Steel supply chain transformation challenges Key learnings

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1 IBM Global Business Services White Paper Industrial Products Steel supply chain transformation challenges Key learnings

2 2 Steel supply chain transformation challenges Key learnings Introduction With rising input costs, the Steel industry s main challenge is to meet increased demand while maintaining profit margins. This has lead to increased pressure on supply chain planning to further reduce cost and improve service levels. Implementation of planning systems is often perceived as a key enabler to achieve supply chain process integration, harmonization, efficiency, transparency and optimization. However we have seen that many companies are not able to get the benefits from implementing a planning tool. In this article we discuss what leading companies are doing to transform their supply chain and share key learnings. In addition, we also present our recommendations to design and implement a planning system to support supply chain transformation. Finally, we will discuss the linkages of planning and execution since no planning is complete without successful execution. Supply chain transformation learnings The supply chain of steel companies is changing at a rapid rate due to the increasing consolidation, expansion and collaboration of participants in the market. Additionally, advances in computing power, instrumentation, mobility, and advanced data analytics are changing how companies optimize their supply chains and gain efficiencies. Some key emerging trends in supply chain management include: Global collaboration for Smarter Operations - Developing a global command center or one virtual factory to monitor and control diverse range of operations, deliver products on time as per required specification while maximizing asset utilization and keeping low inventories. Mobile and wireless technology with fast computing - Nowadays automation systems and sensors are available which can report real-time information for decision management on mobile devices and tablets. This is an emerging space for smarter manufacturing operations, intelligent application development based on sensing information and connecting multiple data streams in real time for reporting, optimization and automated decision management. Supply chain risk and sustainability This area is growing in importance due to increased regulation. Supply chain applications are being developed around this area. For example, systems focused transportation optimization with carbon emission reduction as one of the optimization criteria. Based on our experience of working with leading companies across the world, four cases of supply chain transformation initiatives illustrate the type of imperatives, challenges, and outcomes leading steel companies are managing in their supply chain transformation initiatives. Early starters to transformation have already achieved many benefits in areas like procurement by deploying a shared services model of central procurement for rationalizing contracts across plants, re-negotiating contract with vendors, benchmarking, and other activities. However, to ensure comprehensive benefits of supply chain transformation initiatives are realized we need to redesign the supply chain to exhibit certain characteristics. They must be: 1. Integrated - Sales, production, maintenance, procurement, logistics and finance processes are integrated across the Global supply chain operations to improve due date performance, throughput and reduced inventory. 2. Customer focused - planning is focused to improve customer service levels by confirming orders as requested on shorter lead times and smaller lot sizes. 3. Flexible planning adapts to changing shop floor situations with real time visibility and automated rules-based decision management. Also there is a blending of push pull strategies reducing overall work in progress, reducing lead times, and improving on time fulfillment. 4. Cost reduction supply chain continually adapts to improve business processes to drive cost reduction.

3 IBM Global Business Services 3 Steel industry transformation challenges Americas Europe Japan India History Different systems with some custom built on Mainframe technologies Multiple old SAP instances with discrete interfaces and applications Custom built programs for planning and highly customized to user requirements Manual planning processes relying typically on the experience of planner Drivers to change Consolidation of multiple steel mills with their legacy systems Tightening norms and increasing imports Moving from an export oriented model to global plants and operations Capacity expansion and increasing scale of operations Reducing market share Increasing customer service level expectations Reducing quality gaps among top steel producers Increased local and global competition Transformation agenda Improve customer satisfaction level and employees effectiveness Integrated planning across multiple divisions Leverage package-based applications for new plant operations Implement base planning systems Sell products to customers rather than individual plant capacities Improved visibility in business processes and flexibility in order promise Develop collaboration models for service centers and oversea plants (incl. alliance models) Improve visibility for decision management Challenges Developing Global SOP model that allocates global capacities across customers requires operating model redesign Going beyond divisions and integrating processes requires a strong change management initiative Custom systems are much more flexible and it can be difficult to adapt to packaged applications How to get strong Business buy in on transformational supply chain projects for CIO to support growth Increasingly complicated to develop project phases that can be implemented with low business risk and providing visible benefits Global optimization may lead to sub-optimal planning in specific mills/shops Collaboration will require a relook at the operating model of plants/mills in terms of profit centers or cost centers Business decision makers are reliant on access to many planning department people Figure 1: Comparison of the steel transformation challenges Recommendations for design & implementation of planning systems for supply chain transformation Supply chain planning is dependent on the company s strategy around procurement, manufacturing (including maintenance), logistics, and managing customer relationships. These departmental and functional strategies drive the supply chain planning processes and KPIs. Most companies mature in planning processes as they grow and develop their own leading practices. In Figure 2 on the following page, we depict the maturity levels of the planning systems in steel companies. One strategy adopted by a leading steel company was to provide real time order promises. The enablers to this strategy are a capacity allocation model, a real time quality design process, and an Available To Promise (ATP) system. KPIs by which this process was measured included leadtime to customer order promise, automatic quality design ratio, SOP adherence to allocation, and others of a similar nature.

