Performance of omnichannel warehouse of Muslim fashion company in Indonesia based on workforce, equipment, space, and information system aspects

Figures & data

Figure 1. Projection of global Muslim expenditure on clothing compared to all halal products and the lifestyle sector.

Source: State of The Global Islamic Economy Report (2022).

Table 1. Top exporters to OIC and top fashion importers in OIC.

Top exporters to OIC of fashion US$ Billion (2020 est.)		Top OIC importers of fashion US$ Billion (2020 est.)
China	$13.52	UAE	$5.49
India	$3.00	Saudi Arabia	$3.65
Turkey	$2.17	Turkey	$1.79
Italy	$1.23	Iraq	$1.78
Vietnam	$1.10	Malaysia	$1.54
Bangladesh	$0.85	Indonesia	$1.24
Spain	$0.50	Kazakhstan	$0.97
Hong Kong, China	$0.41	Algeria	$0.86
Indonesia	$0.39	Qatar	$0.85
France	$0.37	Kuwait	$0.71

OIC countries.

Source: State of The Global Islamic Economy Report (2022).

Table 2. The company’s omnichannel warehouse target in fulfilling customer orders in 2020.

No	Month	Fulfillment target (%)	Actual conditions (%)	Gap (%)
1	January	100	90	10
2	February	100	80	20
3	March	100	40	60
4	April	100	40	60
5	May	100	85	15
6	June	100	50	50
7	July	100	60	40
8	August	100	90	10
9	September	100	80	20

Source: Unpublished Warehouse Inventory Records (2021).

Figure 2. Research stages.

Source: The author’s analysis (2021).

Figure 3. Revenue percentage of the four industries in the FMC in 2019–2020.

Source: Unpublished Warehouse Inventory Records (2021).

Figure 4. Product distribution in the omnichannel warehouse by brand.

Source: Unpublished Warehouse Inventory Records (2021).

Table 3. KPIs for the FMC’s omnichannel warehouse.

