improving after market supply chain a top-down approach

7/29/2019 Improving After Market Supply Chain a Top-Down Approach

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Improving After Market Supply Chain: A Top-Down Approach

A Case Analysis from Automotive Industry

Deepak Bartwal*, Abhishek Skariah*, Sachin Juyal*, Ashok K. Pundir**

* Final Year Student, Post Graduate Diploma in Industrial Engineering, NITIE, Mumbai

** Professor (Operations Management), NITIE, Mumbai

1. Introduction:

No matter how big an organization is, more smart people are going to work outside itswalls than inside.

Hamm, Steve. Radical Collaboration, Business Week

Supply chain does not end up with delivering the products to the customer, but the new

kind of activities start even after the sale of product. Customer buys the product discovering out

commitments and assurance about the life and quality of the product. But what if our

commitments do not meet the reality? This is more crucial in Automotive, White goods,

Computer business etc. The support provided by the manufacturer after the sales of the product

to the customer is known as After-market activities.

Aftermarket support refers to activities associated with products (e.g. Service parts) and

services (e.g. engine overhauls) after the initial sale of a product. We can say that the After-

Sales services for manufactured goods encompass the set of activities taking place after

the purchase of the product, devoted to supporting customers in the usage and disposal

of goods.

There are many differences in the working principles of Manufacturing Supply chain and

After-Market Supply chain. Cohen et al. (2006) have made a summary of these differences.

Table: Difference between Manufacturing Supply Chain and After- Market Supply Chain

Manufacturing Supply

Chain

After-Market Service

Supply Chain

Nature of Demand Predictable, can be forecast Unpredictable, Sporadic

Required Response Standardized, can be Scheduled As soon as possible

Product Portfolio Largely Homogeneous Always Heterogeneous


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Inventory Management Aim Maximize Velocity of resources Pre-Position Resources

Performance Metric Fill Rate Product Availability

Inventory Turns Generally more than 6 a year One to four a year

2. Potential of After Market Supply Chain

Automotive, White-goods manufacturer or Computer manufacturer always look for better

customer satisfaction and good profit share. Although, After-market does not provide great

revenue base but it is great contributor of profit in the balance sheet. A study shows that After

Market yields up to 50% profit for the OEM and Supplier where as the revenue contribution is up

to only 5 %. This simply reflects the huge potential of after-market support.

Figure

1: After Market Profitability

For some industries, the initial sale of a product is just the beginning of a product's ability

to generate revenue. In fact, revenue and profit opportunities may be greater for

aftermarket support (e.g. parts and service) than for the initial sale of the product.


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3. Lean Vs Agile: Where are the pain Points

Service Supply Chain comprises of various activities. It starts since the sale of the

products until it ends. If we see the whole Service function, we can classify the all service supply

chain activities in these two major categories:

Figure 2: Activities classification for After-Sales Service

We can see the wide gap in achieving our goals. Henceforth, we have to do trade-off between

two policies to frame the After Market Supply Chain.

Before making After-Market Supply chain more efficient and Lean, we need to have look

into the characteristics of Lean and Agile Supply Chain. If we see the Agile and Lean Supply

Chain, we find that:

Attributes Lean Supply Chain Agile Supply Chain

Products Functional Innovative

Demand Predictable Volatile (Unpredictable)

Product Life Cycle Long Short

Product Variety Low High

Customer Drivers Cost Availability

Profit Margin 5%-15% 20%-60%

Average Forecast Error 5%-10% 30%-50%

It simply shows that the After Market Supply Chain is Agile Typeof Supply Chain. Hence to

solve the pain points in the supply chain, we need to look into the all processes. But any supply


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chain can neither be complete Lean nor Agile. There will be an optimum mix of Lean and

Agile. What we need to do is just to find the Decoupling Point.

3.1 Decoupling Point:

This point differentiates the Lean Activities and Agile Activities. As we know that in

after-market supply chain needs the agility in the front areas, hence the later part always would

be Agile. But the back-end activities and after-replacement activities can be Lean. This is how

we can improve the supply chain by reducing the waste and saving the total cost.

4. Making Process Lean: Improving the Process

The Parameter Diagram (P-Diagram) takes the inputs from a system/ customer and relates

those inputs to desired outputs of a design that the engineer is creating also considering non-

controllable outside influences. The P-Diagram is a useful tool in brainstorming and

documenting. It includes:

Signal Factor(s)

Response Variable or Ideal Function

Control Factors

Noise Factors Error States (or the failure modes)

Signal Factor (inputs) pass through the design of the product and is output into

measured Response Variable (also called the Ideal Function). Signal Factor is transformed via

the Control Factors to convert the input to the desired output.

