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As steel producers continue to be painfully aware, the volatility of global demand for steel looks set to continue for many years. This unpredictability is driven in large part by emerging economies like China, coupled with increasing global market competition. In light of this, improvements in the way that companies manage their supply chain can act as a key competitive differentiator and unlock value, both in terms of reducing working capital requirements, and creating additional value through exploiting new market opportunities.
Over recent years, many steel companies are realizing that they are losing market competitiveness (and in some cases market share) because they are not able to satisfy the requirements of an increasingly demanding market. Customers are demanding shorter delivery lead times, while steel producers are facing increasing business and planning complexity due to growing market demand for more complex steel products, which is driving up production lead times and the need for higher inventory levels. Additionally, many steel producers now have longer and more complex internal and external supply chain processes, including the use of subcontractors, which makes it very difficult to manage and coordinate along the supply chain.
These more recent dynamics also go hand in hand with the traditional challenges that steel producers face, for example: siloed organizational structures, the inability to generate accurate sales forecasts, ineffective planning for market and product mix opportunities, and the difficulty to calculate feasible order delivery dates for production. Such challenges have a direct negative impact on supply performance. (See case example for more detail.)
In simple terms from a supply chain perspective, steel companies need to balance significantly improved customer service levels, while simultaneously minimizing working capital requirements and the potential impact of supply chain disruptions. Unfortunately, enabling these new supply chain capabilities is not a trivial task, and requires a clear strategy and plan for potential success.
Typical barriers to effective supply chain management result from issues such as:
Disconnects between existing business processes and information technology (IT) systems, including gaps in functional coverage.
Inconsistent business rules and priorities across the company, including misalignment between the different planning process time horizons and cycle times.
Inability to align the organization to drive effective supply chain management.
A lack of consistent metrics to drive behavior, and measure adherence to target policies and procedures.
Achieving an effective supply chain transformation requires the careful alignment of processes, organization and job roles with software capabilities.
Based on Accenture’s extensive experience working with steel companies around the world, five of the key factors critical to success in enabling and delivering supply chain transformation projects in the steel industry are:
By not addressing these areas appropriately, many steel companies have not been successful in achieving the supply chain transformations that they originally set out to do. Such missed opportunities are frequently blamed on the lack of maturity of available software tools for supply chain management and, while this partially may have been the case in the past, it is frequently not the real underlying reason.
In the next sections, we will highlight some important considerations relevant to the above factors and provide insights into how steel companies should address them in order to achieve a supply chain transformation that drives toward high performance.
Case example: Large European steelmaker
Example supply chain process issues facing the company
The different planning process levels (e.g., demand planning, production planning) did not have aligned objectives and were being performed in functional silos.
Customer order intake was not fully aligned with the supply/ master plan. As a result, customer orders were accepted that did not fit with business objectives.
Order promises to customers were not based on a realistic evaluation of available material and capacity.
Monthly production plans were generated focused on maximizing Basic Oxygen Steelmaking (BOS) converter utilization, and not the overall material flow and due date requirements of orders. Plans were created based on the use of spreadsheets.
Because the created production plans were not feasible and did not allow manufacturing to meet its objectives, the scheduling of production through the finishing units was not aligned with the production plan.
Business impact of supply chain challenges
Average actual production lead times were typically two times the planned standard lead times—due to lack of coordinated material and capacity production planning.
Stock levels of key steelmaking raw materials (e.g., ferroalloys) were on average 11 days (of cover) higher than industry leading practice—driven by poor sales forecast accuracy.
On-time and in-full delivery of products in some cases was below 50 percent, with high levels of variability— driven by a quantity-based planning process focus, rather than order-based.
Finished steel product stocks for customer consignment stocks were typically 15–20 days too high, when compared to industry leading practice—driven by a lack of visibility of planned order completion dates.
Business policy and process alignment
Supply chain management processes cannot be considered in isolation and their impacts on other end-to-end business processes, such as order-tocash, purchase-to-pay and plan-toreport, need to be carefully determined and aligned. These business process impacts have in turn potentially significant influence on existing enterprise resource planning (ERP), or legacy IT systems, and can present significant constraints in the delivery of a successful supply chain software solution.
