<Supply Chain Management Consulting for CoDRINK> Black Swan
c.m. 900 800 700 600 500 400 300 200 100 0 -100 -200
Current logistics is inefficient due to supply-demand imbalance and requires optimized integrated system Supply-demand of Green Water, 1qrt. Excessive supply
1
Excessive demand
Common approach should be developed based on reduction of supplydemand imbalance at minimal transport and warehouse costs Supply Demand
The same patterns in all CoDRINK products. The way how delivery system is organized now
Excessive Supply/Demand
Stocks Estimate excessive S/D for each city, product and quarter
Each city
Excessive supply in one city can suffice excessive demand in another
3
2
One city supplies 20 recipients on average despite distance and freight costs
To test the model we launch a pilot project in the Central Federal District on the basis of 3 products
Var2 x2 x1
Var3 x1 x1
x2
x0
x4
We analyze various combinations of shipment modes to minimize transportation costs
4
327
Demand on CoDRINK goods within regions, FY 2013
100
CFD*
227
CFD
Russia Less CFD Russia
Other districts
Green water
Yogurt
Current logistics costs
B C D E F
5 -4 -7
5 6 5
Conduct routes from the nearest cities to meet all demand excesses Links Quantity, c.m C-F 5 B-F 5 B-E 6 A-E 1 A-D 4
1H 2014
2H 2014
1H 2015
2H 2015
1H 2016
2H 2016
Pilot project European area Urals
CFD contributes 50% of EBIT and 19% of demand. Siberia & Far East Launching the pilot Warehouse project in CFD we optimization bring in value to the Marketing half of our business Change management
Added value, 2014
Products relevant for CFD pilot project
Soft milk
*Moscow is excluded 81% from analysis
11
1 4
If successful, the pilot project is rolled-out to the entire CoDRINK company in two years
CFD is selected as a pilot as it perfectly represents Russian supply chain CoDRINK Revenue within regions, FY 2012
A
-10
C F at min Costs
Var1 x1 x2
Divide cities in 2 groups. For each recipient sort all suppliers on distance (km)
12
Modeled costs
36,1 mln.R
Additional revenue
Road map: 1. Develop logistic procedures 2. Contract expeditors for real rates 3. Run test races and evaluate results and rectify any issues found
4. Expand to Urals region 5. Expand to Siberia and Far East 6. Sum up results and check for inconsistences p.2
5 Model outputs form a ready-for-implementation solution
6 Current system can be easily extrapolated on other logistic projects
Optimized routes
0,5k RUB/m3
0,4k
RUB/m3
DC
Replenishment schedule
Limitations: • Truck vol./weight capacity • WH expansibility • Alternative costs
0,9 RUB/m3
0,7k RUB/m3
Target
A
B
D
Source
C
C
F
Frequency
Each 2 weeks
Each week
Each 4 weeks
Cargo size
FTL
5 ton truck
LTL
Inputs: • Product profile (vol./ weight) • Target cities • Demand & Supply • Freight rates • Handling costs & rent
1.38
Total system costs
WH rent
0.42
WH operations
0.59
Transp.
