Practical implementation of inventory strategy in project market environment

1. CASE STUDY
By Meidi Imanullah, MBA

2. 1. Inventory
2. Case Study
3. Discussion

3. Why Inventory?
Inside Inventory
Inventory Strategy

4.  Every Business needs inventory
 A shortage affects ability to fulfil Customers’
demand which lead to Customer
dissatisfaction and loss of sales

5.  SKU (differentiated by packaging, size, color,
type, and other configuration)
 Inventory Groups; FG, RM, PM, consumable,
parts
 Parameters; consumption rate, demand pace
& trend, lead time, demand variation,
EOQ/MOQ/batch/lot size, standard cost,
service level target, and criticality
 Tradeoff between inventory cost versus
availability

6.  The more SKUs to serve ex-stock, the more inventory cost
 The higher safety stock required, the more inventory Cost

7.  The goal is to have enough inventory
availability to support the business at the
cost effective way
 Must be aligned with the Business Strategy
◦ Good knowledge of market competition and
Customer expectation
 Good knowledge of supply capacity and
constraints

9. ◦ Background
◦ Issues
◦ Review and Analysis
◦ Recommendation
◦ Implementation
◦ Result

10.  Fosroc is a world leader of Constructive
Solutions in construction market industry
 The market is both new constructions and
building maintenance and repair projects
 Timely delivery and lead time assurance is
critical in serving Projects

11.  OTIF level was low
 Distribution cost over budget
 Fast moving SKUs were not available when
needed
 Slow moving was 30% of total inventory
 Stock at more than 60 days of inventory
 Truck shortage was common
 Shipment lead time exceeded normal lead
time

12.  Issues were from 3 pillars of SC; Service Level,
Inventory, and Cost
 After doing why-why analysis, root of the
problem mostly related to inventory
availability
 Inventory analysis was arranged to
understand the inventory top contributors
and trends
 Demand analysis was arranged to identify fast
moving items

14. Item
Name
Annual
Value
Item
Name
Annual
Value
%
Contribution
Accummulated
Contribution
Item 01 7,318,800 Item 08 38,551,140 44% 44%
Item 02 455,400 Item 03 17,597,580 20% 64%
Item 03 17,597,580 Item 05 9,170,460 10% 74%
Item 04 4,608,000 Item 01 7,318,800 8% 83%
Item 05 9,170,460 Item 07 6,963,690 8% 90%
Item 06 897,840 Item 04 4,608,000 5% 96%
Item 07 6,963,690 Item 10 2,048,000 2% 98%
Item 08 38,551,140 Item 06 897,840 1% 99%
Item 09 411,510 Item 02 455,400 1% 100%
Item 10 2,048,000 Item 09 411,510 0% 100%
Total 88,022,420 Total 88,022,420
 Pareto analysis helped to identify top
contributors of Inventory and Demand

15.  60 SKUs contributed to 80% of inventory
(combination of FG & RM)
 Further review of these SKUs were needed
◦ Demand pace & trend
◦ Demand variation
◦ EOQ/MOQ/batch/lot size
◦ Supply lead time
◦ Service level target
◦ Criticality versus Importance
 Compared estimated average end stock with the
actual – identifying the biggest gaps as the
highest priority

16.  Identified some items having higher end stock
than estimated (or calculated)
 Further analysis needed to check the correctness
of inventory parameter setup
Item
Name
Average
Actual Stock
Value
Average
Demand
STDEV
Demand
SL
Target
Safety
Stock
Lead
Time MOQ Min Max
Average
Stock
Estimated
Average
Stock Value
Item 08 3,212,595 430 321 97% 1,034 7 700 1,785 2,537 2,161 1,030,974
Item 03 1,466,465 351 474 97% 1,243 9 1000 2,243 3,243 2,743 1,267,163
Item 05 764,205 248 313 97% 838 12 500 1,583 2,328 1,955 457,546
Item 01 609,900 161 191 97% 519 3 400 919 1,319 1,119 479,082
Item 07 580,308 236 341 97% 877 4 400 1,277 1,677 1,477 533,206
Item 04 384,000 122 140 97% 384 5 200 584 784 684 328,468
Item 10 170,667 94 93 97% 268 11 1000 1,268 2,268 1,768 707,245
Item 06 74,820 50 51 97% 146 9 200 346 546 446 115,008
Item 02 37,950 89 130 97% 333 7 400 733 1,133 933 42,901
Item 09 34,293 13 14 97% 40 3 600 640 1,240 940 299,774
Total 7,335,202 5,261,368

17.  35 fast moving SKUs contributed to 80% of
total value
 These SKUs were good candidate of Made-to-
Stock SKUs
 The result were reviewed and discussed with
Sales and Customer Service team
◦ Received feedbacks – certain additional SKUs were
requested and some SKUs were not needed on
stock -> led to additional analysis of ABC by
transaction

18.  40 fast moving SKUs contributed to 80% of
total transaction
 Identified high transaction low value SKUs -
were not expensive nor sold in a large
quantity but frequently sold throughout the
year
 Not all of them were part of A class by value
 Identified low transaction high value SKUs too
◦ Sold only 1-2 times in a year but the value was high
Need to formally accommodate the ABC by
transaction

19.  A:B:C = 80:15:5
 Box size
represented the
number of SKUs in
each box
◦ AA = 25 SKUs
◦ BA+AB = 45 SKUs
◦ CA+BB+AC = 100 SKUs
◦ CB+CC+BC = 300 SKUs
Value
Transaction
High
High
Low
C-C B-C
C-B
C-A
A-C
B-B
B-A
A-B
A-A

20.  Redefined SKUs classification based on the
combination of value-transaction
 Corrected inventory parameter to give better
result
 Set actions for Inventory reduction

21.  To ensure that at least 80% of value and
transaction can be served from inventory
Value
Transaction
High
HighLow
C-C B-C
C-B
C-A
A-C
B-B
MTS
MTS
MTS

22.  Production is started when a clear order received
 Service promise based on production lead time
Value
Transaction
High
HighLow
C-C B-C
C-B
MTO
MTO
MTO
MTS
MTS
MTS

23.  Production is started when the order is approved to be served
 Service promise based on production lead time + RM supply lead
time
Value
Transaction
High
HighLow
MTA MTA
MTA
MTO
MTO
MTO
MTS
MTS
MTS

24.  The new SKU classification and service
promise was formally introduced to the sales
team at annual sales meeting
 Simultaneously, SC team redefined inventory
parameter and configuration based on new
SKU classification and inventory reduction
initiative
◦ Negotiation is conducted with the suppliers to
reduce MOQ and supply lead time
◦ Rearranged inventory planning based on min-max
and continuous review

25.  Inventory reduction from 60 days to 40 days
while supporting the demand at forecasted
value
 Slow moving reduction to 20%
 OTIF improvement up to 90%
 Were the Sales team happy?

26.  Did the Inventory Strategy create a
competitive advantage?
 Can the same Inventory Strategy be
implemented in other industry type
◦ FMCG?
◦ Pharmaceutical?
◦ Automotive?
◦ Fashion?