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RE-ORDER POINT AND INVENTORY ANALYSIS

VISALIA DC

Kushaan ShahSummer 2013

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Agenda

● PROJECT BACKGROUND AND GOALS

● DATA COLLECTION

● DATA ANALYSIS AND IMPROVEMENT PLANS

● CONCLUSIONS

● FUTURE OF PROJECT

● QUESTIONS

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● As a global leader of value-added, top-quality products, two of Hilti’s main objectives are to:

• Increase the Quality of Service

• Optimize inventory

BACKGROUND

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BACKGROUND

Increase Service Quality

• One of Hilti’s top objectives is to improve customer satisfaction by delivering customer orders in a punctual and convenient matter

• Logistics uses a metric called COP to measure “Complete Orders delivered from the Primary location”

• A product ordered from Visalia’s region should be shipped from 6150

• 1 point of HNA COP is equivalent to almost $250,000 in freight• Big financial implications

• The target COP rate is 90% for each Distribution Center (Completed Primary Orders/Total Orders)

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BACKGROUND

Optimize Inventory

• Hilti currently uses the SB8 calculation to increase inventory levels in the NDC’s

• In its distribution centers, Hilti is moving from the “Days of Coverage” Method to the more Optimal “ROP” method

• ROP Method is intended to offset inventory increase in NDC’s

• Days of Coverage was a “blanket” approach:• X and Y item from Miami will both have a 9 day average demand

• ROP is a more statistical approach • X and Y item will be distinguished by lead time and average

demand

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• RP1 Calculation = Safety Stock + (Lead Time * Avg. Daily Consumption)

• Optimal for Stable Items and leads to Inventory Reduction• Calculated ROP (System)

• RP2 Calculation = Average Order Size + (Lead Time * Avg. Daily Consumption)

• Average Order Size = Quantity/Frequency• Used for more sporadic items when needed• Manual

• RP3 = Greater Value between RP1 and RP2• Done Manually

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Visalia

• Visalia processes about 1,500 orders a week and is the largest DC after Tulsa and New Jersey

• Visalia accounts for roughly 13.6% of the HNA COP and more than 65% of the West Region

• ROP was implemented in Visalia on Week 24

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GOALS

Project Goals:

• Analyze Hilti objectives in the context of a large distribution center

• Help implement ROP stocking logic within the Visalia DC

• Identify the most effective method to calculate manual ROP values

• Determine Impact of ROP on COP levels for Visalia DC

• Diagnose COP Failures and implement solutions to reduce failures

Ultimate Goal: • -5% Inventory Reduction and +8% Improvement in service quality

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DATA COLLECTION

Data Collection Plan:

• Review COP Failures:• Used Business Analyzer Tool on Excel• Ran weekly query to pull order and material numbers that failed

COP for Visalia

• Root cause analysis on the availability failures:• Used SAP to pull relevant order and material data:

• Sales Order (VA03)• Date of Order, Amount of Material, Location

• Stock and Requirements Situation (MD04)• MRP Type, Purchasing Group, Material Status

• Stocks for Posting Date (MB5B)• Amount of Stock Available on Date of Order

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COP FAILURE ROOT CAUSE PROCESS MAP

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Visalia COP

Failure

Not enough stock

available

Item not on Planning

Cycle (ND)

Item was added after

order completed

Item is Discontinued

and is phasing out

Item is a repair part

(U26)

Item is a special order (U51 – U59)

Stock was available but

order was routed away

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W7 W8 W9 W10 W11 W12 W13 W14 W15 W16 W17 W18 W19 W20 W21 W22 W23 W24 W25 W26 W27 W2884.00%

85.00%

86.00%

87.00%

88.00%

89.00%

90.00%

91.00%

92.00%

Visalia COP%

ROP

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No Stock Not Planned RWS Parts Item Added Specials Other Discontinued0

50

100

150

200

250

300

350

400

450

500

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

VISALIA COP PARETO

WEEK 24 – WEEK 28

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Week 24 Week 25 Week 26 Week 27 Week 280

5

10

15

20

25

30

0%

2%

4%

6%

8%

10%

12%

14%

16%

Part Failures - Visalia COP

Week 24 Week 25 Week 26 Week 27 Week 280

5

10

15

20

25

30

35

40

45

50

0%

5%

10%

15%

20%

25%

30%

RWS Failures - COP

• Observation: Spike in Parts Failures after Week 26

• Due to the Harrisburg Spare part project, Visalia Repair Center is no longer shipping customer orders and all repair parts are temporarily routed to Tulsa NDC

