Lehigh Steel

Harvard Business School Case: 9-198-085

Instructor Prof. K. M. Padmanabhan

12/16/2011

Submitted By Section E, Group 8 Aravind Ganesan 2011PGP448 Gadkhel Rohit 2011PGP629 Gokulnath R 2011PGP638 Kartik Shrivastava 2011PGP685 Sumit Prakash 2011PGP907 Upasana Mukherjee 2011PGP922 Vemb V 2011PGP932

The task is to evaluate the best costing alternative for Lehigh steel. For this, an improvised

costing system is developed which overcomes the assumptions of ABC and TOC costing and

the optimum product mix for Lehigh Steel is calculated using the same

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Executive Summary

Lehigh Steel is a manufacturer of speciality steels for high strength, high use applications. Its

financial performance has generally trended wit but outperformed the industry as a whole.

Following the general recessionary trend of the market, Lehigh Steel reported record losses in

1991 after posting record profits in 1988. This had led to an increasing need to rationalizing

Lehigh Steel‟s product mix.

Traditionally, Lehigh Steel has followed Standard Cost Method for cost accounting. Jack

Clark, CFO of Lehigh Steel has given Bob Hall the task of implementing Activity Based

Costing at Lehigh Steel. Mark Edwards, Director of Operations and MIS explored the

implementation of Theory of Constrains (TOC) accounting for Lehigh Steel.

The task is to evaluate the best costing alternative for Lehigh steel. For this, an improvised

costing system is developed which overcomes the assumptions of ABC and TOC costing and

the optimum product mix for Lehigh Steel is calculated using the same.

Situation Analysis

Company Analysis

Founded in 1913, Lehigh Steel enjoyed a niche position as a manufacturer of speciality steels

for high strength, high use applications. Products included high-speed, tool and die,

structural, high temperature, corrosion-resistant and bearing steels, available in a wide range

of grades in a variety of shapes and finishes. Its markets included aerospace, tooling, medical,

energy and other performance industries. Lehigh Steel‟s premium market position came from

its superior ability to integrate clean materials with precision processing to produce high

quality products which were often customized for specific applications, and bundled with

metallurgy and other technical services. It also operated a small distribution division which

served certain market segments by offering a broad product line comprising of products from

multiple manufacturers.

Lehigh Steel was acquired by The Palmer Company in 1975. The Palmer Company was a

global manufacturer of bearings and alloy steels with revenues of $1.6 billion in 1992. Palmer

believed that long-term specialization developed knowledge and innovation, the true source

of competitive advantage. Palmer‟s corporate objective was to “increase penetration in

markets providing long-term profit opportunities” by taking “a long-term view in decision

making by strategically managing (the) business,” and “emphasizing the fundamental

operating principles of quality, cost, investment usage and timelines.” The acquisition of

Lehigh Steel gave Palmer speciality in Continuous Rolling Mill (CRM) that could convert

steel intermediate shapes to wire for Palmer‟s bearing rollers.

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Lehigh operated under a matrix organization structure. Reporting to the company president

were the General Managers of Primary Operations, Finishing Operations, and Marketing and

Technology; Vice President of Sales; Director of Operations Planning and MIS; and CFO.

Their performance was measured by product contribution margin calculated using standard

costs: revenue less materials, direct labour, and direct manufacturing costs such as utilities

and maintenance; other overhead was considered beyond their control.

Lehigh had 7 product lines – Alloy, Bearing, Conversion, Corrosion, Die Steel, High Speed

and high Temp. Out of this Alloy, Die Steel and High Speed comprised 70% of the sales,

Lehigh also carried niche product lines – Bearing, Corrosion and High Temp are – whose

volume fluctuated with market conditions.

Conversion involved the processing of non-Lehigh owned material on equipment such as the

PFF or the CRM that was not economical for some products to own. Conversion was subtly

complex, as the breadth of the end customer‟s product line translated into multiple rolling

specifications, and multiple setups.

Industry Analysis

Structure

Speciality steel comprised roughly 10% of the total US steel industry, and like other high-

tech, speciality industries, and offered growth and profit opportunities to firms who targeted

specific applications and developed unique technical competencies. Speciality steel was

characterized by variations in metallic steel composition and manufacturing processing which

enhanced the properties of basic carbon steel.