Variable	Indicator	Explanation	KPI Formula
Labor	Receiving productivity	Employee productivity in the process of receiving fashion products during the five working days a week.	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{products}\hspace{0.17em}\hspace{0.17em}\text{received}\hspace{0.17em}\hspace{0.17em}\text{in}\hspace{0.17em}\hspace{0.17em}\text{the}\hspace{0.17em}\hspace{0.17em}\text{receiving}\hspace{0.17em}\hspace{0.17em}\text{process}}{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{receiving}\hspace{0.17em}\hspace{0.17em}\text{personnel}\hspace{0.17em}\hspace{0.17em}\times \hspace{0.17em}\hspace{0.17em}\text{receiving}\hspace{0.17em}\hspace{0.17em}\text{time}}$
	Product identification productivity	The process of identifying fashion products stored and managed in centralized storage facilities.	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{products}\hspace{0.17em}\hspace{0.17em}\text{identified}\hspace{0.17em}\hspace{0.17em}\text{for}\hspace{0.17em}\hspace{0.17em}\text{ware house}\hspace{0.17em}\hspace{0.17em}\text{management}}{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{personne}\hspace{0.17em}\hspace{0.17em}\text{l in}\hspace{0.17em}\hspace{0.17em}\text{this}\hspace{0.17em}\hspace{0.17em}\text{process}\times \text{putaway}\hspace{0.17em}\hspace{0.17em}\text{time}}$
	Picking productivity	Employee productivity in selecting fashion products that consumers need involves online and offline picking processes.	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{products}\hspace{0.17em}\hspace{0.17em}\text{taken}\hspace{0.17em}\hspace{0.17em}\text{from}\hspace{0.17em}\hspace{0.17em}\text{the ware}\hspace{0.17em}\text{house}}{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{personne l}\hspace{0.17em}\text{in this}\hspace{0.17em}\text{process}\times \text{picking}\hspace{0.17em}\hspace{0.17em}\text{process}\hspace{0.17em}\hspace{0.17em}\text{time}}$
	Labor productivity	Overall workforce performance during a full day of task implementation.	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{products}\hspace{0.17em}\hspace{0.17em}\text{managed}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\text{from}\hspace{0.17em}\hspace{0.17em}\text{picking}\hspace{0.17em}\hspace{0.17em}\text{to shipping}}{\text{Total}\hspace{0.17em}\hspace{0.17em}\text{working}\hspace{0.17em}\hspace{0.17em}\text{hours}}$
	Shipping Productivity	Productivity in the process of delivering fashion products, both via online and offline channels	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of products}\hspace{0.17em}\hspace{0.17em}\text{managed}\hspace{0.17em}\hspace{0.17em}\text{in}\hspace{0.17em}\hspace{0.17em}\text{the}\hspace{0.17em}\hspace{0.17em}\text{shipping}\hspace{0.17em}\hspace{0.17em}\text{process})}{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{personnel}\hspace{0.17em}\hspace{0.17em}\text{in}\hspace{0.17em}\hspace{0.17em}\text{this process}\times \text{shipping}\hspace{0.17em}\hspace{0.17em}\text{process time}}$
Equipment	Receiving productivity	Productivity of tools used in receiving fashion products	$\frac{(\text{Number of products received in the receiving process}}{\text{Number of equipment used}\times \text{receiving time})}$
	Product identification productivity	Calculating the productivity of tools used to identify fashion products	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{products}\hspace{0.17em}\hspace{0.17em}\text{identified}\hspace{0.17em}\hspace{0.17em}\text{for}\hspace{0.17em}\hspace{0.17em}\text{ware house}\hspace{0.17em}\hspace{0.17em}\text{management}}{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{equipment}\hspace{0.17em}\hspace{0.17em}\text{used}\hspace{0.17em}\times \text{p icking}\hspace{0.17em}\hspace{0.17em}\text{time}}$
	Picking productivity	Productivity of tools used in picking fashion products, both offline, such as in stocking physical stores, and online with various orders from consumers and varying quantities and products.	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{products taken}\hspace{0.17em}\hspace{0.17em}\text{from}\hspace{0.17em}\hspace{0.17em}\text{the ware}\hspace{0.17em}\text{house}}{(\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{equipment}\hspace{0.17em}\hspace{0.17em}\text{used}\times \text{picking}\hspace{0.17em}\hspace{0.17em}\text{time}}$
	Shipping productivity	Tool productivity in the fashion product delivery process	$\frac{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{products}\hspace{0.17em}\hspace{0.17em}\text{to}\hspace{0.17em}\hspace{0.17em}\text{be}\hspace{0.17em}\hspace{0.17em}\text{shipped}\hspace{0.17em}\hspace{0.17em}\text{to}\hspace{0.17em}\hspace{0.17em}\text{consumers}}{\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{equipment}\hspace{0.17em}\hspace{0.17em}\text{used}\times \text{shipping}\hspace{0.17em}\hspace{0.17em}\text{process}\hspace{0.17em}\hspace{0.17em}\text{time}}$
Space	Building utilization	Overall building utilization in omnichannel warehouse activities or optimizing building use.	$\frac{(\text{Ware}\hspace{0.17em}\hspace{0.17em}\text{house}\hspace{0.17em}\hspace{0.17em}\text{space}\hspace{0.17em}\hspace{0.17em}\text{used}}{\text{Total}\hspace{0.17em}\hspace{0.17em}\text{ware house}\hspace{0.17em}\hspace{0.17em}\text{space}}\times 100\text{\%}$
	Storage space utilization	Storage space utilization or storage management, whether it is optimal or not.	$\frac{(\text{Storage}\hspace{0.17em}\hspace{0.17em}\text{space}\hspace{0.17em}\hspace{0.17em}\text{used}\hspace{0.17em}\hspace{0.17em}\text{in}\hspace{0.17em}\hspace{0.17em}\text{the ware}\hspace{0.17em}\text{house}}{\text{Total}\hspace{0.17em}\hspace{0.17em}\text{storage}\hspace{0.17em}\hspace{0.17em}\text{space}}\times 100\text{\%}$
	Product placement area	Utilization of staging areas before goods are sent or as a place to display fashion products in the warehouse	$\frac{\text{Area}\hspace{0.17em}\hspace{0.17em}\text{for}\hspace{0.17em}\hspace{0.17em}\text{product}\hspace{0.17em}\hspace{0.17em}\text{placement}\hspace{0.17em}\hspace{0.17em}\text{in}\hspace{0.17em}\hspace{0.17em}\text{the}\hspace{0.17em}\hspace{0.17em}\text{shipping}\hspace{0.17em}\hspace{0.17em}\text{process}\hspace{0.17em}\hspace{0.17em}\text{used}\hspace{0.17em}\hspace{0.17em}\text{in}\hspace{0.17em}\hspace{0.17em}\text{the}\hspace{0.17em}\hspace{0.17em}\text{ware house}}{\text{Total}\hspace{0.17em}\hspace{0.17em}\text{space}}\times 100\%$
	Product turnover	Optimizing fashion products and inventory in the company’s omnichannel warehouse.	$\frac{\hspace{0.17em}\text{Number}\hspace{0.17em}\hspace{0.17em}\text{of}\hspace{0.17em}\hspace{0.17em}\text{items}\hspace{0.17em}\hspace{0.17em}\text{sold}}{\text{Average}\hspace{0.17em}\hspace{0.17em}\text{product}\hspace{0.17em}\hspace{0.17em}\text{stock}\hspace{0.17em}\hspace{0.17em}\text{in}\hspace{0.17em}\hspace{0.17em}\text{the}\hspace{0.17em}\hspace{0.17em}\text{ware WWWWWhouse}}$
	Product dwell time in warehouse	Calculating how many fashion products are sold or managed in a day.	$\frac{\mathit{\text{Number ofproducts}}\hspace{0.17em}\mathit{\text{leaving the}}\hspace{0.17em}\mathit{\text{ware house}}}{\mathit{\text{Operational hours}}\hspace{0.17em}\mathit{\text{of the}}\hspace{0.17em}\mathit{\text{ware house}}}$
	Transportation utilization	Calculating transportation capacity utilization for shipping fashion products	$\frac{\text{Number of item}\hspace{0.17em}\hspace{0.17em}\text{sloaded}\hspace{0.17em}\hspace{0.17em}\text{intovehicles}}{\text{Total capacity}}$
Information system	Warehouse information management system	Measuring the performance of the warehouse information management system in fashion companies, namely the percentage of the warehouse information management system to all warehouse activities.	Overall warehouse optimization with a warehouse management information system

