Zeitschrift für die Herstellung und Verarbeitung vonEisen und Stahl

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ISSN 0340-4803

5/2018Mai 2018

Internet-PDF aus „stahl und eisen“ (2018), Heft 5, Seite 35 – 40. Nachdruck verboten. © jbd Gesellschaft für Medien und Kommunikation mbH, Düsseldorf

How digital technology can transform steel and metals value chains

stahl und eisen 138 (2018) Nr. 5

TECHNIK + TRENDS

Digitalisierung

How digital technology can transform steel and metals value chainsWie digitale Verfahren die Wertschöpfungsketten von Stahl- und Metallherstellern revolutionieren können

Steel and metals manufacturers have a huge opportunity to transform their value chain by implementing digital technology, enabling them to simultaneously improve customer service, profit margins, and inventory levels. Moreover, capturing these benefits does not require a full IT transformation. Rather, companies can quickly capitalize on new technologies like predictive analytics and data lakes through agile pilot tests and begin generating results in weeks, at a fraction of the cost of previous technology.

Digitale Technologien bieten Stahl- und Metallherstellern die Chance, ihre Wertschöpfungskette substantiell zu verbessern und dabei gleichzeitig ihren Kundenservice, ihre Gewinnmargen und ihre Bestände zu optimieren. Zudem erfordert die Realisierung dieser Vorteile keine umfassende IT-Transformation. Vielmehr können Unternehmen durch agile Pilotierung schnell von neuen Technologien wie Predictive Analytics und Data Lakes profitieren und innerhalb von Wochen erste Ergebnisse erzielen, zu einem Bruchteil der Kosten bisheriger Transformationen.

D igital technologies are changing the world – and dramatically improving the way that organizations operate. Companies that embrace digital can create new business models, develop

innovative products and services, and transform their value chains. There is tremendous value-creation potential, especially for industrial companies such as steel and metals manufacturers.

Based on our experience, the typical benefits from an improved and digitized value chain include:

▷ Up to a two-fold increase in customer service levels and deeper customer integration

▷ Improved EBITDA of up to 2 to 4 percentage points with the existing customer base

▷ Inventory reductions of ten days or more.These gains do not require a full IT transformation. Several immediately available technologies such as predictive analytics and cloud-based data lakes can be deployed rapidly. Most companies that implement these technologies can begin generating a positive ROI in their first year itself, a notable improvement from previous IT or digital programs.

Challenges with traditional value chains

Value chains in the steel and metal industry are extremely complex. Companies must contend with

Rainer Schuster, Nicole Voigt,

Gaurav Nath and Nanne Louw

Digital technology can transform steel and metals value chains

Digitale Verfahren können die Wertschöpfungsketten verändern

Ph

oto

: b

ild

kis

tel

stahl und eisen 138 (2018) Nr. 5

TECHNIK + TRENDS

Digitalisierung

a large number of interconnected volatile assets, a vast amount of SKUs, a diverse customer base with varying service and quality requirements, and multiple customer channels with different margin implications. Therefore, asset utilization is often a priority and incentives are structured accordingly, yet these decisions often don’t factor in all business drivers influencing profit margin, service levels, or working capital. Plants and assets often operate in silos, rather than being integrated to meet a larger strategic objective. Supply chain executives have little access to real-time information, leaving them unable to anticipate changes in the market. As a result, companies perpetually play defense, without the ability to anticipate and mitigate risk

or jump on short-term opportunities. Combined, these factors all lead to a significant loss of value, see figure 1 .

Digital as a solution

Many digital solutions are available today and rel-atively inexpensive to implement. Companies can launch smaller-scale pilot tests that focus on a single business unit, asset, or geographic market, and thus prove the concept and begin generating value in a matter of months. This approach puts business needs ahead of the technology, rather than the other way around. Figure 2 shows the range of technologies available now and on the horizon.

1

Typical value leakage in metals supply chains

Typische Wertverluste in Lieferketten von Metallen

2

The maturity radar for digital technology

Reifegrad für digitale Technologien

Gross Margin (million $)

Actual Salesvs. Plan

Low planadherence

Forecastingerror

Salesplan

Co-productsCapacityPrioritisation

AddressableMarket

Demand

PlanDeviation

Management

Total MarketDemand

Executiongap: ~5–10%

INCOMPLETE SYSTEM VIEWINABILITY TO RESPOND SWIFTLY

TO LAST-MINUTE DEVIATIONS FROM PLAN

HIGH-MARGIN DEMAND NOT ACCESSED DUE TO HIGHER

SERVICE LEVEL NEEDS

SUBOPTIMAL SUPPLY-DEMAND BALANCE DUE TO INACCURATE

FORECASTING & PLANNING

Planninggap: ~25%

REAL-VIRTUAL-REALINTERFACE

IoTPredictiveAnalytics

QuantumComputing

New DeviceForm Factors

Augmented/Virtual Reality

4DPrinting

General-PurposeMachine

Intelligence

HumanAugmentation

MASTERINGCOMPLEXITY

AUTOMATEDOPERATIONS

Autonomy

ArtificialIntelligence

ACCESS TODATA

DataLakes & Cloud

stahl und eisen 138 (2018) Nr. 5

In particular, predictive analytics and cloud-based data lakes have demonstrated their potential to revolutionize the performance of value chains, in terms of speed, cost, and ease of implementation.

▷ Predictive analytics and artifi cial intelligence (AI) can sift through large volumes of data generating insights and identifying patterns. For example, predictive algorithms and AI can be used to analyze historical demand and the factors that infl uence it, allowing metals companies to adapt and buffer performance in order to meet market demands.(see the “Use Case: Demand Forecasting” sidebar).