• Observation: Spike in RWS Failures after Week 26

• Material Number 387514 is reserved for a large project and will continue to route away until order is complete

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ROP

W7 W8 W9 W10 W11 W12 W13 W14 W15 W16 W17 W18 W19 W20 W21 W22 W23 W24 W25 W26 W27 W2884.00%

85.00%

86.00%

87.00%

88.00%

89.00%

90.00%

91.00%

92.00%

0.0028

0.0226

0.0129

0.0198

0.01350.0157

RWS: 387514

Parts

Visalia

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• Roughly 50% of all failures in a week are attributed to availability

• Analyzed “Material Movements” to view schedule of replenishments• Occasionally, a large order will deplete stock

• Also checked for National or Local Outages • A national outage will subsequently route the item to the closest DC

with available stock

• Graph – No Real Trend for Availability Failures as of yet

Week 24 Week 25 Week 26 Week 27 Week 280

20

40

60

80

100

120

140

0%

10%

20%

30%

40%

50%

60%

Availability or “No Stock” Failures - COP

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• Monitored a QRS – UVW chart to check for erratic items

• QRS• Number of Hits in last

6 months• UVW

• Variability from Normal Order Quantity

• Action:• QW and QR changed to

RP2 (Average Order Size)• Result:

• Decrease in QW and QR

• In the future, there are plans to start a process of upstreaming very sporadic items (S) to the NDC’s

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Week 24 Week 25 Week 26 Week 27 Week 280

10

20

30

40

50

60

70

0%

5%10%

15%20%25%

30%35%40%

Not Planned Failures - COP

• Checked weekly for not planned materials with a high frequency• Demand Hits: Items with more than 3 hits in the last 6 months • Hilti currently has a process in place which reviews ND’s monthly

• For these particular items, looked at the TABCD status, material status, and purchasing group

• MRP type is set to Y5 and a manual ROP (RP2) is turned on for items using average order size, daily demand, and lead time

• To date, 24 Items have been turned on for Visalia

• Result: Decrease in “Not Planned” Failures

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Week 21 Week 22 Week 23 Week 24 Week 25 Week 26 Week 27 Week 283,000,000.00

3,100,000.00

3,200,000.00

3,300,000.00

3,400,000.00

3,500,000.00

3,600,000.00

3,700,000.00

3,800,000.00

3,900,000.00

4,000,000.00

4,100,000.00

Inventory MUSD DC's

• Inventory Value (Provided by Global Team)• Biggest success is the money saved on inventory• 16.8% decrease in Inventory amount – 649,293 in reduction • $77,915.16 in annual savings (based on a 12% carrying cost)

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CONCLUSIONS

• Despite a slight decrease in COP, there is an offsetting savings in inventory carrying costs. What is the impact?

• Visalia DC annual inventory savings: $77,915 • Calculated from carrying cost at 12%

• Visalia DC COP from week 24 -28:• We have seen a .62% decrease in Visalia (if we disregard the

failures due to Harrisburg and item 387514)• Loss of $24,800 annually in transportation costs

• +1% on Visalia COP -> 0.16% rise in HNA COP (+ $40,000)*• -1% on Visalia COP -> 0.16% fall in HNA COP (- $40,000)*

*Based on $250,000 freight cost with all else equal

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• COP relies on many factors outside of ROP and is fluid in nature. • If ROP is helping us save money on inventory regardless of a

slight decrease in COP, its implementation should be encouraged

• Inventory shortage, unpredictable orders, and sporadic demand are all problems that we cannot eliminate but work to reduce. There are many factors of COP that are out of our control

• Manually monitoring COP failures, adjusting ROP levels where needed, and distinguishing materials by their demand nature can help combat some of the shortfalls

• It is recommended to have a manual eye even with automation

• Four or five weeks is not enough to see the full impact • Short-term setbacks can be offset by long-term objectives

• Conclusion: Keep manually monitoring COP and adjusting ROP levels

CONCLUSIONS

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FUTURE

• Will continue analyzing Visalia• Note any changes in Stock Availability

• Replicate project with another large Distribution Center• Toronto Roll-Out is being scheduled

• RP3 Calculation to be automated • Will take the optimal value between RP1 and RP2

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QUESTIONS?