The deployment of a supply chain transformation in a company is often accompanied with a significant change in market-facing and manufacturing strategy. Most recently, many steel companies are moving away from more traditional make-to-order business models to a combined make-to-stock/ make-to-order approach. Such changes in operating model clearly require a careful redefinition of certain key business policies to confirm that the new model can function appropriately. Furthermore, such policies and procedures need to be carefully aligned both vertically and horizontally across the different planning time horizons and functional areas.
Business process and software alignment
A number of supply chain software solutions are available in the market that provide a good fit to the requirements of the steel industry.
One of the most common mistakes made when implementing SCM software is the failure to correctly align the tools (and their capabilities) to the business and functional requirements. A frequently observed scenario is as follows:
A company starts a supply chain initiative with a focus on production planning and purchases an appropriate software application. During the solution design phase, a long list of business and functional requirements are identified, which include many requirements that are beyond the actual scope of the designed functional capabilities of the software. A simple example of this is a requirement to be able to model the sequencing of material for a hot rolling mill. The project team decides that these sequencing requirements are important and, even though the tool is not really designed for it, they believe that customizations can always be implemented to ‘make it work.’
Later in the build phase of the project, such customizations effectively fail because the application is being forced to do things it was never designed to do. As a result, the project struggles, users become dissatisfied because the software does not function according to their expectations, and ultimately the company does not receive the benefits expected.
Because of such initial experiences that many companies have with advanced supply chain software tools, often the software is blamed for not being good enough and the company is reluctant to make further investments in the supply chain area.
A critical aspect of any supply chain transformation is, therefore, to have a deep understanding of the capabilities of different software applications being considered, and to be able to map these capabilities in the correct way to business and functional requirements.
Demand planning and supply planning combine to provide sales and operations planning (S&OP) capability. S&OP provides a medium-/long-term tactical plan for the business—taking a consensus sales forecast that is balanced against production capabilities. Tools often provide capabilities for characteristic dependent planning, capacity reservations and the ability to create plans optimized based on relative margin contribution of different products (so called ‘profit optimization’).
Order promising enables both available-to-promise (ATP) and capable-to-promise (CTP) capabilities. ATP provides a reliable ‘due week’ order confirmation to customers, based on allocations driven from the S&OP process. CTP provides a ‘due date’ order confirmation, based on the current production plan, reflecting actual material and capacity availability.
Production planning generates a feasible short-term, order-based plan that is key to seeking to achieving the on-time delivery of customer orders.
Scheduling creates material-based sequences based on detailed manufacturing constraints of the production plan. Typically, multiple scheduling tools are used at different stages of the steelmaking supply chain.
Planning model granularity
Due to the complexities of steelmaking manufacturing processes and products, it is not practically possible to manage all planning decisions that are relevant to different time horizons in one single planning tool. Therefore, different planning horizons require different tools and levels of granularity in what they model.
A good example of this is S&OP. In the steel industry, because of the large number of end products involved (up to hundreds of thousands), S&OP should be performed at an aggregated product family, or group, level. A product family represents a logical grouping of individual sold products that have similar attributes, follow similar production routings and consume similar product capacity (as measured in terms of machine run rates and yield). In some cases, it also may be appropriate to differentiate between sales forecast product groups and supply planning product groups, which can be managed on different aggregation levels. The optimum level at which to perform product group aggregation is different for each steel company—depending, for example, on product mix and process route complexity—and is a function of the trade-off between requirements for planning accuracy and control, versus model complexity and usability.
It is important to recognize that small differences between individual products—for example, steel grade specification, width and thickness—does not automatically drive a need to proliferate the number of product groups that are defined. Conversely, the defined product groups need to be able to provide a reasonable model of production capacity consumption, to allow realistic mid- and long-term planning decisions to be made, and to allow the business to make correct product/market allocation decisions.
A further key consideration is that the level at which planning groups are defined should be a level of aggregation at which the company can make a sales forecast with a reasonable degree of accuracy. At the S&OP planning level, steelmakers are not trying to create a sales forecast and plan for the next week; therefore, an aggregated view of demand based on a few key product attributes, such as steel grade and thickness, will suffice and result in a much higher degree of forecast accuracy.
It is often non-intuitive for steel companies—where the culture is to work at a very detailed level of information—to create a planning model at a high level of aggregation. Many steel companies start out by believing that they will require several thousand product groups in order to be able to represent the complexities of their business. The reality is that planning at such a granular level is not manageable and product group numbers in the low hundreds result in a much more successful S&OP solution.