Source: Author’s analysis (2021).

Table 4. Respondents for performance weighting questionnaire completion.

No	Name	Position	Duration of work (years)	Justifications for choosing knowledgeable responders
1	Mr. PD	Head of Warehouse Department	>15	He has been working in the warehousing field for over 15 years and has been with the company since its inception.
2	Mr. DI	Head of Warehouse Department	7	He is one of the individuals who joined the company from the beginning and has been working in the warehouse for 7 years, experiencing various changes and participating in strategic warehouse activities.
3	Mr. DD	Head of Warehouse Department	7	He is one of the high-achieving individuals, which led to him becoming the head of the warehouse department. He can provide detailed information.

Source: Author’s analysis (2021).

Table 5. Weighting for each KPI of the company’s omnichannel warehouse.

Category	Performance indicator	Weight
Labor (0.241)	Receiving productivity	0.053
	Product identification productivity	0.043
	Picking productivity (offline)	0.060
	Picking productivity (online)	0.041
	Labor productivity	0.044
	Shipping productivity	0.046
Equipment (0.169)	Receiving productivity	0.032
	Product identification productivity	0.044
	Picking productivity	0.047
	Shipping productivity	0.043
Space (0.265)	Building utilization	0.032
	Storage space utilization	0.054
	Product placement area	0.043
	Product turnover	0.023
	Product dwell time in warehouse	0.046
	Transportation utilization	0.024
Information system (0.325)	Warehouse information management system	0.325

Source: Author’s analysis (2021).

