Emerging Steel Giants: Are All Sources of Value Explored?

In recent years, observers have seen the steel industry rapidly consolidate. In the past five years, more than 800 steel producers have changed hands. Consolidation activities in the mid-1990s focused on alliances between domestic steel producers. This type of consolidation wave can also be expected in the Chinese market.

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Hans Bohnen Nils Naujok Joachim Rotering Peter von Hochberg

Emerging Steel Giants: Are All Sources of Value Explored? How to Generate All Top- and Bottom-Line Contributions from Ever-Growing Production Networks
This report was originally published before March 31, 2014, when Booz & Company became Strategy&, part of the PwC network of firms. For more information visit www.strategyand.pwc.com.

Booz & Company is a leading global management consulting firm, helping the world’s top businesses, governments, and organizations. Our founder, Edwin Booz, defined the profession when he established the first management consulting firm in 1914. Today, with more than 3,300 people in 58 offices around the world, we bring foresight and knowledge,

deep functional expertise, and a practical approach to building capabilities and delivering real impact. We work closely with our clients to create and deliver essential advantage. For our management magazine strategy+business, visit www.strategy-business.com. Visit www.booz.com to learn more about Booz & Company.

Joachim Rotering is a partner based in Düsseldorf. He focuses on market strategy, postmerger integration, restructuring, transformation, and sourcing. His industry experience is in process industries, especially steel and chemical. He can be reached at +49-211-3890-250 or [email protected] Peter von Hochberg is a partner based in Düsseldorf. He has broad experience in integrated restructuring, cost management in operations, manufacturing diagnostics, and transformation. His industry experience is in the automotive, steel, and high-tech industries. He can be reached at +49-211-3890-170 or [email protected] Hans Bohnen is a principal based in Düsseldorf. His areas of focus are cost management, optimizing production networks in process industries, Lean production, and Six Sigma deployments in the chemical and steel industries. He can be reached at +49-211-3890-112 or [email protected] Nils Naujok is a principal based in Berlin. He has broad experience in manufacturing, supply chains, postmerger integration, restructuring, and sourcing, especially in the chemical, steel, and industrial gas industries. He can be reached at +49-30-88705-855 or [email protected]

Originally published as: Emerging Steel Giants: Are All Sources of Value Explored? How to Generate All Top- and Bottom-Line Contributions from Ever-Growing Production Networks, by Joachim Rotering, Peter von Hochberg, Hans Bohnen, and Nils Naujok, Booz Allen Hamilton, 2008.

Emerging Steel Giants: Are All Sources of Value Explored?
How to Generate All Top- and Bottom-Line Contributions from Ever-Growing Production Networks
In recent years, observers have seen the steel industry rapidly consolidate. In just the past five years, more than 800 steel producers have changed hands. Consolidation activities in the mid-1990s focused on alliances between domestic steel producers. In Europe, for example, Krupp acquired Hoesch and then merged with Thyssen to form ThyssenKrupp Steel, and British Steel merged with the Dutch metals producer, Koninklijke Hoogovens. When Japan’s Kawasaki Steel merged with NKK, the result was JFE Steel—the world’s fifth-largest steel producer and Japan’s second-largest after Nippon Steel. This type of consolidation wave can also be expected in the Chinese market; the extremely fragmented steel industry in that country has more than 40 steel producers with a total production capacity of less than 5 million tons of crude steel.
During the past five years, global alliances have also become strategically relevant. Domestic steelmakers have allied with those in different regions and with foreign companies. Mittal Steel was among the first to put a global spin on this M&A trend with its most recent coup—the acquisition of main competitor Arcelor. Mittal’s move was soon followed by Tata Steel’s unexpected acquisition of Corus. Today’s steel landscape indicates that both regional and global consolidation will continue in the upcoming years. Although the trend among U.S. and European players has been to merge with companies in their respective markets, they might need to take a global approach in the future. U.S. Steel and Nucor, for example, are big players in their home countries; each has an annual output of about 20 million metric tons. Globally, however, these production levels place them in a secondary tier, and they have only a minor international presence for serving their globalizing customer accounts. For an overview of steel industry consolidation activities since 1992, see Exhibit 1, page 2. Ultimately, the goal of consolidation in the steel industry is simple: become more flexible and thereby better able to manage the cyclical nature of the market to ensure price stability. Because these cycles will never completely disappear, consolidation is a good way of matching supply with demand. Emerging steel giants will manage the balance of supply and demand by leveraging their increased bargaining power over consolidating raw material (iron ore, coal) and customer (automotive) industries. But consolidated industries at the beginning and end of the steel value chain can create a “consolidation trap,” the negative effects of which numerous large steel companies have experienced. Such companies,