Control Factors are typically elements such as design, materials and processes that the

operator has 'control' over. Error States are the failure modes or effects of failure as defined by

an end user when using the product. Noise Factors are things that can influence the design but

are not under the control of the engineer, such as environmental factors, customer usage,

interfaces with other systems, degradation over time, piece-to-piece variation, among others.

System Response Variables

Error States

Control Factor

Signal Factors

Noise Factor


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4.1 Forward Planning: Distribution Strategies

This includes the inventory stocking at various locations in whole Supply Chain as well as the

structure of Supply Chain. Network structure designing is very tedious job in after-market supply

chain as there are many performance indices to decide upon. After an extensive study, we

come to conclusion that After-Market Supply Chain can be measured on following parameters:

Cost

Quality

Lead Time

Service Level/Availability

There are some basic network structures followed in current industry scenario:

Supplier Warehous

Local

warehouseDealer

Customer

Supplier Warehous

Local

warehouse

Customer

Supplier Warehous

Dealer Customer

Supplier Customer

A1

A2

A3

A4


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5. Case Study: Automobile Industry

ABC (name is kept not disclosed to hide the confidential data) Service Supply chain consists of

Auto OEMs, their Dealers and Final Customer. The most important factor here is CES doesnt

directly interact with the final consumer. The routing passes through always OEMs. And hence it

becomes very complex to optimize as it is difficult to keep everyones interest intact and

maintain the high customer satisfaction level but not impossible. OEM Dealers location is the

place where service action will take place.

5.1 Distribution Network: Application of AHP

As discussed above that there are four basic types of distribution network. Now selecting the

optimum way on the basis of performance parameters is very complex problem. Hence we used

AHP (Analytical Hierarchy Approach) to get the most suitable and optimum result.

*The Calculation for AHP is not included in the paper.

Parameter Matrix

Cost Quality

Lead

Time Availability

Final Weightage

Cost 1 1 2 0.33333333 0.18336

Quality 1 1 2 0.5 0.22397

Lead Time 0.5 0.5 1 0.2 0.0998

Availability 3 2 5 1 0.49286

Column Sum 5.5 4.5 10 2.03333333

Final Weightage

A1 0.266845


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A2 0.214139

A3 0.283948

A4 0.235068

Fig. The Optimum Distribution Network Structure for the Company

5.2 Forward Planning: Service Parts Distribution and Inventory Allocation

To improve this activitydemand process is needed to be known. But we know, Service

parts are of highly erratic demand. And without accurate demand, it is very difficult to manage

the inventory levels at each echelon of supply chain partner. Hence, before going for the

inventory level, we have to divide all the items in some specified categories for simplification of

the policies.

a) Classification with respect to Cost: Classifying inventory items with respect to theircost is usually achieved with ABC analysis, which is a commonly applied technique

based on Paretos law.

Sr.

No. Item Name

Cost (In

dollar)

Annual

Usage

Usage

Value

Cumulative

Value Rank % value

Cumulative

%

1 ALPHA $X 10 $10 X 10 X 1 24.44987775 24.44987775

2 Beta $Y 40 $40 Y 10 X + 40Y 2 68.4596577 92.90953545

3 Gama $Z 50 $50 Z --- 3 1.833740831 94.74327628

4 Gama 2 $M 50 $50 M ----- 3 1.833740831 96.57701711

5 Zeta $N 100 $100 N -------- 4 3.178484108 99.75550122

Supplier OEM Warehouse OEM Dealers Customer

Money &

Information Flow

Material Flow

Service Flow


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6 Omega $O 50 $50 O ----------- 5 0.244498778 100

Total $40,900.00 100

Figure: ABC Classification for SCR-Items Figure: ABC Classification for

SCR-Items

CLASSIFICATION

ITEMS CATEGORY

ALPHA A

Beta A

Gama B

Gama 2 B

Zeta B

Omega C

Figure: Classification of Items

A B C


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b) Classification with respect to Criticality: It is related to the consequences

caused by the failure of a part in case replenishment is not readily available. Parts

are usually classified in terms of their criticality using qualitative criteria.1. Highly Critical (class H): Absolutely essential for the operation of the equipment.

