Lehigh Steel Case Analysis

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 Gadkhel Rohit Gokulnath R Kartik Shrivastava Sumit Prakash Upasana Mukherjee Vemb V

2011PGP448 2011PGP629 2011PGP638 2011PGP685 2011PGP907 2011PGP922 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

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 hightech, 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 Direct labour Direct manufacturin g expense

0.54 0.29

0 0.07

0.12 0.28

0.21 0.18

1.58 0.14

0.24

0.06

0.23

0.16

0.12

1.24

0.64

0.39

0.38

0.49

53.70%

83.10%

38.20%

40.90%

21%

593562

1332188

941187

2545119

1239970

0.64

0.64

0.64

0.64

0.64

0.6

0

-0.25

-0.26

-0.15

26%

0%

-24.50%

-28%

-6.40%

287207

0

-603325

-1741397

-379583

Contribution margin ($) Contribution margin (%) Total Contribution( $) Manufacturin g & Admn. Overhead Operating profit ($) Operating profit (%) Total Operating profit ($) Total Profit($)

-$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

Melting - Dep

Melt machine minutes

51,45,632

21,39,865

0.415860481

Melting Maintenance

Melt machine minutes

51,45,632

975130

0.189506362

Melting utilities

Melt machine minutes

51,45,632

2036477

0.3957681

56,91,042

1711892

0.300804668

56,91,042

780104

0.137075776

56,91,042

1745551

0.306719051

Refining - Dep Refining Main Refining Utilities

Refine machine minutes Refine machine minutes Refine machine minutes

Molding - Dep

Mold machine minutes

42,26,965

427973

0.101248295

Molding Main

Mold machine minutes

42,26,965

390052

0.092277083

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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Cumulative Rate

1.001134943

0.744599495

0.262351356

Rolling - Main

Roll machine minutes

82,58,382

975130

0.118077609

Rolling Utilities

Roll machine minutes

82,58,382

872776

0.105683656

40,57,311

1283919

0.316445794

40,57,311

780104

0.192271187

0.586521306

Finish machine minutes Finish machine minutes Finish machine minutes Pounds

40,57,311

872776

0.21511193

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

Finishing Dep Finishing Main Finishing Utilities G&A

7

0.72382891

ABC Costing ABC Cost ($/lb)

Alloy : Condition round

Price($)

Conversio n: Roller wire

Die steel : Chipper knife

Die steel: Round bar

High speed: Machine coil

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

-34.339

0.761

6.238

Total Operating profit

-52386.495

-17.546 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 8

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

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Cost Driver

Weight is taken as primary cost driver

2

Time orientation

Independent of Time

ABC All indirect costs are related to the product through a causal relationship, so the cost drivers are different for different activities Long term Oriented

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

Cost pools are homogeneous

Only matrial costs included, hence only economies/diseconomies of scale in procurement may be involved

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4

Linearity of Variable Costs

Cost pool not homogeneous

TOC

Time taken by a process is the main cost driver

Short Term Oriented

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. 10

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 11

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, Z   ( pi  ci ) X i   s j qij X i i

(1)

i, j

According to the TOC system, Z   ( pi  ci ) X i   s j Q j i

(2)

j

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 Z   ( pi  ci ) X i   s j ( N j  R j ) i

(3)

i, j

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 12

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

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