Table 6. Result of traffic light system aggregation for the KPIs in the company’s omnichannel warehouse.

Category	Performance indicator	Total	Target	Category (%)
Labor	Receiving productivity	41.67 product/day	90	−53.70
	Product identification productivity	31.25 product/day	80	−60.94
	Picking productivity (offline)	23.92 product/day	50	−52.16
	Picking productivity (online)	3.59 product/day	2	79.50
	Labor productivity	2870.47 product/day	2000	43.52
	Shipping productivity	76.55 product/day	50	53.10
Equipment	Receiving productivity	20.83 product/day	35	−40.49
	Product identification productivity	52.42 product/day	70	−25.11
	Picking productivity	71.76 product/day	50	43.52
	Shipping productivity	45.93 product/day	50	−8.14
Space	Building utilization	74%	90%	−17.78
	Storage space utilization	86%	90%	−4.44
	Product placement area	86%	90%	−4.44
	Product turnover	74%	70%	5.71
	Product dwell time in warehouse	2871 unit	2500	14.84
	Transportation utilization	41.34%	80%	−48.33
Information system	Warehouse information management system	80%	80%	0.00

Source: Author’s analysis (2021). Note: the colors in the table indicate the achievement of KPI targets, in which green means the KPI has been achieved, yellow indicates the KPI is nearly achieved, and red signifies the KPI needs immediate improvement as it is far from the target.

Figure 5. An illustration of omnichannel retail in the FMC.

Source: The author’s analysis (2021).

Figure 6. Overview of FMC fashion omnichannel warehouse activities.

Source: The author’s analysis (2021).

Figure 7. Fishbone diagram for issues in the product receiving section of the omnichannel warehouse of the company (2021).

Source: Author’s analysis (2021).

Figure 8. Fishbone diagram for issues in the product identification section by warehouse workforce in the company’s omnichannel (2021).

Source: Author’s analysis (2021).

Figure 9. Fishbone diagram for issues in the offline order picking section of the company’s omnichannel warehouse (2021).

Source: Author’s analysis (2021).

Figure 10. Fishbone diagram for problems in the transport utilization section in the company’s omnichannel warehouse (2021).

Source: Author’s analysis (2021).

Table 7. Current performance measurement of omnichannel warehouse FMC.

Category	Performance indicators
Labor	Workforce productivity in the product picking process
	Number of workplace accidents in the warehouse
	Number of damaged product in the warehouse
	Working productivity in the receiving process
Space	Stock opname activity
	Errors in product location
	Warehouse capacity

Source: Unpublished Warehouse Inventory Records (2021).

Table 8. Comparison between current warehouse performance and proposed omnichannel warehouse performance for the company.

No	Indicators	Current warehouse performance	Proposed warehouse performance
1	Category	Two categories (labor and space)	Four categories (labor, space, equipment, and management information systems)
2	Key performance indicator	Seven KPIs	Sixteen KPIs
3	Calculation	Making use of management perceptions and qualitative data	Using predefined formulas
4	Advantages	Recognized by the business	Performance indicators that are comprehensive, clear, and include precise computations. Fishbone analysis is used to identify issues through analysis.
5	Disadvantages	Inadequate and ambiguous measurement indications	Although the company has some data accessible, the measuring process takes longer than necessary because of the data processing. Additionally, the business still lacks complete mastery over this particular measurement.

Source: The author’s analysis (2021).

State of The Global Islamic Economy Report (2022). Retrieved from https://www.dinarstandard.com/post/state-of-the-global-islamic-economy-report-2022

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Catatan inventarisasi gudang yang tidak dipublikasikan [Unpublished Warehouse Inventory Records] (2021). FMC.

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