4 4 Steel supply chain transformation challenges Key learnings Level 0 Siloed management Level 1 Functional & data excellence Level 2 Process excellence Level 3 Decision support excellence Level 4 Collaborative excellence Informal practices Manufacturing only focused on asset utilization and yeild Changing goals Siloed technology around business processes Formal data governance: customer, etc. Integrated business functions with visibility across processes: order management, manufacturing Plan/actual comparisons Integrated SOP, order planning and piece scheduling Scenario planning: what-if Event based notifications Analytics Alignment with internal and external partners Optimization product mix, inventory, margins, etc. Sustainability models around green impact Figure 2: Maturity curve for supply chain planning We can broadly classify planning in three levels for a steel company: 1. Sales and Operations planning / Order Independent Planning is done for a horizon of two years at aggregated planning level. 2. Master Production Schedule / Master Planning which is part of order dependent planning across the entire production network, including casting, rolling and finishing. Generally we see companies do this for a horizon of three months at actual product level. 3. Detailed Planning / Piece based line scheduling which is done for the short-term horizon. It is important to note that planning needs to be updated as per execution changes and quality / rework requirements evolve. Additionally we need planning to be integrated with all other processes and functions of procurement, logistics, production, maintenance, sales and finance. There are multiple technology solutions available from vendors for some or all of the planning levels. However we need to correctly define the objectives and set the responsibility for each planning level before we begin the implementation. Guidelines to metrics across planning levels are provided in Figure 3. The question that we are asked most is often is regarding ATP. In a typical warehouse scenario that question can be addressed by the stock availability. However in a steel plant that mostly operates in a make-to-order scenario; there are multiple answers to this problem.

5 IBM Global Business Services 5 The planning system design must integrate all three levels of planning and provide us with an integrated plan. Additionally the planning engine should consider multiple and changing rules that are prevalent in steel production. For example, if the quality of intermediate coil is not conforming to customer specification we can do an additional operation in the finishing line to bring the coil within specified quality. An approach to manage this scenario is to build rules for non-conformity situations and integrate them with planning. A rules engine is generally used to build rules and can have additional functionally to manage feasibility check (translating commercial to metallurgical characteristics), price discounting based on customer segmentation, rework decisions, etc. Sales and operations planning/order independent planning Forecasting accuracy at planning level Customer prioritization/ product mix decisions Master production scheduling/ master planning Lead time across product categories/ customer segments On time order fulfillment Detailed planning/piece based line scheduling Throughput and delay per shop Productivity loss and process efficiency (coffin shape etc) Availability management scenarios generally followed in steel companies Manage Availability by Allocations or Quota per customer In this scenario the SOP plan recommendations are used to confirm availability for customers. Preferable when we generally accept large lot sizes. Additionally contracts are sometimes managed by allocation and then a replenishment process is used to deliver steel to customer as per weekly requirements. Manage Availability by Schedule In this scenario availability decisions are taken based on master planning. This is preferable when we commit to smaller lots. In some cases companies confirm by allocations and derive sales order schedule lines by master planning (preferably by bottleneck resources) Mixed Strategy of make to order / make to stock In this scenario the company commits order for important customers from an intermediate stocking location to reduce lead time and increase net sales realization. This intermediate stock is produced by the company at a decoupling point based on forecast and risk appetite. Capacity Allocation and Allocation deviations Procurement and Transportation Planning Inventory levels (raw material, work in progress, finished) and upstream resource plan for maximum utilization of multiple downstream resources Procurement/ Logistics decisions and deviations Adherence to inventory levels and master plan of orders for each resource Logistics Plan for inplant/in-shop movement, Stacking In the context of the above discussion, we have listed few recommendations for successful implementation of a planning system to support supply chain transformation: 1. Identify processes within Procurement, HR, Finance & Accounts, IT to develop a shared services model. 2. Develop central planning, maintenance, and logistics cells to harmonize processes first. Figure 3: Key metrics per planning level 3. Develop a business benefit case detailing key metric and process improvements.