Steel products were defined by several attributes which determined the product application

and defined quality. Grade described the metallic (chemical) composition of the steel, or the

elements added to the basic recipe of iron and carbon to create the desired properties. Product

described the shape of the product, including semi-finished shapes (blooms, billets and bars)

and finished shapes (wires and coils). Surface finish described the smoothness and polish that

could be applied to the material‟s surface to enhance presentation. Size described the

latitudinal and longitudinal dimensions of the product. Structural quality described the

absence of breaks in the inner metallic structure. Surface quality described the absence of

cracks or seams on the surface. Because specific applications called for specific attributes,

many products were customized along one or more attributes for the customer. However, of

all attributes, customers valued most the grade, which determined product performance.

Producers typically focussed on a portfolio of product shapes within a single segment to

carve niches in a broad industry. This focus strategy protected capital investments in a capital

intensive industry. The industry was capital intensive because (i) lumpy and expensive

capacity additions, (ii) cost structure was significantly changed only by generational,

expensive new technologies (like Lehigh‟s Precision Forging Facility (PFF)) and finally, (iii)

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knowledge work performed by metallurgists and other technical specialists was a significant

portion of the cost structure.

Economics and „focus‟ also divided the industry into manufacturers and finishers/developers.

Manufacturers were the ones who melted, refined, moulded and rolled steel into basic shapes.

Finishers/Distributers were the ones who broke semi-finished steel orders and shapes down to

specific products for metalworking shops and original equipment manufacturers (OEMs).

Manufacturers and Distributers worked closely together, often as separate divisions within a

firm.

Conduct and Performance

Maintaining high standards of product quality while keeping costs competitive were essential

to compete in the specialty steel industry. Quality differences between manufacturers meant

that products were not perfectly substitutable. Differentiation also benefitted buyers, who

enjoyed a range of choices within a product category, and could pay for the precise version of

quality required. Technical services also differentiated suppliers while benefiting buyers, and

were becoming increasingly important. Over time customer had become sophisticated about

the value of the product, and the price they would pay for it.

Producers of speciality steel were small, fragmented price takers in the market dominated by

powerful, sophisticated customers. Market share could be bought or sold by pricing slightly

below or above the market price. Niches provided some protection for the providers.

Reputation for excellent quality and technical services also earned producers some price

premium. Manufacturers exited themselves quietly out of non-profitable products, sourcing

those critical to their product lines from other firms. Cost, therefore, was a significant

competitive weapon in determining share and profits.

To manage utilization rates and unit costs, producers sought volume and long production

runs. When demand was strong, producers would select high volume orders which allowed

continuous operations at high setup time workstations. In low demand times, firms chase low

volume niche businesses to fill plants, rationalizing the poor margins as volume that would

contribute against fixed-cost while adding little variable cost.

Steel performance trended with the economy. Industry profitability fluctuated widely, ranging

from -16.7% to 5% in the late 1980s. Industry capacity utilization peaked in 1988 at 89.2%,

plummeted to 74.1% in 1991, and recovered partially to 82.2% in 1992.

Problem Statement Industry wisdom stated that steel profits were a function of prices, costs and volume. Volume

was available at market price, though in form of niche specialities and small orders, but

virtually disappeared at premium prices. Costs failed to decline with price or volume:

shrinking operating rates drove up unit costs, and broader customer bases and product lines

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bred complexity and increased labour resources, particularly in scheduling. Profit could not

be generated by simply working the traditional levers of price, cost or volume.

In 1992, Lehigh CFO Jack Clark hired Bob Hall to implement activity based costing at

Lehigh. On the other hand, Mark Edwards, Director of Operations Planning and MIS

explored Theory of Constraints (TOC) based costing system for Lehigh Steel.

Clark has to base his costing decision based on the reports of these two costing systems as

well as the outcome of standard costing system.

Evaluation of Alternatives

Standard Costing

Lehigh Steel along with the rest of steel industry has followed standard costing method. But

this method did not seem completely accurate as the company showed record profits in 1988

and record losses in 1991. In this costing method, profits from steel sales were a function of

prices, costs and volume. Product weight (pounds) was taken as the primary cost driver for

the measurement of standard cost, which included materials, labour, direct manufacturing

expense and overhead cost categories. Direct manufacturing costs such as maintenance and

utilities were allocated to products based on machine hours. Indirect manufacturing and

administrative costs were allocated to products on the basis of pounds produced, since weight

was assumed to be the primary driver of resource consumption.

From the context of this strategy, Alloys was the most profitable product and was extensively

promoted by the company. In spite of this, Lehigh witnessed record losses in 1991. The

calculation of costs by standard costing is shown below.

