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W A R E H O U S E P E R F O R M A N C E M E A S U R E S

C H A P T E R S 1 4 - 1 5

Warehouse and Distribution

Science

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C H A P T E R 1 4

Activity Profiling

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ABC Analysis

80-20 Rule

Ranking by $-volume is financial

Ranking by labor or space needs is operational

Often find surprises in examining warehouse activity

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ABC Profiling

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Statistical Analysis

Data Needs

Sku data

Order data

Warehouse location data

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Sku data

May reside in different databases

When in doubt get it all

ID, description, product family, address of storage

locations, dimensions, packing, date introduced,maximum inventory level

Sku data

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Order Data

Order ID, Skus, customer, special handling,date/time order picked up, quantity shipped

Order data is financial information and usually

accurate, but Not necessarily operations focused, e.g. date ordered,

not date picked

Validate with lines shipped each day

Very large quantity of data

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Warehouse Layout & Location

Least standardized

Blueprints, sketches, CAD files

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Issues with Profiling

Getting the data

Data mining

Discrepancies in the data

Validating Interpreting patterns

Beware of small numbers

Beware of sample biases E. TuftesThe Visual Display of Quantitative

Information

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C H A P T E R 1 5

Benchmarking

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Benchmarking

What to measure?

With whom to compare?

How to improve?

Compare a warehouse with similar warehouses. Examine its facilities and processes to adopt if better

performing.

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Performance Measures

Units of output achieved/Units of input required

Operating cost (cost as % of sales)

Operating productivity (picklines, orders, etc. per

person hour) Response time (order-cycle time)

Order accuracy (% of shipments with returns)

Advantages/disadvantages of these measures?

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Benchmarking

Comparing warehouse with other warehouses

Internally or externally

Ratio-based benchmarking

Aggregate benchmarking Data Envelop Analysis

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Efficient Frontier

Convex combination

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Regression Line

Pick rates at

similar

warehouses

Fit a regression line forsize versus averagepicks per person-hour.

Generally, larger

warehouses are lessefficient

Larger warehouses havemore travel time

Figure 15.5

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Conclusions of GT Study

There was no difference between union and non-union warehouses.

Warehouses with low capital investment tended to

outperform those with high capital investment.Inflexible automation.

Smaller warehouses tended to outperform largerwarehouses.

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Are smaller warehouses more efficient?

Pure size hurts efficiency

Size requires process changes

E.g. Walmart

Changed the smallest quantity handled, from eaches tocartons, etc.

Utilize cross-docking to eliminate double handling.