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Kushaan Shah - Hilti Final

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My final presentation for my summer internship at Hilti Inc.

My final presentation for my summer internship at Hilti Inc.

Published in: Business, Economy & Finance

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  • Service Level: probability that a chosen level of safety stock will satisfy customer demandDemand Volatility: Average daily demand of the last 6 monthsSupply Quality: Lead time in the last 6 monthsForecast Accuracy: Forecast deviation in lead time in the
  • 6 monthsOnce a Month
  • Harrisburg EffectExplain reason for brief instabilityFix Scale for COP – make it flat (Week 24 – Week 28)
  • Dan note’s: Split into two different slides and fill in the fish bone
  • Relate back to COPHarrisburg Effect
  • Upstreaming (Very Sporadic Items, shipped up to the NDC’s), QW and RW (use average order size + daily demand at lead time) – RP1 (Calculated)Laser PointerFigure out what exactly you want to say in the proposed result (message didn’t sink in)Fix Chart for QRS – UVW (Amount of Material in an order), Order Frequency Split into two slides
  • Be more concise
  • Clarify that your saying weekly demand hits review was the solution, that the monthly process was in place but not reactive enough
  • - ROP arrow for Week 24
  • - Toronto Live Schedule
  • Transcript

    • 1. www.hilti.com 1 RE-ORDER POINT AND INVENTORY ANALYSIS VISALIA DC Kushaan Shah Summer 2013
    • 2. www.hilti.com 2 Agenda ● PROJECT BACKGROUND AND GOALS ● DATA COLLECTION ● DATA ANALYSIS AND IMPROVEMENT PLANS ● CONCLUSIONS ● FUTURE OF PROJECT ● QUESTIONS
    • 3. www.hilti.com 3 ● 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
    • 4. www.hilti.com 4 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)
    • 5. www.hilti.com 5 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
    • 6. www.hilti.com 6 • 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
    • 7. www.hilti.com 7 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
    • 8. www.hilti.com 8 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
    • 9. www.hilti.com 9 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
    • 10. www.hilti.com 10 COP FAILURE ROOT CAUSE PROCESS MAP
    • 11. www.hilti.com 11 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
    • 12. www.hilti.com 12 84.00% 85.00% 86.00% 87.00% 88.00% 89.00% 90.00% 91.00% 92.00% W7 W8 W9 W10 W11 W12 W13 W14 W15 W16 W17 W18 W19 W20 W21 W22 W23 W24 W25 W26 W27 W28 Visalia COP% ROP
    • 13. www.hilti.com 13 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0 50 100 150 200 250 300 350 400 450 500 VISALIA COP PARETO WEEK 24 – WEEK 28
    • 14. www.hilti.com 14 0% 2% 4% 6% 8% 10% 12% 14% 16% 0 5 10 15 20 25 30 Week 24 Week 25 Week 26 Week 27 Week 28 Part Failures - Visalia COP 0% 5% 10% 15% 20% 25% 30% 0 5 10 15 20 25 30 35 40 45 50 Week 24 Week 25 Week 26 Week 27 Week 28 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
    • 15. www.hilti.com 15 ROP 0.28% 2.26% 1.29% 1.98% 1.35% 1.57% 84.00% 85.00% 86.00% 87.00% 88.00% 89.00% 90.00% 91.00% 92.00% W7 W8 W9 W10 W11 W12 W13 W14 W15 W16 W17 W18 W19 W20 W21 W22 W23 W24 W25 W26 W27 W28 RWS: 387514 Parts Visalia
    • 16. www.hilti.com 16 • 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 0% 10% 20% 30% 40% 50% 60% 0 20 40 60 80 100 120 140 Week 24 Week 25 Week 26 Week 27 Week 28 Availability or “No Stock” Failures - COP
    • 17. www.hilti.com 17 • 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
    • 18. www.hilti.com 18 0% 5% 10% 15% 20% 25% 30% 35% 40% 0 10 20 30 40 50 60 70 Week 24 Week 25 Week 26 Week 27 Week 28 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
    • 19. www.hilti.com 19 3.00 3.10 3.20 3.30 3.40 3.50 3.60 3.70 3.80 3.90 4.00 Week 21 Week 22 Week 23 Week 24 Week 25 Week 26 Week 27 Week 28 Millions 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)
    • 20. www.hilti.com 20 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
    • 21. www.hilti.com 21 • 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
    • 22. www.hilti.com 22 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
    • 23. www.hilti.com 23 QUESTIONS?