6 6 Steel supply chain transformation challenges Key learnings 4. Select appropriate packages for implementation that are scalable, easy to maintain, seamlessly integrates with the core ERP & MES layers and offers steel industry specific prebuilt functionality. Some times it is better to evaluate packages and their sub modules against each requirement or gap present in our current planning function / system. 5. Design and implement the IT system to provide harmonized processes, visibility, integration and automated decision support. 6. Measure the success of implementation by the achievement of key metric goals. Linkages of planning and execution The reason we discuss the linkages topic is due to the fact that no supply chain planning is complete without successful execution. In the past, many steel producers either have developed very good execution systems or planning systems but in more of the cases, gaps are identified between planning and execution. We define linkages of planning and execution as Shop Floor to Top Floor Integration. The goal of execution systems is automation of business functions to improve people productivity, reduce operation variability, reduce process waste, and optimize operations. The execution system must also seamlessly integrate into the steel company s application landscape with planning systems, L2 systems and core ERP. Many companies have existing legacy or in-house developed systems for execution. The challenge faced with these systems is that they are difficult to maintain, person-dependent and inflexible. Nowadays packaged MES systems are available from multiple vendors to enable steel production, tracking and recording. Steel Industry specific MES systems even offer functionality to manage detailed planning / piece based line scheduling and sequencing example coffin shapes etc. Functions of an MES system - Order execution, Material requests, Equipment requests, Transportation request, Quality Measurement, Non-conformity identification, Stock Management, warehouse logistics, L2 integration (feed and record execution data), planning and ERP system integration. Steel producers embarking on supply chain transformation are first to implement a planning system or execution system. There is no right answer to this question and it depends on business benefits versus business risk. Our vision of Shop Floor to Top Floor Integration is more than just a package implementation of SCM or MES. It is the integration of processes and data that were historically managed in multiple layers. Business goals like real time order promise may require organization, policy and process changes with tight linkages of planning and execution systems. We think that with advancement in technology, integration of shop floor to top floor is possible in real time. This enables us to build intelligent analytics driven enterprise wide applications working with ERP, Planning and Execution systems. In addition to a systems enablement of supply chain transformation, this initiative also requires operating model redesign to align the organization, policies and processes in line with the supply chain goals. As with all changes to technology and process, formal change management initiatives are an integral part of Planning and Execution system implementation because of the profound, direct impact on shop floor workers who are accustomed to operating in the same way for many years.

7 IBM Global Business Services 7 Supply chain analytics In continuation of our discussion around integration of shop floor to top floor, the biggest advantage that we see is in the area of supply chain analytics. Presently there is typically a low utilization of data coming from shop floor. Even if data is utilized, it is typically used in a siloed fashion by individual departments. For example, the quality department will only analyze quality data for a mill and the production department will only analyze the yield. This leads to blind spots which if not corrected affect manufacturing lead time, quality and cost. Increasing data utilization and generating a useful meaning of the data is the goal of supply chain analytics. This enables holistic and collaborative analysis of data to provide visibility in real-time to aid decision-making. We call this the vision for the Smarter Plant. Predictive Quality Monitoring: This means to monitor proactively at defined quality monitoring points like BF (molten iron), EAF(molten iron+scrap), LD/ VD (Steel + Alloys) factors that lead to specified quality. At each of the stages if there are changes in key factors then the quality models that predict the output quality assist us to take corrective actions before there is a deviation from the desired or specified quality. Conclusion Many companies are embarking on a supply chain transformation journey and establishing their 2020 Plan will likely present a more competitive and challenging marketplace. Steel companies who take action today to transform and optimize their execution and planning capabilities from shop floor to top floor, adopt leading execution and planning systems, and embrace data analytics will position themselves to be competitive and successful for today and 2020 and beyond. For more information To learn more about IBM Global Business Services, please contact your IBM sales representative or visit us online: ibm.com/metalsmining About the authors Jeremy Yoo, Vice President, Global Industrial Products Industry Leader IBM Global Business Services Abhishek Kaul Global Metals Industry, Supply Chain Consulting IBM Global Business Services The Smarter Plant vision will require multiple departments working with each other across mills and across geographies with Global corporate-wide analytics and intelligent applications for decision management. This can be a resultdriven and rewarding experience for steel makers.

8 Copyright IBM Corporation 2012 IBM Global Services Route 100 Somers, NY U.S.A. Produced in the United States of America April 2012 All Rights Reserved IBM, the IBM logo and ibm.com are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are marked on their first occurrence in this information with a trademark symbol ( or ), these symbols indicate U.S. registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Webat Copyright and trademark information at ibm.com/legal/copytrade.shtml Other company, product and service names may be trademarks or service marks of others. References in this publication to IBM products and services do not imply that IBM intends to make them available in all countries in which IBM operates. Please Recycle GBW03172-USEN-00

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