▷ Cloud-based data lakes provide access to data in a way that is fast and scalable – at a fraction of the cost than a major IT transformation – to capitalize on the massive amount of data that is already existent in companies.

How to land the opportunity

To successfully implement and benefi t from these new digital possibilities, one needs to consider three elements:

▷ Harness the power of data through predictive and digital technologies

▷ Build the digital “muscle” in the organization ▷ Maintain a relentless focus on direct business value.

Harness the power of data. To effectively deploy pre-dictive analytics and digital technologies, it is important to break down the problem into specifi c independent topics. These so called “use cases” can be deployed se-quentially and allow companies to capture value early without waiting for the full scope being implemented. Figure 3 shows sample use cases for a metals manu-facturer. A value chain control tower connects all use cases to provide visibility across all initiatives.

Build the digital muscle. While companies can achieve quick-wins with technologies that are relative-ly quick and inexpensive to implement, the gains of digital will only become sustainable through broader organizational measures. Changing cultures and be-haviors can be diffi cult but is critical to fundamentally improve performance. Departments can no longer function in silos; digital allows for collaboration across the company, but only if silos are opened up to foster a more comprehensive view of the value chain.

Furthermore, companies will need to develop their digital capabilities, by putting the right people into three key roles:

Use Case: Demand Forecasting

The most common use case for metals manufacturers is demand forecasting. More accurate forecasts—based on a detailed understanding of customer needs and demand drivers—allow companies to reduce inventory and improve margins while delivering better service. Predictive analytics techniques use advanced, self-learning algorithms to break down demand into component drivers. This improves a company’s understanding of historical trends and enables it to forecast each driver independently; by aggregating these factors, the company can create a far more accurate and richer demand forecast. Prediction models get back-tested for accuracy, and the algorithms adjust based on real-world results to improve their accuracy over time. Such a demand forecast can be set up in as little as 12 weeks, and is ultimately integrated into regular daily processes and decision-making.Metal companies that have applied predictive analytics to their demand-forecasting processes have improved the accuracy of their overall forecasts by 20% to 30% and enable their account teams to focus on what matters—the customer.

3

Typical use cases for metal manufacturers regarding predictive algorithms

Typische Anwendungsfälle für Metallhersteller in Bezug auf prädiktive Algorithmen

Balancing Demand-Supply

Optimising the System

Consistent Plan Deployment

Capacity Forecasting

Demand Forecasting

Flow System Design

Next Generation Sales

Effective Order Exec. &SchedulingOptimal Allocation

Dynamic Pricing

Outbound Logistics

Value Chain Control Tower

Inventory & Buffer Mgt. Customer ServicePerformance

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Digitalisierung

▷ Product owners: the “CEOs” of a given project, who require both business and digital competency

▷ Data scientists/business analysts: experts who ex-ecute analytics projects, gather data, constructing models, and maintain the actual algorithms

▷ Scrum masters and agile coaches: experts who can create the right environment at the beginning of a project and help teams work in a more agile fashion.

Some of these roles can be fi lled through training initiatives for internal talent, but it also requires attracting new talent and building up new functions.

Smart IT. A common refrain at companies is that they are constrained by legacy IT systems, and changes are costly and time consuming. Yet adopting new cloud-based data lake technology enables a more agile approach and can be implemented in parallel to legacy IT, shown in fi gure 4 .

These tools can be piloted at the level of individual business units or projects, allowing the company to build up capabilities and quickly demonstrate the value of such technology with a minimal investment of time and capital. Over time, as the company gen-erates momentum, it can scale up successful projects to other functions, units, and markets. And gradually, legacy systems can be progressively switched off.

Maintain a relentless focus on direct business value.To capture the full promise of digital, companies need to focus on a clear path to value by linking all initiatives to quantifi able benefi ts and actively tracking against it. Digit -al enables companies to create value fast by deploying agile teams that use the insights created to change ways of working already in the concept development phase. This

creates buy-in for the broader initiative by winning over skeptics. It also funds the journey, allowing companies to go further and move faster in their embrace of digital.

Key success factors

Based on our experience, we have identifi ed a num-ber of key success factors to help metals companies implement digital.

▷ Lead from the business side, rather than the tech-nology side

▷ Obtain top level buy-in from day one ▷ Aim to generate value quickly ▷ Immerse the organization in the digital world ▷ Enable agile decision makingIn the past, metals producers could succeed based

solely on operational excellence. Today, that is no longer possible, and companies will rise and fall based on how they handle—and capitalize on—data. Many metals manufacturers have only taken the initial steps to transform their value chains through digital. Although that means a longer path ahead, it also means a bigger potential advantage for fi rst-mov-ers. Companies that recognize the opportunity from digital and take deliberate moves to capitalize on it will give themselves a sustainable advantage. Those that don’t risk falling behind.

nicole.voigt@bcg.comRainer Schuster, Principal, The Boston Consulting Group, Munich, Germany; Nicole Voigt, Partner, The Boston Consulting Group, Düsseldorf, Germany; Gaurav Nath, Partner; Nanne Louw, Project Leader, The Boston Consulting Group, London, Great Britain.

4

Approach to IT

Ansatz für die IT

ManualProcesses

UnavailableFeeds

BUSINESS APPLICATIONS AND USES

Reporting Tool (data warehouse)Processed Data (aggregations)

Data Transformation & Cleansing

Data Extract & Staging

Data Load

Operational Systems and Data Stores

Multiple Systems – do not communicate

DATALAKE

ANALYTICSTOOLS

NEWBUSINESS

TOOLS

Data Processing

Nicole VoigtPartner and Managing Director Duesseldorf

Rainer SchusterPrincipal Munich

Gaurav NathPartner and Managing Director London

Nanne LouwProject Leader London