Warehouse Resourcing and Costs: Comprehensive Notes
Part Four: Resourcing a Warehouse
Introduction: The chapter focuses on determining the required resources for efficient warehouse operation, categorized into resources driven by processing activities and those determined by other factors.
Processing Activities
Processing activities involve handling products and generate resource multiples, such as receiving products.
Example: Put-away of pallets to racked storage.
Units measured: Pallets over a time period.
Work rate (productivity): Time taken to identify, collect, transport, lift a pallet into storage, confirm put-away (barcode scan), and return to the start location.
Figure 11.1: Put-away time illustration.
Table 11.1: Task breakdown example.
Activity Description: Put-away in wide aisle racking, drive-in racking, and pick locations.
Daily volume, productivity standard, hours required, MHE type, and other equipment are specified for each activity.
The time for a single put-away cycle can be expressed as pallets per hour or minutes per pallet.
Dividing the activity level by the productivity rate yields the number of hours for the task.
Example Calculation for Drive-in Racking: 300 pallets ÷ 16 pallets per hour = 18.75 hours.
This generates 18.75 worked operative hours and 18.75 used reach truck hours.
If voice technology is used, 18.75 hours of voice terminal use is generated.
A resource model requires balancing task lines for every work element and recognizing interdependent elements.
Direct Put-away to Pick Face: Product goes directly to the pick face upon receipt.
The reach truck driver includes this in their daily work.
Alternatively, a second operative could replenish the pick face.
Table 11.2: Task breakdown, version 2.
Includes delivering pallets to the aisle front and replenishing the pick face.
Adds a second unit of measure (cartons) and equipment (powered pallet truck, hand-held barcode scanner).
Productivity Rate: A key element in the resource budget.
Quantitative benchmarks offer useful comparisons, but warehouses vary.
Productivity rates are driven by multiple factors.
Establishing Budget Productivity Rates
Synthesis: Composite construction of productivity rates from work element components.
Work Study: Using an approved work study engineer and work measurement techniques.
Historical Comparison: Identifying productivity levels in existing operations and factoring in changes.
Historical comparison is the most accessible option, relating to an existing work profile.
Key drivers: Hit rates, order composition, etc.
If productivity improvement is a key driver, build from the existing process to identify improvements.
Consider the size of the new warehouse and potential travel time increases.
Changes in equipment affect productivities.
Compare with available productivity benchmarks and supplier data.
Review productivity rates in detail to confirm assumptions and build confidence.
Use techniques such as simulation where congestion is a factor.
Aim of a resource budget: Set resource levels and feed into the financial budget for cost forecasting.
Consider other applications: Managing ongoing operations, activity costing, or constructing charging mechanisms.
A rule of thumb is that when over 80% of total time can be calculated by quantifiable activities, further model development may not be justifiable (for basic warehousing operations).
If the budget generates data for costing or charging, a higher percentage may be required.
Core Processes: Receiving, put-away, retrieval, picking, replenishment, and despatch.
These account for over 80% of handling (touch points) and mechanical handling equipment use.
In a manual warehouse, case picking is the largest component, often exceeding 50% of direct man-hours.
Modeling Variations in Demand
Demand varies at different times, requiring modeling to understand resource requirement changes.
Start with an averaged figure (average day/week) or a typical day/week.
Profiles from previous data or existing trading patterns provide a good indication.
Model 'peak' activity alongside 'average' activity to account for prolonged peaks from seasonal products.
Example: Warehouse receiving palletized product on side-loaded vehicles and loose-loaded product in containers.
Despatches: Palletized on tailgate-loaded vehicles.
Sub-operations: Value-add zone and unit pick-and-pack for internet shopping orders.
Value Add 1: Takes from stock, converts product, and returns it to stock.
Value Add 2: Stand-alone business segment where product is handed over as a specific pick.
Table 11.3: Details main warehouse activities, productivities, and volumes for average and peak periods.
Establish the relationship between modeling data and the budget's total volume.
Budget period: One year.
A simple average day multiplied by the number of working days should equal the annual total.
Variance in demands comes from seasonal variations, weekly variations from sales patterns, and daily variations in order placement.
Modeling addresses variations: Average and peak provide for variation in activity levels.