-32%
0.94
0.97
0.31
0.35 0.23
0.40 0.23
0.37
m3
7 Current solution can bring significant project flow to the company 26-52 weeks $0,6 - 0,7 mln
Transitional support
Procurement and contracting
12-24 weeks $1 - 2 mln (or) % of economy
Operations optimization
6-8 weeks $0,4 mln (or) % of economy
Organizational structure and logistics strategy
12-14 weeks $0,6 mln
Logistics optimization
* based on public data on Accenture rates
Total:
Tailored solution
Resources: • 3PL’s • Logistic companies • Distributors
0.39
kRUB per
Model framework
up to $3 mln in additional dealflow
8 Summary The model analyzes excessive demand and supply, conducts optimal routes with minimal costs and brings value to CoDRINK Pilot project in CFD involves transfer of 3 products
17 cities 3 products with imbalanced demand and supply CFD can be easily expanded
Current costs less modeled costs plus extra-revenue 36,1 mln. rub. In 2014
Expansion and business development 1. The system is easily extrapolated on other businesses 2. Developed solution can bring up to 32% decrease in costs depending on type of product 3. Supply chain optimization can originate up to $3 mln from complimentary services and project p.3
Black Swan Konstantin V. Samarin
• • • •
k.v.samarin@gmail.com +7 (916) 942-23-52 HSE, Master’s Degree Programme, Strategic Management of Finance Microsoft Case Competition Sky – Finalist Banks’ Battle 2013 – Semifinalist Youth Russian Petroleum & Gas Challenge 2013 - Semifinalist
Dmitriy O. Shvetsov
Dmitriy S. Chupin
• • • •
chupinds@gmail.com +7 (903) 195-70-13 HSE, Master’s Degree • Programme, Strategic Management of Finance Microsoft Case Competition • Sky – Finalist “Young Financier” (Perm region • CFO Association) - Winner
dishv@mail.ru +7 (929) 577-31-25 HSE, Master’s Degree Programme, Strategic Management of Finance Student’s International Finance Contest – Winner Student’s Regional Microeconomics Contest – Winner
Artem D. Kasatkin
kasatkin.artem@yandex.ru +7 (926) 525-84-57 • • • •
MGIMO, Bachelor of Economics CL Cup Russia 2013 - 3rd place Fincontest 2013 - 1 place FutureToday 2013 - Finalist
p.4
Appendix 1 Pilot area distance matrix, kilometers Km
Vladimir Ivanovo
Vladimir
115
Ryazan Smolensk
Tver'
Yaroslavl Belgorod Bryansk Voronezh Kaluga
Kursk
Lipetsk
Tula
233
607
364
217
865
582
696
366
714
495
354
348
726
406
113
984
701
796
485
833
610
473
592
370
439
669
484
384
295
518
262
187
404
689
680
250
722
363
536
679
471
299
866
531
686
315
715
648
355
960
688
776
472
809
721
449
430
256
512
151
407
490
469
225
286
429
333
451
228
119
345
361
395
108
311
339
Ivanovo
115
Ryazan
233
348
Smolensk
607
726
592
Tver'
364
406
370
404
Yaroslavl
217
113
439
689
299
Belgorod
865
984
669
680
866
960
Bryansk
582
701
484
250
531
688
430
Voronezh
696
796
384
722
686
776
256
469
Kaluga
366
485
295
363
315
472
512
225
451
Kursk
714
833
518
536
715
809
151
286
228
361
Lipetsk
495
610
262
679
648
721
407
429
119
395
311
Tula
354
473
187
471
355
449
490
333
345
108
339
266 266
p.5
Appendix 2 Costs, 1.5 ton shipment, Rubles Rub
Vladimir
Vladimir
Ivanovo 2 359
Ryazan Smolensk
Tver'
Yaroslavl Belgorod Bryansk Voronezh Kaluga
Kursk
Lipetsk
Tula
3 067
5 312
3 853
2 971
6 861
5 162
5 846
3 865
5 954
4 640
3 793
3 757
6 026
4 105
2 347
7 575
5 876
6 447
4 580
6 669
5 330
4 508
5 222
3 889
4 303
5 684
4 574
3 973
3 439
4 778
3 241