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Standard Costing

Standard Cost Alloy :

Conversion

: Die steel : Die steel: High speed:

($/lb) Condition

round Roller wire

Chipper

knife

Round

bar

Machine

coil

Price 2.31 0.77 1.02 0.93 2.33

Materials 0.54 0 0.12 0.21 1.58

Direct labour 0.29 0.07 0.28 0.18 0.14

Direct

manufacturin

g expense

0.24 0.06 0.23 0.16 0.12

Contribution

margin ($) 1.24 0.64 0.39 0.38 0.49

Contribution

margin (%) 53.70% 83.10% 38.20% 40.90% 21%

Total

Contribution(

$)

593562 1332188 941187 2545119 1239970

Manufacturin

g & Admn.

Overhead

0.64 0.64 0.64 0.64 0.64

Operating

profit ($) 0.6 0 -0.25 -0.26 -0.15

Operating

profit (%) 26% 0% -24.50% -28% -6.40%

Total

Operating

profit ($)

287207 0 -603325 -1741397 -379583

Total Profit($) -$2,437,098

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Activity-Based Costing

In 1992, Lehigh CFO Jack Clark decided to try out alternatives to standard costing. In order

to find the correct product mix to maintain profitability even in recessionary periods, he

decided to implement Activity Based Costing in the company. As a manufacturer of

thousands of SKUs that shared the same production processes,, Lehigh was ideal for

implementing ABC.

Implementing ABC was a 2-stage process, (i) identifying activates and their cost-drivers and

(ii) allocating activities to products and customers using appropriate cost drivers. The results

of implementing ABC were unexpected: Company profitability was found to be highly

dependent on high volumes of High Speed and Die Steel sales which was a departure from

their earlier stance of making more Alloys.

However, there were some results which were counter-intuitive. For example, high temps

showed a similar profitability to high speeds, even though high speeds could be processed

across the CRM at a 6 times faster rate.

Lehigh Activity Cost Pools

Activity Driver Driver

volume Amount ($) Rate

Cumulative

Rate

Melting - Dep Melt machine

minutes 51,45,632 21,39,865 0.415860481

Melting -

Maintenance

Melt machine

minutes 51,45,632 975130 0.189506362 1.001134943

Melting -

utilities

Melt machine

minutes 51,45,632 2036477 0.3957681

Refining - Dep

Refine

machine

minutes

56,91,042 1711892 0.300804668

Refining -

Main

Refine

machine

minutes

56,91,042 780104 0.137075776 0.744599495

Refining -

Utilities

Refine

machine

minutes

56,91,042 1745551 0.306719051

Molding - Dep Mold machine

minutes 42,26,965 427973 0.101248295

Molding -

Main

Mold machine

minutes 42,26,965 390052 0.092277083 0.262351356

Molding -

Utilities

Mold machine

minutes 42,26,965 290925 0.068825978

Rolling - Dep Roll machine

minutes 82,58,382 2995811 0.362760042

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Rolling - Main Roll machine

minutes 82,58,382 975130 0.118077609 0.586521306

Rolling -

Utilities

Roll machine

minutes 82,58,382 872776 0.105683656

Finishing -

Dep

Finish

machine

minutes

40,57,311 1283919 0.316445794

Finishing -

Main

Finish

machine

minutes

40,57,311 780104 0.192271187 0.72382891

Finishing -

Utilities

Finish

machine

minutes

40,57,311 872776 0.21511193

G & A Pounds 5,02,99,420 5400955 0.107376089 0.107376089

Mat Handling

& Setup orders 57,147 4936068 86.37492782 86.37492782

Order

Processing orders 57,147 3953709 69.1848916 69.1848916

Production

Planning orders 57,147 3339500 58.43701332 58.43701332

Technical

Support SKUs 6,642 5766579 868.199187 868.199187

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ABC Costing

ABC Cost Alloy :

Conversio

n: Die steel : Die steel: High speed:

($/lb)

Condition

round Roller wire

Chipper

knife

Round

bar

Machine

coil

Price($) 2.310 0.770 1.020 0.930 2.330

Materials($) 0.540 0.000 0.120 0.210 1.580

Direct labor($) 0.290 0.070 0.280 0.180 0.140

Contribution

Margin($) 1.480 0.700 0.620 0.540 0.610

Manufacturing

expense:

