Benchmarks achieved in manufacturing industry

Achievable Benchmarks

The following benchmark performances have been achieved for quality, productivity, delivery, agility, purchasing, and production control prerequisites in manufacturing industry. Comparisons are difficult since some industries are inherently better than others for good reasons, however in many cases performance can be improved significantly by following the best practices outlined on this site and the Benchmarking procedures outlined in "Introduction to Benchmarking".

Links to other best practices and training at bottom of page.

Measure	Benchmark (Best we know)	Calculation	Our best project	Where are you?
Quality	25 faults per million produced	Quantity of defects x 10⁶¸ Total	120
Productivity	666,000$ per employee pa	Sales ($)¸ number of employees	£120,000
Production Planning	+/- 2% of planned achievement	Full quantity on the day (Plan verses actual)	3%
Delivery to customers request	98% delivered as requested	This is based on the customer's desired date not the agreed date (which may be later) (See Previous Best Practice 045: OTIF (on time in full)	98%
Demand forecast accuracy	>95%	Accurate quantity and date (based on hits and misses) (See Forecast Accuracy, and Demand Management)	100%
Arrears/overdue sales orders	Zero	Any overdue is a miss	1%
Capacity Planning	+1, -10%	Planned capacity balanced to required capacity	+5%, -10%
MRP schedule adherence	99.5%	% of all work orders complete (full quantity on the day)	97%
Most overdue shop order	<2 days	Past due shop order	3 days
Pick material Shortages from raw materials	<2%	Over due purchase order quantities (less than full quantity on the day)	<2%
Open purchase and shop order accuracy	>95%	At a stock take all orders are real and accurate counted as either accurate or inaccurate (hits & misses)	90%
Shop orders started on time	>99%	% of planned orders started on the planned day	99%
Shop orders completed on time	>98%	% of planned completions	98%
Engineering data
Bill of Material Accuracy	>98%	All single level B.O.M.s are audited at build time and are either completely right or wrong	>98%
Routing Data accuracy	>98%	All planned routes audited against actual and are completely right or wrong	Not available (See note 1)
Engineering Change	>95% on time	All engineering changes implemented to schedule	85%
Purchasing
Raw material availability (No shortages)	98% on time	Picking or Kanban shortage to production line	94%
Supplier on time	>95%	Full quantity on the day, with perfect quality	90%
Overdue purchase orders	< 2 days	Full quantity, perfect quality	Not available (see note 2)
Inventory record accuracy	>95% hits	Bin quantity accurate to 2% (to system) when counted. Within 2% is a hit. Outside 2% is a miss.	94%
Flexibility
Lead-time	< 2 days	Lead-time from order to delivery of complex make to order assembly	5 days
Changeover time	7.9 minutes for large press die	End of one batch to set up and make first satisfactory component of new batch	11 minutes for large complex former
Innovation Ideas raised	>10	Ideas raised per person per week. (Not all of these will make it.)	5
Ideas implemented	>3	Ideas implemented per week per person	2
Stock Turns	160 (one and a half days stock) (See note 3)	The ratio of raw material issues to total stock holding at material costs.	20 (See note 3)
		The UK Department of Trade and Industry also recommend the following further measures and they are included for completeness rather than because we believe in them:
Overall Equipment Effectiveness	Not available	Availability % x Productivity % x Quality %	We do not use this measure (See note 4)
Floor Space Utilisation	Not available	Sales revenue per square metre of floor space	We do not use this measure (See note 5)

Note 1: We do not view this as too important for planning and scheduling, or costing, and is only important for routing work in non cellular factories. Although it is often important for specifying the required processing, for quality purposes and product recall. This will be covered in a future article.

Note 2: We tend to use raw material line shortages since this measures overall availability to where the items are needed and includes direct line feed methods and raw material stores efficiency.

Note 3: It is difficult to provide outside industry comparisons for stock turn, except it is possible to quote some examples for particular industries:

Automotive component manufacturer	14 is the best we have achieved in high mix situations using MRP techniques alone
	160 refers to Kanban in an continuous automotive situation
FMCG's	20 is the best we have achieved in lower mix situations of assemblies using Kanban techniques.
Aerospace	16 is the best we have achieved in high mix situations using Kanban systems.

Note 4. We do not recommend the use of Overall Machine Effectiveness OME / OEE (See Previous Technique of the Week 006: RAP (Why OEE / OME is for the birds) because we feel it is meaningless for any resource other than the bottleneck. We also do not recommend composite measures such as this because it does not help in problem solving.

Note 5. In most of our work floor space savings may be an objective. However ongoing measurement is unlikely to influence this. These changes can only be brought about from major change programmes, which might include:

Cellular Manufacturing (See "Organisational Redesign")
Flexibility Changes (See "Agile Manufacturing")
Control systems changes such as Kanban, Participative Sales and Operations Planning etc.

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Other articles mentioned in this document include:

Introduction to Benchmarking

Demand Management

Organisational Redesign

Kanban

Forecast Accuracy

Participative Sales and Operations Planning

Previous Technique of the Week 007: RAP (Why OEE / OME is for the birds

Previous Best Practice of the Week 045: OTIF (on time in full)

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