Consider 'low' period (intake and despatch both less than average) and 'high' period (build towards peak).
Extrapolate levels from average and peak to maintain different profiles in the data.
Reflect different intake and despatch activity levels between periods.
'Low' period: Bigger decrease in despatch than intake, signifying stock build.
'High/Peak': Opposite applies.
'Peak' already displays profile changes in value-add operations.
Net result: Resource requirements reflect changing business demands, improving resource level decisions.
Peaks and troughs bring resource changes (overtime, equipment hire, etc.).
Insufficient work may occur during quieter periods.
Example defines four activity levels: Low, average, high, and peak.
'Average': 24 weeks.
'Low': 18 weeks (including holiday periods).
'High' and 'Peak': Each accounting for five weeks.
Cross-check inputs to ensure total budget activity summed across the budget period equals anticipated annual activity.
Example: Total working days: 265 (five public holidays not worked, 10 weeks have a sixth day).
Daily Activity Variance
Profiles show different activity levels on different days of the week.
Businesses serving fast-moving retail outlets exhibit demand patterns reflecting purchasing behavior.
Receipt of goods follows a different profile from despatch.
Determine different daily profiles for different aspects of the warehouse operation.
Example: Split operations into palletized receipt, loose receipt, despatch, and other activities.
Palletized receipt may be determined by production running times.
Loose receipt reflects shipping and container transfer.
Figure 11.2 Graphic showing average and peak for intake and despatch.
Table 11.4 Daily activity levels for value-add operations.
Apply variance factors to the core resource model.
Aim: gain an idea of overall requirements to set resource levels.
'Low' is scaled from 'average', and 'high' is scaled from 'peak' to reflect variances.
Possible to vary profiles and productivity rates for different periods (e.g., case sizes vary).
Productivity differences can occur during different shifts (night and day).
Increase complexity of resource or budget model requiring care.
Table 11.5 Period and daily variations (shows complete details for average and peak only).
Illustrates varying resource requirements through the year.
For main warehousing, average daily requirement is 391.5 hours (direct labor).
Varies between 365.8 and 422.2 during the week.
Peak average rises to 453.3 hours, peak daily requirement of 505.1 hours.
Peak days are around 18% busier than average.
The weekly requirement rises from 1957.4 hours to 2719.8 hours (approximately 40% increase).
'High' period is a step change to 'peak', 'low' identifies requirements below average equivalent to six full-time operatives.
Similar tables can be extracted for individual elements or equipment requirements.
Key Concept
Demand for resources varies with time.
Determine actual resource levels required.
This example features daily despatches, picking and despatch focused on afternoons and evenings.
Intake is biased to mornings using loading areas for later despatch.
The workload justifies a two-shift operation.
Equipment is specific leading to consideration of daily operating hours or task allocation to time windows.
Tasks are allocated by shift (splitting into shorter time windows may be appropriate).
Critical requirement is likely on the busiest day and is used to determine equipment needs.
Hours are spread between shifts and requirements developed for numbers required per shift.
Highlights manning requirements during the day.
Table 11.6 Allocation of hours and equipment by shifts on average and peak Day 4.
Equipment is calculated by taking the maximum requirement in one shift, dividing by number of worked hours (after break time) and rounding up.
Generates estimates for total requirements/maximum requirements during budget period.
These are quantities for actual working resources; excludes factors such as availability (planned or unplanned).
Determine downtime and the balance of fixed and flexible resource for the budget year.
an extra day at peak periods effectively adds 20% availability to equipment, but not necessarily labor where weekly worked hours will be a constraint.
Some equipment may not be readily available for short-term hire and the operation may need to resource it for peak demand.
When calculating resource levels there are no definitive rules, compare alternative scenarios via modeling techniques.
Value needs to be given to repair and maintenance levels of equipment, absence, premium time costs and temporary labour costs.
For established operations, factoring may be included in the financial budget.
A contingency may be factored in for unforeseen circumstances.
Complicated working patterns or variable workday length is proposed complicate process.
Table 11.7 Labour hours calculations.
Five-day working is assumed during average periods, five days from six during peak periods.
Hours required per day are taken as previously calculated.
Estimate number of FTEs, contingency is added, and factor for non-availability of labour (holiday, sickness, training).