Exhibit 1
Consolidation Process in the Steel Industry since 1992
2007 Rank, in MTPA (metric tons per annum) 2004 ISG Arcelor 2002–2004 2 1998 2001 4 NKK Kawasaki Steel British Steel Koninklijke Hoogovens Tata Anshan Steel Benxi Steel Shangahai Steel Systems Meishansteel U.S. Steel National Steel Kosice Sartid Nucor Trico Birmingham Wuhan Steel Liuzhou Steel Hoesch Krupp Thyssen
Source: Booz Allen Hamilton

1992–1997 LNM Group Ispat LTV Acme Bethlehem Weirton Georgetown Steel Cockerill Sambre Usinor Arbed Aceralia

1998–2006 1

Mittal Steel

66 117 51

Nippon Steel JFE Steel POSCO Corus Tata Steel

33 32 30 18 25 7 23


2002 1999 2006











U.S. Steel










1993 1997




however, now can leverage their combined market knowledge to a greater extent, and this enables them to make better price and production decisions. These strategic objectives alone do not make steel industry mergers and acquisitions successful; other enabling prerequisites must be achieved during postmerger integration. From the beginning, the new enterprise has to establish a stable organization and a joint knowledge base for dealing with the

complexities of cultural integration. This is especially true for those mergers that bring together very different cultural heritages. In addition to creating a well-functioning organizational network, it is almost as important to create a newly balanced and harmonized production network. This “network perspective” on production yields significant and sustainable top- and bottomline synergies in addition to the more common ones


from SG&A (selling, general, and administrative expenses) and procurement. But despite the ongoing consolidation activities and increasing joint production capacities of the merged companies, little focus has been placed on optimizing the newly established production networks. Many companies still view production as the sum of individual plants and not the product of an integrated production network, even though a well-optimized production network offers significant potential for cost reduction and throughput increases. To react to cyclicality and remain competitive, steel companies will have to increase production efficiency by making better use of their existing or newly created networks’ capacity. Booz Allen Hamilton has established a structured and proven four-step approach that generates improvements in cost as well as throughput. It is based on a solid data baseline that optimizes the allocation of production orders within the network. As shown in Exhibit 2, the results of this approach could be significant. Based on Booz Allen’s experience, the application of this methodology can generate
Exhibit 2
Benefits of Cost and Output Optimization

cost advantages of US$20–$40 per ton for up to 20 percent of the combined production volume. Moreover, the methodology can achieve an increased throughput between 15 and 20 percent, and this offers a consolidated steel network the flexibility to react to changing supply and demand scenarios. Details of Booz Allen’s four-step approach to network optimization are illustrated in Exhibit 3, page 4. Step 1: Scoping the Combined Production Volume The composition of an optimized production network configuration should derive from well-grounded operation status; therefore, describing and scoping the combined production program is a necessary first step for understanding site-related constraints and customer requirements that prevent certain steel qualities from being produced elsewhere in the production network. As an example, site-related constraints can occur in the primary and secondary metallurgy because of limited capabilities in attaining different sulfur or silicon contents. These limitations can reduce the scope of the production volume

Cost Optimization

Output Optimization

10%–20% of the production volume in scope can be optimized (cost difference of US$20-$40/ton)

15%–20% more output can be generated (cost bene t of US$80-$120/ton)



Cost Advantage (US$/ton)

Cost Advantage (US$/ton)

Upper limit

Upper limit

Base case
$50 $40 $30 $20 20 30 40

Base case Lower limit

Lower limit


Cost Difference (US$/ton)
Volume in Scope (MTPA)


Cost Difference (US$/ton)
80 1.85 100 120 2.45


Throughput Increase (MTPA)





US$25–$60 Million
Source: Booz Allen Hamilton

US$150–$300 Million


Exhibit 3
Four Steps for Optimization of Steel Production Networks
2a Cost Optimization

1 Description of Production Volumes

Identi cation of cost drivers Evaluation of process-related cost differences Identi cation of steel grades to be exchanged

3 Production Volumes Network Optimization

4 Evaluation

Description of combined production program Identi cation of site-related constraints Customer requirements

2b Output Optimization

Identi cation of boundary conditions: – Quality – Logistics Description of product/ asset allocation principles

� � �

Financial bene ts Implementation steps Investments

Identi cation of production bottlenecks Optimization of steel-graderelated slab throughput