2. Moderately Critical (class M): Moderate effect on the operation of the equipment.

3. Low Critical parts (class L): Parts that hardly affect the operation of the equipment

CRITICALITY

COST H M L

AALPHA &BETA --------- ------

B ZETA GAMA 1& 2

C -------- OMEGA

Figure1: Classification on the basis of Criticality and Consumption

c) Classification with respect to Demand/ (Failure Rate): Demand pattern for theservice items is highly erratic for each individual item. Hence it is necessary to

have a classification on the basis of demand rate. As we are only considered with

the Service parts, so the demand depends on Failure Rate of the items.

High RPH (High

Demand)

Medium RPH (Medium

Demand)

Low RPH (Low

Demand)

CRITICALITY CRITICALITY CRITICALITY

COST H M L H M L H M L

A BETA -- --

--

-- ------ ------

ALPH

A -- --

B ------ -- --

--

--NOZZEL GAMA 1& 2

----- -- --

C ------ -- --

--

-- ------ OMEGA ----- -- --


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Figure: Classification with respect to Demand Rate, Criticality and Consumption

SELECTION OF INVNETORY SYSTEMS:

After the classification of Inventory items, control policies can be established associated

with each group of items.

ITEM

CATEGORY

(Cost/Criticalit

y/Demand)

POLICIES

Beta A/H/HD Tight Control, Continuous Replenishment System

ALPHA A/H/LD

Tight Control, Continuous Replenishment System (S-

1, S)

Zeta B/M/MD Periodic replenishment System

Gama B/L/LD Periodic replenishment System

Omega C/L/LD kept in Stock, Cost-based Stocking

Figure 2: Policy Decision for the Items with respect to Classification

5.3 Inventory management for Low Demand item: METRIC Model

Generally Low Demand item posses a great problem to us during maintain the inventoryat different echelon. So here only the case of Low Demand Item is discussed.

In our specific case, we have one OEM warehouse and many OEM-Dealers. One-to-

One Replenishment System says as soon as an item is sold to the customer at Dealer Location,

simultaneously an item is ordered from Warehouse. This is called S-1, S System. Here, S is

the level of Inventory we need to maintain. As soon as one unit is sold and inventory level

becomes S-1, one unit is ordered from the Warehouse.

If for any product, mean demand rate at Dealer Location is i (i is Dealer Location and =

0, 1, 2,), then it is assumed that the demand follows the Poisson distribution. And if there are N


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Dealers, then the Demand Rate (w) at OEM-Warehouse will also follow the Poisson distribution

with Mean Demand Rate:

For One-to-One Replenishment, if stock level at Dealer Location is s i then orders one

unit from OEM-Warehouse each time. If warehouse has the stock then it will replenish the

demand and say the time to replenish item from warehouse to Dealer is i. And if Warehouse

does not have the item, it orders to CES: Supplier of the Item. Say the time to replenish the item

from CES to Warehouse is w.

Now, if the Demand Rate at Dealers Location is and mean time to replenishment is

then the number of units in order mi is Poisson Distributed with parameter . If the stock level

at dealer location is si, then the Probability of a stock-out is

And the Expected Back-orders (EBO) will be:

At the OEM-Warehouse, the Demand Rate is , the Mean Replenishment time is and the

Stock Level is sw. Then the Stock-out probability at Warehouse will be:

Backorders at the Warehouse do not necessarily reduce the service level at the Dealers

Location, as long as stock remains at the Dealers Location. However, if Backorders accumulate

at the Warehouse, it becomes more likely that the Dealers will be affected because the

replenishment time at the Dealers Location becomes longer. The average additional waiting

time at the Dealers Location is:


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Wo= (Expected Numbers of Backorder at Warehouse)/

This is an application ofLittles Law.

Hence the expected replenishment time from warehouse to dealer will be:

And new probability will be:

METRIC Model Demonstration:

The inputs needed are:

INPUTS

Mean Demand Rate (say monthly)

Mean Transit time from CES to TML (In months)

Table: Input data for product Availability

Gama 1 Gama 2 Beta Zeta Zeta seat ALPHA

1i 1i 2i 2i 3i 3i 4i 4i 5i 5i 6i 6i

OEM

Warehousei=0 5 0.50 5 0.50 10 0.50 7 0.50 5 0.50 2.5 0.50

Dealer 1 i=1 2.5 0.01 2.5 0.01 5 0.01 3.5 0.01 2.5 0.01 1.25 0.01

Item

No.