Lower block allows for resources including temporary and overtime.
Manual input generates hours available at base rate, using overtime and temporary labor.
Idle or unused time in quietest periods is estimated.
Contributes a reduced productivity standard (work per attended hour).
Contribution from each activity period is produced and summarized.
Weighted hours are calculated, costing overtime and temporary hours as a factor of a paid base hour, including paid time for absence.
Figure 11.3 Different levels of permanent resource.
Graph illustrating impact on idle hours, overtime, and temporary staff costs.
The optimal number is example is 57.
Not necessary/appropriate for all resource types; the value-add operations illustrate this.
First operation (bundling and relabeling) is a series of individual jobs (broad estimate).
More appropriate to have a small core of staff and use temporary labor for individual jobs.
Second operation (Value Add 2) has more consistency, and may use part-time employees (supplemented by temporary resource).
Other Resources
Other resource requirements are not driven by processing activity (e.g., clerical, administrative, managerial staff).
There may be choices between direct provision and bought-in services.
Touch-labor modelling forecasts activity (volume, numbers, timings), informing judgments of levels of such resources.
Operations office requires manning while the operation is active; personnel may vary by activity type.
Number of orders, type of paperwork (import/export documentation) influence choice, and a key element is the nature of the IT systems employed and the levels of manual intervention envisaged.
A voice picking operation should require less intervention than a paper-based operation.
Consider which functions are the responsibility of the warehouse.
The scale of an operation will drive the management structure and functional responsibility.
Reference to historical arrangements is a starting point.
First line management may be incorporated as working supervisors or shared with team leaders.
Resource modeling generates projected usage data to assist in the procurement process for new MHE, where lease/rental costs vary with use.
Daily hours of use for equipment will help determine spare battery requirements.
Suppliers also help advise on equipment hire during peak periods.
Part Five: Warehouse Costs
Summary and Conclusion
The resource model is built to use data in financial budget and monitor resource requirements.
Productivity standards can be compared with achievement and adjusted.
The model can assist in estimating prices for goods and services and calculate resources for specific operations.
“Every dollar of cost (or expense) that is cut falls directly to the bottom line.”
The cost of operating a warehouse averages between 1 and 5% of total sales.
Warehouse managers require knowledge of costs and cost drivers to reduce costs and produce customer service.
Managers are expected to contribute to the budget and reassess the resource and cost budget.
This chapter will assist managers in producing budgets, calculating ROI for projects, and using information for decision-making.
The chapter also compares traditional and activity-based costing and types of charging models.
Types of Costs
Associated with a warehouse operation:
*Space costs: rent/leasing costs, insurance, rates, utility costs, fixtures and fittings depreciation, racking depreciation, refrigeration plant depreciation, repairs and maintenance, cleaning, security, other building equipment depreciation, and waste disposal.
*Direct labor costs (fixed): warehouse operators wages including on-costs, personnel insurance, safety wear (PPE), welfare, and training.
*Indirect labor costs (fixed): warehouse management, supervisors, and administrators wages including on-costs, insurance, safety wear (PPE), welfare, and training.
*Labor costs (variable): overtime and bonuses.
*Equipment costs (fixed): depreciation/lease costs/rental costs.
*Equipment costs (variable): running costs, packaging, pallets, and stretch wrap.
*Overhead costs (management, finance, human resources, IT, and administration): salaries and on-costs, company cars and running costs, office equipment and furniture depreciation/lease/rental costs, and information technology costs (hardware and software).
Overhead costs (sales and marketing): salaries and on-costs; company cars and running costs; and marketing spend.
Miscellaneous costs: communication costs, postage, bank charges and interest payments, funding costs/cost of finance, insurance, and legal and professional fees
Building Costs to Produce a Total Warehouse Cost
Employer’s social contributions and non-wage costs are an element. Third-party logistics companies can add an element of profit. Models can be used in conjunction with resource models to calculate activity rates.
Return on Investment
Formula is:
During a voice picking trial, a client calculated their ROI was 25.4% in the first year. (£86,400 – £68,900) ÷ £68,900 × 100
Payback period = £68,900 ÷ £86,400 × 12 months = 9.6 months.