Weight◦Volume◦Holding Cost

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Within Each Source Group, Aggregate Products by Similar Characteristics

Test Case for Product Aggregation

5 Plants25 Potential Warehouse LocationsDistance-based Service ConstraintsInventory Holding CostsFixed Warehouse CostsProduct Aggregation◦46 Original products◦4 Aggregated products◦Aggregated products were created using weighted averages

Sample Aggregation Test:Product Aggregation

Total Cost:$104,564,000Total Products: 46

Total Cost:$104,599,000Total Products: 4

Cost Difference: 0.03%

The Impact of Increasing the Number of Warehouses

• Improve service level due to reduction of average service time to customers

• Increase inventory costs due to a larger safety stock

• Increase overhead and set-up costs

• Reduce transportation costs in a certain range

Industry Benchmarks:Number of Distribution Centers

Sources: CLM 1999, Herbert W. Davis & Co; LogicTools

Avg.# ofWH 3 14 25

Pharmaceuticals Food Companies Chemicals

- High margin product- Service not important (or easy to ship express)- Inventory expensiverelative to transportation

- Low margin product- Service very important- Outbound transportationexpensive relative to inbound

A Typical Network Design Model

Several products are produced at several plants.

Each plant has a known production capacity.

There is a known demand for each product at each customer zone.

The demand is satisfied by shipping the products via regional distribution centers.

There may be an upper bound on total throughput at each distribution center.

A Typical Location Model

There may be an upper bound on the distance between a distribution center and a market area served by it

A set of potential location sites for the new facilities was identified

Costs:◦Set-up costs◦Transportation cost is proportional to the distance◦Storage and handling costs◦Production/supply costs

Complexity of Network Design Problems

Location problems are, in general, very difficult problems.

The complexity increases with the number of customers, the number of products, the number of potential locations for warehouses, and the number of warehouses located.

Solution Techniques

Mathematical optimization techniques:

1. Heuristics: find “good” solutions, not necessarily

optimal2. Exact algorithms: find optimal solutions

Simulation models: provide a mechanism to evaluate specified design alternatives created by the designer.

Heuristic refers to experience-based techniques for problem solving, learning, and discovery that give a solution which is not guaranteed to be optimal.

Where the exhaustive search is impractical, heuristic methods are used to speed up the process of finding a satisfactory solution via mental shortcuts to ease the cognitive load of making a decision.

Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, stereotyping, or common sense.

What is the meaning of heuristics?

Simulation modeling is the process of creating and analyzing a digital prototype of a physical model to predict its performance in the real world.

What is a simulation modeling?