Table: Stock Quantity at warehouse

0 2 5 8 10 15 20

1 0.917915 0.4561869 0.042021038 0.0011403 6.16269E-051.06924E- 4.06897E-


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08 13

2

0.917915 0.4561869 0.042021038 0.0011403 6.16269E-05

1.06924E-

08

4.06897E-

13

3

0.9932621 0.875348 0.384039345 0.0680936 0.013695269

6.90082E-

05

8.10925E-

08

4

0.9698026 0.6791528 0.142386447 0.0098737 0.001019394

9.18386E-

07

1.86906E-

10

5

0.917915 0.4561869 0.042021038 0.0011403 6.16269E-05

1.06924E-

08

4.06897E-

13

6 0.7134952 0.1315323 0.001838085 6.711E-06 9.318E-08 5.22249E-13 0

Figure: Backorder Quantity at OEM Warehouse

Item NoQuantity in Stock at Dealer Location

0 2 5 8

1 1.2916667 0.0142781 1.93765E-10 0

2 1.2916667 0.0142781 1.93765E-10 0

3 2.5833333 0.3301208 1.94224E-05 7.358E-14

4 1.8083333 0.0771035 4.55557E-08 5.248E-16

5 1.2916667 0.0142781 1.93765E-10 0


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6 0.6458333 0.000218 1.54548E-13 0

Figure: Backorder Quantity at OEM Dealer

5.4 Process Improvements: Removing the Waste

After market Supply Chain activities, as discussed earlier, can be classified into two

major groups: Forward Planning and backward Planning. Forward Planning includes mainly the

Parts Distribution Strategy across the supply chain while the backward planning include part

Return process (if Company wants to get its part back to its premises), Warranty management,

Information and Money flow etc.

5.4.1 Backward Planning: Part Return Process

Briefly, Part Return Process takes care of all the processes related to replacement,

service and incident reports. Since the replacement of part at OEM Dealers Location till failure

Analysis and warranty claim settlement, if any, are covered in this process.

P-diagram is one of the best ways to design the robust process. So we take the help of

P-Diagram to design the part Return process. This simply clarifies the input and output for the

process with possible error states. This helps us in taking the Preventive Maintenance to

escape the error states. Figure below shows theP-Diagram for the Part Return Process.

No timely intimation ofreplacement

NOISE FACTORS

Control over scheduling Information integration

among partners

Continuous tracking

CONTTROL FACTORS

Unable to identify

ERROR STATES

Safely and timelyPart Return

DESIRED OUTPUT Intimation of replacement Condition of failed part and

Location

Schedule of the dispatchfrom dealer Details of art

INPUT PARAMETERS

Part Return

Process


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5.4.2Backward Planning: Warranty Management

For the parts covered under the warranty claim, the company has to follow the very

careful procedures. The true claim should be met while the fraud one should be rejected. Again,P-Diagram for the Warranty Management can give us some warning bell in advance to correct

the process.

5.4.3 Backward Planning: Information Integration

Visibility and traceability are two technology-related issues that are driving forces in

supply chain improvements. Visibility allows an organization to track a part or order as it passes

through the supply chain. Traceability, on the other hand, allows firms to trace individual

components.

Enterprise Resource Planning (ERP) encompasses the different activities into a

company and can be considered as the backbone of IT infrastructure. Nowadays ERP systems

should organized an enterprise completely according to customer needs, regarding the

business environment of the enterprise as a supply chain including, repair vendors,

manufactories, 3PLs network, OEM logistics networks and customers.

6. Conclusion

Once the supply chain and the services are operating, dynamical metrics (Keep

Performance Indicator KPIs) should monitor the customer and supply chain performance. From

a customers perspective, service quality is defined by delay of the part request and from the

OEM supply chain perspective there are various measurements involve associated with the

availability of the service. The principal is part fill rate, the fraction of demand for parts that is

available in stock at the site receiving the demand.


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References:

Bruce, M., Daly, L., Towers, N., 2004. Lean or agile: A solution for supply chain

management in the textiles and clothing industry? International Journal of Operations andProduction Management 24 (2), 151170

Cohen, Moris A., Agarwal Narendra, Agarwal Vipul, Winning in the aftermarket, HowardBusiness Review, May 2006

Christopher, M., & Towill, D. (2001). An integrated model for the design of agile supplychains International Journal of Physical Distribution & Logistics Management, 31 (4), 235-246

Hammant J., Disney S.M., Modelling the consequences of a strategic supply chain initiativeof an automotive aftermarket operation, International Journal of Physical Distribution &

Logistics Management, Volume 29 issue 9

Womack, J., Jones, D., Roos, D. (1990), The Machine that Changed the World,HarperPerennial

About the author

Deepak Bartwal

National Institute of Industrial Engineering (NITIE), Mumbai

E-mail id: [email protected]

Mobile No. : +91-7666236135

improving after market supply chain a top-down approach

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