Melting 0.200 0.000 0.090 0.090 0.090

Refining 0.156 0.000 0.074 0.074 0.074

Molding 0.031 0.000 0.018 0.021 0.018

Rolling 0.059 0.088 0.194 0.053 0.018

Finishing 0.043 0.014 0.051 0.058 0.036

G&A 0.107 0.107 0.107 0.107 0.107

Mat handing, setup 0.173 0.173 0.115 0.043 0.035

Order processing 0.138 0.138 0.092 0.035 0.028

Production planning 0.117 0.117 0.078 0.029 0.023

Tech support 0.564 0.197 0.150 0.022 0.035

Total 1.589 0.835 0.970 0.533 0.465

Operating Profit -0.109 -0.135 -0.350 0.007 0.145

Operating profit % -4.738 -17.546 -34.339 0.761 6.238

Total Operating profit -52386.495

-

281218.895 -845267.107 47427.417 367778.317

Total Profit = - $763666.7616

Theory of Constraints

Another thing that caught the management‟s attention (apart from ABC results) was that

despite the decrease in demands, Lehigh‟s lead times had not decreased comparably. Excess

material could be found on the shop floor despite the reduced process batches. The Theory of

Constraints argued that in the short run the only costs that were variable were the operating

costs and advocated that management should focus only on the constraint. To increase the

throughput through the constraint was to increase throughput for the entire system. Time was

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the only resource that mattered in TOC but time was not typically a factor used in Lehigh‟s

decision-making. The key to profitability was to send only the most profitable products

(higher gross margins) through the constraint. The results were again very different from

what was expected.

TOC Costing

TOC Cost Alloy : Conversion : Die steel : Die steel: High

speed:

($/lb) Condition

round Roller wire

Chipper

knife

Round

bar

Machine

coil

Price 2.31 0.77 1.02 0.93 2.33

Materials 0.54 0 0.12 0.21 1.58

Throughput

Contribution ($) 1.77 0.77 0.9 0.72 0.75

Time taken in

Bottleneck stage

(mins)

0.21 0.15 0.33 0.1 0.1

Throughput/min 8 5 3 7 8

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Different Assumptions between Standard Costing, ABC

and TOC Costing

The main assumptions that go in calculation of costs in case of standard costing, ABC and

TOC costing are shown below

Standard Costing ABC TOC

1 Cost Driver

Weight is taken as

primary cost

driver

All indirect costs

are related to the

product through a

causal

relationship, so the

cost drivers are

different for

different activities

Time taken by a process

is the main cost driver

2 Time orientation Independent of

Time

Long term

Oriented Short Term Oriented

3 Application

Major Component

of Cost is direct

Variable Cost

Major Component

of Cost is

Overhead Cost

The overhead costs are

fixed and cannot be

altered over given time

duration

4 Linearity of

Variable Costs

Cost pool not

homogeneous

Cost pools are

homogeneous

Only matrial costs

included, hence only

economies/diseconomies

of scale in procurement

may be involved

Alternate Costing Strategy Both ABC and TOC have some disadvantages when it comes to deciding the product mix. In

case of ABC the product mix was decided on the basis of profitability of each product and the

production of the most profitable product was maximized. This ABC completely ignores the

opportunity cost of utilizing the bottleneck.

TOC on the other hand takes into consideration the effect of the most critical resource in

finalizing the product mix. This system maximises the product which gives maximum profit

on utilizing one unit of the critical resource. Hence TOC is focused in planning the product

mix in synergy with the operating efficiency of the system.

However, selecting ABC or TOC based costing is dependent upon the context in which the

system is operating. The effectiveness of selecting a particular process is dependent upon the

assumptions made about the relevance of labour and overhead for selecting an optimal

product mix.

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Time Horizon of using ABC and TOC

The TOC bas should costing is recommended to be used in the short run as in the short run, it

may be difficult for management to control or influence the labour and manufacturing

overhead costs. On the other hand, ABC can be used in the long run as in a longer time

period the manufacturing overheads and labour costs can be better controlled by the

management. However, there may be certain circumstances when management has control

over labour and manufacturing overhead in the short run or some situations when it cannot

control these costs even over an extended time period, the suggestion that the TOC should be

used in the short run and ABC should be used in the long term may be misleading. In practice

there will be situations where the management will not have either complete or zero control

over these costs and hence the cost will be a function of that particular context.

It is evident that time is not a factor which determines the use of ABC or TOC based costing

for product mix decisions. The ABC gives a product mix based on the resources used in

production. Thus management has the liberty to redeploy these resources or completely stop

the use of these resources depending on its interpretation of ABC results. Unused or excess

capacity lead to suboptimal product mix and consequently profitability is affected.

Conversely, the TOC system leads to an optimal product mix based on the labour and

overhead resources supplied to production. If unused resources can be redeployed to

productive uses elsewhere within the firm or terminated, the product mix selected with the

TOC may be suboptimal and hence will lead to reduced profitability. Thus, management's

control over labour and manufacturing resources determines when the TOC and ABC lead to

an optimal product mix. Management's control over labour and overhead normally depends

upon the time horizon selected. For example, the shorter the time horizon, the less control

management generally has over labour and overhead resources. On the other hand, the longer

the time horizon selected, the more control management has, or has the ability to acquire,

over labour and overhead. Thus managers have to understand the context of the situation in

order to determine when the TOC and ABC will lead to optimal product-mix decisions rather

than focusing on the time horizon alone.