2 791
4 093
5 804
5 750
3 169
6 002
3 847
4 886
5 744
4 496
3 463
6 867
4 856
5 786
3 559
5 960
5 558
3 799
7 431
5 798
6 326
4 502
6 525
5 996
4 364
4 249
3 205
4 742
2 575
4 111
4 610
4 484
3 019
3 385
4 243
3 667
4 376
3 037
2 383
3 739
3 835
4 039
2 317
3 535
3 703
Ivanovo
2 359
Ryazan
3 067
3 757
Smolensk
5 312
6 026
5 222
Tver'
3 853
4 105
3 889
4 093
Yaroslavl
2 971
2 347
4 303
5 804
3 463
Belgorod
6 861
7 575
5 684
5 750
6 867
7 431
Bryansk
5 162
5 876
4 574
3 169
4 856
5 798
4 249
Voronezh
5 846
6 447
3 973
6 002
5 786
6 326
3 205
4 484
Kaluga
3 865
4 580
3 439
3 847
3 559
4 502
4 742
3 019
4 376
Kursk
5 954
6 669
4 778
4 886
5 960
6 525
2 575
3 385
3 037
3 835
Lipetsk
4 640
5 330
3 241
5 744
5 558
5 996
4 111
4 243
2 383
4 039
3 535
Tula
3 793
4 508
2 791
4 496
3 799
4 364
4 610
3 667
3 739
2 317
3 703
3 265 3 265
p.6
Appendix 3
Costs, 5 ton shipment, Rubles Rub
Vladimir Ivanovo
Vladimir 3 042
Ryazan
4 188 5 306
Tver'
Tver'
Yaroslavl Belgorod Bryansk Voronezh Kaluga
Tula
7 678 5 520 6 191 8 426 6 628 5 656 4 791 6 959 4 470 3 741
7 824 8 980 7 678
5 851 8 621 8 533 4 354 8 942 5 452 7 134 8 524 6 502
5 462 5 870 5 520 5 851
4 830 10 341 7 085 8 592 4 986 8 874 8 222 5 374
4 033 3 022 6 191 8 621 4 830
Belgorod
10 332 11 488 8 426 8 533 10 341 11 255
Bryansk
7 581 8 737 6 628 4 354 7 085 8 611 6 103
11 255 8 611 9 466 6 512 9 787 8 932 6 288 6 103 4 412 6 900 3 391 5 880 6 687 6 482 4 111 4 704 6 094 5 160
8 689 9 661 5 656 8 942 8 592 9 466 4 412 6 482
6 307 4 140 3 080 5 277
Kaluga
5 481 6 638 4 791 5 452 4 986 6 512 6 900 4 111 6 307
Kursk
8 864 10 021 6 959 7 134 8 874 9 787 3 391 4 704 4 140 5 433
Lipetsk
6 735 7 853 4 470 8 524 8 222 8 932 5 880 6 094 3 080 5 763 4 947
Tula
Lipetsk
5 306 8 980 5 870 3 022 11 488 8 737 9 661 6 638 10 021 7 853 6 521
Yaroslavl
Voronezh
Kursk
3 042 4 188 7 824 5 462 4 033 10 332 7 581 8 689 5 481 8 864 6 735 5 365
Ivanovo Smolensk
Ryazan Smolensk
5 433 5 763 2 973 4 947 5 219 4 509
5 365 6 521 3 741 6 502 5 374 6 288 6 687 5 160 5 277 2 973 5 219 4 509
p.7
Appendix 4
Costs, 10 ton shipment, Rubles Rub
Vladimir Ivanovo
Vladimir
Ryazan Smolensk
Yaroslavl Belgorod Bryansk Voronezh Kaluga
Kursk
7 753
Ryazan
9 082 10 378
Tula
10 378 14 635 11 031 7 731 17 541 14 353 15 423 11 921 15 840 13 328 11 785 13 126 10 625 11 402 13 993 11 909 10 783 9 781 12 292 9 409 8 564
Smolensk 13 295 14 635 13 126
11 008 14 218 14 117 9 274 14 590 10 546 12 495 14 106 11 763
10 558 11 031 10 625 11 008
9 826 16 212 12 439 14 184 10 006 14 511 13 756 10 456
Yaroslavl
8 902 7 731 11 402 14 218 9 826
Belgorod
16 200 17 541 13 993 14 117 16 212 17 270
Bryansk
13 013 14 353 11 909 9 274 12 439 14 207 11 301
17 270 14 207 15 198 11 774 15 570 14 579 11 515 11 301 9 341 12 225 8 159 11 042 11 977 11 740 8 992 9 679 11 290 10 209
Voronezh 14 297 15 423 10 783 14 590 14 184 15 198 9 341 11 740
11 538 9 026 7 798 10 344
Kaluga
10 580 11 921 9 781 10 546 10 006 11 774 12 225 8 992 11 538
Kursk
14 500 15 840 12 292 12 495 14 511 15 570 8 159 9 679 9 026 10 524
Lipetsk
12 033 13 328 9 409 14 106 13 756 14 579 11 042 11 290 7 798 10 907 9 961
Tula
Lipetsk
7 753 9 082 13 295 10 558 8 902 16 200 13 013 14 297 10 580 14 500 12 033 10 445
Ivanovo
Tver'
Tver'
10 524 10 907 7 674 9 961 10 276 9 454
10 445 11 785 8 564 11 763 10 456 11 515 11 977 10 209 10 344 7 674 10 276 9 454
p.8