In contrast with S&OP, in the short-term planning horizon (typically the next few weeks or months), production planning makes decisions based on a relatively detailed description of a product that needs to be produced, for example, taking into account relevant product attributes, such as steel grade, width, length and weight. At this level of planning, it is important to recognize differences between material attributes in order to correctly plan their impact on resource capacity consumption and on material allocation decisions. Therefore, production planning is carried out at an end-product level of detail based on steel quantity (e.g., the number of tonnes) with no aggregation being used.
One of the key failings of many supply chain projects is the lack of attention paid to organizational impacts, change management and training. It frequently is assumed that merely implementing a new software tool will bring the desired business results.
To achieve the desired business objectives of a supply chain transformation, the future organization needs to be aligned carefully with the future supply chain processes. For example, in the S&OP process, there is the commercial (sales) view and the supply (operations) view (as well as others). Furthermore, verifying that the new supply chain organization reflects the appropriate balance and influence of these organizations in the various S&OP activities and decision-making processes is important.
Within the defined supply chain organization, it also is important to be able to define the key roles for people in the future supply chain organization, what responsibilities and accountabilities they will have, how communication will be performed, and how they will be individually measured.
Supply chain performance metrics
The principle of key performance indicators (KPIs) to measure the success of a supply chain project is a well-known and used concept. In addition to KPIs, however, there are a number of other indicators that also should be employed to support the success of a supply chain management project (see Figure 5), namely:
Key conformance indicators.
One of the main challenges in any successful supply chain project is to confirm that the plans being proposed by the software tools are actually being used to drive the business. For example, do the manufacturing shopfloor workers actually produce the planned production orders at the times proposed by the planning tool? To measure such adherence to the plan, key conformance indicators should be defined in the project.
The production planning process has generated a set of planned orders for production on a hot rolling mill for the next three days (the ‘planned quantity’). Based on this plan, the production schedulers have created a suitable hot rolling mill slab sequence (the ‘scheduled quantity’). The actual production over the three days is tracked on a cumulative basis and based on a number of conformance indicators that can be calculated. As can be seen in this example, while conformance to schedule is high (above 90 percent), conformance to plan is low (about 50 percent), indicating a potential disconnect between these two processes—as reflected by the relatively low schedule-to-plan conformance.
A further challenge in effective supply chain management is to counteract the variability resulting from people who are involved in the planning processes themselves. Again, to take scheduling as an example, often schedules may be created by different people on different days or shifts. Because, the people performing these processes typically have many years of experience in such tasks, they have their own subjective interpretations of what constitutes a ‘good plan’ or ‘good schedule.’ Therefore, to confirm business process consistency, it is necessary to define plan quality indicators, which allow the planners and business to determine objectively which of the alternative plans and scenarios being created are the most appropriate.
Delivering successful supply chain transformations
The successful delivery of a supply chain transformation requires a deep understanding of both business and technology impacts, and their potential consequences. By failing to address correctly factors such as those discussed earlier in this paper, steel companies may fail to unlock the full potential value of their supply chain, and in the worst case, may actually destroy value. To foster success when embarking on a supply chain transformation, companies should look to leverage wherever possible existing leading-practice design experiences and models.
Through its extensive experience working with many steel and metals companies in the world, Accenture has developed a patented business process management (BPM) framework for the metals industry that provides steel companies with an integrated model for defining leading-practice supply chain (and other business) processes. In addition, the BPM solution provides key performance indicators, organizational architectures and role descriptions that are relevant to each process area. The BPM model helps to reduce risk and improve delivery timelines by providing a common language and ready-made supply chain process architecture.
From an IT and software viewpoint, it also is important to understand the demands steel industry-specific requirements place on available software solutions, and how such tools should be deployed and configured to address the business needs and expectations. For advanced supply chain software solutions, such as those from SAP, the Accenture Advanced Enterprise Solution for Metals links the industry-specific, leading-practice BPM processes to a preconfigured planning solution built on the latest SAP technology, and is packaged with complete process documentation and industrialized implementation accelerators. In addition, AAES provides a number of industry-specific configurations and/or enhancements to core supply chain and ERP functionality that help metals companies to address their requirements.
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