Optimization Scope

Optimization Levers

Optimization Concept

Optimization Bene ts

Source: Booz Allen Hamilton

for a network optimization by 30 to 50 percent. In addition to understanding customer and technical requirements, it is necessary to generate transparent and comparable data for chemical analysis; key quality data; production routing; and casting width, length, or speed. A common, singular technical language from the beginning is the prerequisite for any network optimization. Step 2: Evaluating the Optimization Levers Before the most important optimization levers can be identified, it is essential to verify two things: the units (from desulfurization to casting) that are causing bottlenecks and the related root causes (casting width, casting speed, vacuum capacity, or any other technical constraints). One way of gaining transparency into the production process is by compiling the operating asset effectiveness (OAE) of the main bottleneck units. The OAE places the most common and important sources of productivity losses

into three categories: utilization rate, throughput rate, and quality rate. Exhibit 4 illustrates the OAE for a continuous casting unit. The OAE analysis clearly indicates the main levers for a higher and more cost-efficient steel output. For continuous casting units in particular, most output losses occur as a result of a very low throughput rate. Based on Booz Allen’s experience, poorly planned order configuration within the network is the key root cause for such losses. Optimizing slab width by combining production orders is one of the levers with a very high impact. Of the overall throughput improvements, 70 to 80 percent can be generated by a better aligned forecasting and planning process for production orders. Another important lever for an increased throughput rate is the casting speed. Analysis of steel production networks indicates there are significant differences in casting speed among different casting units for the same steel quality. Optimizing the


Exhibit 4
Illustration of the Operating Asset Effectiveness for a Continuous Casting Unit
Operating Asset Effectiveness (OAE) Utilization (percent) 8,760 hours x hours X Throughput (percent) 8,760 hours–x hours X Acceptance (percent) = OAE (percent) OAE Analysis: Levers for OAE Losses tons Utilization Losses: Changeover (low sequence rates), breakdowns, planned and unplanned maintenance


Throughput Losses: Lower casting speed, no optimized slab width, poor adaptation of steel grades to process requirements

Quality Losses: Quality defects and rework, startup losses

Annual Production Time

Utilization Losses

Utilization Rate

Output at Maximum Throughput

Throughput Losses

Net Output

Devaluation and Scrap

Achieved Output

Source: Booz Allen Hamilton

production order configuration to the most suitable production plant for the particular steel quality results in additional benefits. Allocating steel grades to just one or two specific steel plants creates less complexity and a more standardized production program. As a consequence, longer production cycles can be run; because there are fewer changeover activities, the utilization rate increases. Booz Allen has identified four main levers, shown in Exhibit 5, that generate capacity increase within a steel production network. In addition to output optimization, cost benchmarking among plants for specific steel grades offers further benefits from an aligned production network. A more standardized and focused production program leads to a reduced material flow and improved internal logistics, which lower the overall transportation and distribution cost. By taking into account the specific technological strengths and weaknesses in the primary and secondary metallurgy, still other cost improvements are realized. Exhibit 6, page 6, summarizes some of these cost drivers. For example, while one plant has improved its substitution of scrap

for some steel grades, other plants have advantages because of their reduced use of additives for other grades. Exhibit 7, page 6, illustrates Booz Allen’s cost benchmarking approach. Based on the main cost driver, steel grades A and B have clear cost

Exhibit 5
Levers to Increase Capacity within Steel Production Networks

1. Optimization of slab width by combining production orders

Identification of production bottlenecks

Identification of throughput improvement levers

2. Increase of casting speed

3. Combination of production orders to increase sequence rates 4. Adapting steel grades to desulfurization, converter and casting process requirements

Throughput improvements from primary metallurgy to slab casting

Source: Booz Allen Hamilton


Exhibit 6
Influencing Site-Specific Production Requirement on Cost Drivers
Cost drivers...
� �

...are influenced by production process requirements Cost reduction due to captive raw material supply Optimization of blast furnace marginal cost

1. Raw iron supply

2. Alloys, scrap, and additives

� �

Scrap quality adaptation Reduced use of additives (e.g., for desulphurization or oxygen reduction)

Speci c “consumption” (kilograms/ton) multiplied by material prices (US$/kilogram)

3. Auxiliary and supporting systems

Reduced use of refractory due to longer sequence rates and bundling of production orders

4. Quality

Reduced devaluation and scrap volumes due to the optimal allocation of steel grades to production equipment

5. Asset utilization

Improved throughput (tons per hour) due to the optimal allocation of steel grades to production equipment Reduced idle time due to standard production programs with fewer planning requirements Reduced transportation needs and external distribution costs due to reduced material ow and improved internal logistics