The Effect of Management’s Degree of Control over Resources2

TOC and ABC are ideally implemented in extreme circumstances. The management has

either complete or no control over labour and overhead resources. The ABC system assumes

that the management has complete control over labour and the overhead resources and they

will vary according to the quantity of products produced. On the other hand the TOC costing

system assumes that the management has no control on the quantity of supplied resources. So

no matter what is the demand in the market the operating cost of producing the products

barring the direct material cost will remain fixed.

But in real life this is not the case. A proportion of the allocated resources always remain

under the control of the management and another portion remains uncontrollable. Thus there

will be a minimum operating cost that the firm will have to bear regardless of the amount of

production but beyond that the operating costs are variable with the amount of the

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production. The production capacity of the system depends on the system bottleneck and

hence the capacity utilized of the non-bottleneck process depends upon the bottleneck

process. The important distinction between the costing structure of the ABC and TOC system

is the allocation of the costs associated with non-bottleneck processes.

According to the ABC system,

,

( )i i i j ij i

i i j

Z p c X s q X (1)

According to the TOC system,

( )i i i j j

i j

Z p c X s Q (2)

Where pi= Price of the ith

product

ci = Cost of the ith

product

Xi = Quantity of product i

sj = Cost of the jth

activity

qij = quantity of activity j used for product i

Qj = Capacity of activity j

The product mix decisions are taken by maximizing Z in the above two equations for the

ABC and TOC systems respectively under the constraints of resource capacity and demand.

As an alternative to ABC and TOC systems, the following system can be used which

integrates both the controllable and non controllable indirect costs.

According to this system,

Profit ,

( ) ( )i i i j j j

i i j

Z p c X s N R (3)

Where Nj = Portion of labour and overhead costs that do not depend upon the management

control

Rj = Portion of labour and overhead costs that depends upon the management control

In this case the Nj is taken as the period expense and Rj is taken as the product cost and hence

in order to find the optimal product mix Z is to be maximised under the constraints of non

controllable resources and the capacity of controllable resources.

For ABC system Rj = Qj as the management has complete control over the labour and

overhead resources and for TOC system Rj = 0 as the management has no control over the

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labour and overhead resources. But in general 0 < Rj < Qj , and thus in these cases the ABC

system and the TOC system can only find sub optimal product mix. Taking the general

equation (3) we can find the most optimum product mix.

Applying ABC TOC mix method to Lehigh Steel

The costing system mentioned above can be applied to the Lehigh Steel determine

profitability of individual product lines and based on the results the optimum product mix can

be decided in accordance with the profitability of these product lines.

To achieve that, the bottleneck process for individual product lines has to be determined and

the unused capacity of the non bottleneck resources has to be calculated. The control of

management upon this unused capacity will determine whether it is to be taken as fixed or

variable cost. This will help determine the total operating cost for each product line and also

the contribution for each product line can be obtained by deducting the variable cost

components from the selling price of the corresponding product. Using this result and the

demand for individual products in the market an optimum product mix can be calculated.

This will help identify the most constrained resource and also to improve operational

efficiency by removing the constraints of the resource.

Recommendations on the Product Mix In deciding the product mix, the bottleneck process of each of the product line is decided and

according to that the maximum throughput of the 5 sample products are obtained based on

TOC system. But some of the products which give maximum throughput are non profitable

according to the ABC system. Thus we need to determine the control on indirect costs in

order to reach the optimum product mix.

The most profitable products among the five sample products are High Speed: Machine Coil

and Die Steel: Round Bar. The quantity of production of each is obtained by solving an

optimization problem where the constraints are the resource capacity constraints.

The amount of the products that should be produced is given in the table:

Die Steel : Round Bar(lbs) High Speed : Machine Coil(lbs)

Total

Profits(RS)

54,05,248.70 72,41,510.20 10,87,855.72

Thus based on the data given in the case the above product mix is the most optimal one as

obtained by integrating ABC system and TOC system.

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References

1) “Cost Accounting: A Managerial Emphasis”, Horngen, Datar, Foster, Rajan and Ittner,

Thirteen Edition

2) A comparative analysis of utilizing activity-based costing and the theory of constraints for

making product-mix decisions, Robert Kee, Charles Schmidt, Int. J. Production

Economics 63 (2000) 1}17