Examples of Supply Chain Optimization projects Initiated and Managed by Vladimir Krasojevic

Due to confidentiality only projects older than 5 years included

Assembly Lead Time reduction

Context: High WIP inventory & assemblage time

• 15 steps=Total activity time 4 hours+36 hours thermical test

• Lead time = 35 days

• Batch management

• High quality/craftmanship/activity

• Final Quality check after thermical test

• Full batch release

© vladimir krasojevic

Assembly Lead Time reduction

Results: 65% improvement of WIP/LT

• CHANGES: – Thermical test multiple

changes of temperature in 12 hours instead of stable high temperature for 36 h; Bottleneck: QA

– Release of good watches from the batch: specific pieces retained: Technology solution for batch management improved

– Process group activities

– Cash-flow (WIP) & lead time reduced from 35 to 12 days

© vladimir krasojevic

Material PULL and Heijunka

• High volume factory

• Supplier with European DC

• Distance: 60 km

• Order lead time according to standard ERP configuration: Make to order, based on production plan, safety stock, price according to EOQ

• Expensive material

• Simple portfolio : 3-5 different item materials SKUs

• Average stock in factory 25 days

Context: High value stock and ERP ordering

© vladimir krasojevic

Material PULL and Heijunka

Results: 60% improvement with weekly Pull

• CHANGES: – Change in ERP – weekly requirements and

stock by AT item ; Bottleneck: Purchasing, QA, IS

– Weekly requirements submitted: Full truck load sent during the week.

– Price list adapted to reflect continuous flow: flat price per item independently on quantity in delivery

– Cash-flow (factory AT stock) reduced from 25 to ~ 10 days

© vladimir krasojevic

Supplier driven VMI

Context: No warehouse in factory: VMI

• New factory built in residential area

• No on-site direct material warehouse (max 1 day stock)

• Supplier of blanks is «next door»

• New VMI process is established to «help-out» factory

• Daily exchange of scheduling, stock and production plan of cigarette factory

• 1 truck used to replenish by pallete according to scheduling

• Average stock in factory 1 day. Supplier: 17 days

© vladimir krasojevic

Supplier driven VMI

Results: 97% (60%) less vs. other factories

• CHANGES: – Daily exchange of stock and

scheduling in EXCEL; Bottleneck: IS integration

– Expert (informal) rules for printing at supplier(slow movers 25 days, fast movers 3 days).

– Commitment & price through daily orders: no remuneration for Supplier stock (recompensated by lower paper stock)

– Cash-flow (factory blanks stock) 1 instead of 45 days (18 with supplier)

© vladimir krasojevic

Process flow optimization

Context: Different lead time & WIP inventory

• Repacking process is highly manual

• 2 different social-work companies have been used for the same task

• Bottleneck identified with time needed for repacking (lack of resources and long lead-time)

• Field visit and analysis of the process identified major difference in process: – Small cell, continuous repacking in teams of

two vs.

• Batch repacking, team work by activity

• Repacking time 45 days in bigger of two companies

Company 1

Company 2

© vladimir krasojevic,

Process flow optimization

Results: 50% time reduction with same teams

• CHANGES:

– Use of the same process in 2 companies: 50 % reduction of lead time and work in progress

– Initial questions whether specific social work company process could be transferred to another place

– Higher satisfaction of operators (they see results of their work, every day)

– Elimination of unnecessary control steps (quantity & quality)

– New lead time for market: 20 days and reduced WIP stock

Company 1

Company 2

Company 2

© vladimir krasojevic

Cost-to-serve optimization

Context: Cost, stock and availability

• Activity Based Costing from manufacturer to Retailer – simulation and estimates

• Assumption might be wrong (ie: delivery frequency and minimum stock in POS)

• OoS in POS – holly grail of FMCG stock management service level 98%

• Manufacturer push to retailers

• Plannograms: retailers paid to expose all products in portfolio

• Manufacturers stock 30 DOI, Retailers distribution system 12 DOI, POS estimate 20-30 DOI (previous assumptions 3-7 DOI)

© vladimir krasojevic

Cost-to-serve optimization

Results: Improvement initiatives started

• CHANGES: – Retailer to eliminate back-office stock and

store all in shelves: 25 % reduction of OoS potential (implemented in other categories)

– Introduction of fiscal warehouse status in Switzerland 1 day of retail stock value = 20 days of manufacture value (bonded warehouse status): potential to reduce retail distribution stock from 12 to 3 days (75%)

– Higher interest for collaboration, consumption driven supply : demand sensing, daily deliveries, portfolio optimization (retail stock potential from 20-30 to 3 DOI (80%)

© vladimir krasojevic

Replenishment and Stock Optimization

Context: Replenishment of Vending Machines

• Vending machines visited once in 1-3 weeks to be replenished

• Machines are usually filled up to their capacity – «column size»

• Operator use the rule defined by back office

• If he decides to change the rule, handheld computer has to be reprogrammed

• Most of operators are not changing quantity in order to be more efficient

• Stock in vending machines is up to 50 days of inventory

© vladimir krasojevic

Replenishment and Stock Optimization

Results: 60% potential of stock reduction

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Stock loaded Sales Remaining Safety factor

• CHANGES: – Detailed analysis of sales, stock,

replenishment not in line with consumption: 60% reduction potential identified

– New rules defined: load standard quantity in multiple of 5 packs (slow movers), 10 packs fast movers

– New order preparation proposed on automatic line, based on historic sales

– Higher frequency of delivery proposed to reduce time for cash collection

– Total cash-flow improvement potential up to 75%. Project not implemented.

© vladimir krasojevic

Direct Store Deliveries Optimization

Context: Van Sales - Portfolio Planning Complexity

• Gemba walk

• Complex population with different SKUs by nationality

• Delivery specific portfolio picking and preparation

• Complex Order Cheking process (Manual and without system support)

• Van sales deliveries supported by complex delivery planning and forecasting process

• 2.5 hours (total) spend in the morning and at the end of the day on order control, checking and reconciliation

• 60% returned from delivery (not sold)

© vladimir krasojevic

• 2 hours considered as «lost for sales» daily from deliverymen

Direct Store Deliveries Optimization

Results: 2 hours more for sales, better FA, low return

• CHANGES: – Standard portfolio for every

delivery

– Every load identical: Heijunka

– Forecast on returned vs loaded to understand optimal portfolio

– 2 hours eliminated as non-value added and used for extra sales (25% productivity improvement)

– Returned goods non delivered 50% reduction

– Extra sales (not claimed)

© vladimir krasojevic