6. Transport and distribution
Source: Booz Allen Hamilton

Exhibit 7
Cost Differences by Shifting Steel Grades
Sum of Cost Benchmarking for All Drivers in US$/ton
Cost Advantage Steel Plant A

Shift to Plant A Booz Allen Hamilton Experience A
Steel Grade



Peritectic steel E

IF steel

Mild steel

High-alloyed steel

Micro-alloyed steel



Average of US$20–$40/ton cost difference in speci c steel grades (assumption) Steel grade speci c difference depends on site-speci c production requirements Cost difference highly affected by speci c scrap and raw iron rates and their prices (level of backward integration)

Cost Advantage Steel Plant B
Source: Booz Allen Hamilton

Shift to Plant B


advantages in Plant A, while the steel grades E, F, and G can be produced more cost-efficiently in Plant B. Assuming that the exchanged production volume between plants is equal so that production capacity is not lost, the overall cost benefit is substantial (see Exhibit 2, page 3) even if some steel grades (such as grade D) have to be produced at the nonpreferred plant. Step 3: Fine-Tuning the New Production Network As a result of the throughput and cost analysis, a first set of planning principles can be developed using the identified bottlenecks most efficiently. Booz Allen has identified three main restrictions that need to be analyzed up front, before executing the new planning principles. First, customer requirements such as delivery dates or preferred hot or cold strip mills need to be considered. Second, it is necessary to understand the impact of an increased OAE for bottleneck units, including converter or casting lines on downstream aggregates such as vacuum units or finishing lines. Finally, transportation and logistics have to be reviewed to find bottlenecks within the
Exhibit 8
Prerequisites for Successfully Optimizing a Steel Production Network
� �

logistics supply chain from slab production to the final strip mills. Step 4: Executing the Concept To sustain the benefit and continuously improve the internal production network, certain conditions must be met (see Exhibit 8). The formulation of planning principles for each steel grade is essential for setting up distinct standard operating procedures for production scheduling. It is important that the supply chain organization works within this process and is not captured in a functional ivory tower. This is key to having a transparent and consistent forecasting process that determines the effect of planning and production principles. The continuous coverage of the OAE for all bottleneck units within the network is also a necessary task for operations. Order planning and capacity utilization have to be aligned and follow the same rules. It is well known that only what is measured can be improved; therefore, a consistent key performance indicator (KPI) system both for planning and production efficiency and customer satisfaction



1. Scoping

� �

Data transparency Comparable operational de nitions Standardization Identi cation of interchangeable production volume Evaluate main levers for output optimization Evaluate main cost driver Prepare planning principles for an optimized production network

Development of standard operational de nitions for production and quality parameters Clear understanding of technical capabilities of individual plants with a special focus on primary and secondary metallurgy

2. Evaluating and Fine-Tuning

� �

� �

Development of planning principles for every steel grade based on the optimized production network Development production principles (standard slab production versus exible slab production; pull versus push production) Development of a supporting stock concept (make to order versus make to stock) Continuous OAE coverage for all bottleneck units within the production network Supply chain organized by process, not function, following common supply chain principles Development of an IT-based planning system following the introduced planning principles Transparent and consistent forecasting process Cross-functional training classes for all involved employees Consistent KPI system for planning, production ef ciency, and customer satisfaction Cross-functional approach of an incentive bonus system

� �

3. Executing

Generate output and cost bene ts Sustain and continuously improve the internal production network Be responsive to changing market conditions or customer requirements

� � �

Source: Booz Allen Hamilton


is essential for driving continuous improvement activities within the production network. All of these things need to be implemented within the entire network, bringing together cross-functional and cross-regional employees. Thus, a consistent company-wide approach to training and coaching key personnel is necessary to tap the full potential. Operational network optimization meets cultural network improvements—this makes any production network optimization a cornerstone of successful postmerger integration for newly established steel conglomerates. Conclusion Optimization of combined steel production networks is strategic by nature because it differentiates a company from its competition, delivers revenues as well as cost benefits, and addresses supply chain

challenges. Optimization guarantees a high return on investment: The initial analysis is fairly quick—four to six months—and payback time is often less than one year. The benefits of a consistent and robust network optimization are long lasting, and because the initiative has to be cross-functional, the entire organization is included. For recent mergers in particular, the proven Booz Allen approach ensures a global rather than local optimization that uncovers hidden synergies and eliminates duplications. A comprehensive network optimization is still cuttingedge thinking for most steel companies, and to date there is limited evidence for fully integrated and aligned steel production networks. Booz Allen’s innovative and comprehensive approach provides clear guidance on how to establish an optimized network, which could lead to a sustained competitive advantage in the current steel industry environment.

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