Abstract
This paper considers the key factors regarding Supply Chain Usage in Business Intelligence. The paper analyses the role of Supply chain to reduce operating costs and be more responsive to customers. The goal of Supply Chain Intelligence is to enhance an executive’s ability to reason through business outcomes. The paper outlines the conceptual frame work, needs, challenges and software requirements of a Supply Chain Model.
Introduction
A supply chain is a system of organizations, people, technology, activities, information and resources involved in moving a product or service from supplier to customer. It is also known as, logistics network, or supply network. Supply chain activities transform natural resources, raw materials and components into a finished product that is eventually delivered to the end customer. In sophisticated supply chain systems, used products may re-enter the supply chain at any point where residual value is recyclable. Supply chains link value chains.
A supply chain can also be used to show how several processes supply to one another. Thus the term supply chain can also be applied to Internet technology, finance, and many other industries. A supply chain strategy defines how the supply chain operates in order to compete in the market. The strategy evaluates the benefits and costs relating to the operation. While a business strategy focuses on the overall direction a company wishes to pursue, supply chain strategy focuses on the actual operations of the organization. It also focuses on supporting and meeting a specific business goal.
A supply chain has three main parts:
- Supply: This mainly focuses on how, when and from where are the raw materials supplied for manufacturing,
- Manufacturing: It focuses on the conversion of these raw materials into finished products.
- Distribution: It focuses on ensuring these products reach the consumers through an organized network of distributors, warehouses, and retailers.
Supply chain is among the most complex and crucial functions. To measure the supply chain effectively, one should identify metrics that are appropriate for the organization and that will improve business performance. One cannot manage what one cannot measure. And the supply chain being one of the most important functions to manage it is important to measure it.
Supply Chain Management (SCM)
Another term associated with a supply chain is Supply Chain Management (SCM). It is the oversight of materials, information, and finances as they are distributed from supplier to consumer. The supply chain also includes all the necessary stops between the supplier and the consumer. Supply chain management involves coordinating this flow of materials within a company and to the end consumer.
The term Supply Chain Management arose in the late 1980s and came into widespread use in the 1990s. Prior to that time businesses used terms such as “logistics” and “Operations Management” instead.
Supply Chain Management can be divided into three main flows:
Product Flow: This includes moving the goods from a supplier to a consumer. It also deals with customer service needs.
Information Flow: This includes order information and delivery status.
Financial Flow: This includes payment schedules, credit terms, and additional arrangements.
Supply Chain Management (SCM) remains a high priority for manufacturers. This is because it helps to improve margins and retain and increase market share.
“Supply chain management remains at the top of the agenda for many enterprises today as a way to reduce operating costs and be more responsive to customers,” reports Jeff Woods, senior analyst at Gartner Inc., Stamford, Conn.
The success of supply chain management at this strategic level requires considerably more integration with other enterprise systems. Since many business targets and performance indicators are established in the budgeting process, efficiency demands that the planning, budgeting, sales and marketing, and SCM systems talk with one another.
Supply Chain Intelligence (SCI)
Today, more than ever, managers need tools to hat generate insights which would help them to make smarter decisions efficiently. To do so, they need to learn to ensure that Supply Chain performance supports their business goals. This very need of managers gave space to the evolution of Supply Chain Intelligence (SCI), a successful blend of Supply Chain Management and Business Intelligence.
SCI is fundamentally a predictive discipline that helps planners foresee events and anticipate trends. It is addresses numerous Supply Chain challenges. Analytical modeling techniques and optimization are at the core of Supply Chain intelligence. It is a new initiative that provides the capability to extract sense and analyze information about a Supply Chain. It has a broad mandate and provides a BI layer that compliments the SCM initiatives. SCI enhances an executive’s ability to reason through business outcomes. It prescribes the best course of action and helps the executive focus on the highest impact activities.
SCI in all regards is geared up to using SCM and ERP data as the basis for informed decisions.
SCI takes broader, multidimensional view of supply chain in which, using patterns, rules and meaningful information about the data can be discovered. The Supply Chain Intelligence provides accurate forecasts to improve the demand planning process thus giving a clear view of the future. It also reveals opportunities to reduce costs and stimulate revenue growth. It enables companies to understand the entire supply chain from the customer’s perspective. Before examining the supply chain of a particular business, it may be advantageous to understand the motivations behind supply chain improvements.
Difference between SCM and SCI
Supply Chain Management
- Largely about managing the procurement and production links of the supply chain.
- Transactional
- Tactical decision making
- Helps reduce costs through improved operational efficiency
- Records one state of data representing “now”
- Assists in material and production planning
- Quantifies cost of some materials.
- Can show today’s yield but cannot explain influences on it, so offers no help in improving it.
- Simple reporting
Supply Chain Intelligence
- Provides a broad view of an entire supply chain to reveal full product and component life cycle
- Analytic
- Strategic decision making
- Reveals opportunities for cost reduction, but also stimulates revenue growth
- Keeps a historic record.
- “What-if” forecasting based on historic data
- Enables an understanding of total cost
- Can drill into yield figures to show what caused the performance level, so you can improve it
- Collaborative environment with personalized monitoring of metrics
Levels of BI application in Supply Chain
With the advancement of technology at an exponential rate and the ferocious competition in the rapidly changing market, Business Intelligence has moved to the core of Supply Chain Management.
Most Organizations have different BI functions in IT department, Marketing Research and independent department. Timely information about market, customers and competitors stand crucial to meet the Supply Chain challenges. Business Intelligence value chain is an interrelated process of suppliers, manufacturers, distributors and customers. It uses the information and knowledge to pilot a company towards competitive success.
Business Intelligence is grounded in various supply chain activities and processes that serve as the sources of BI data and information. Vital components of value chain management are networking, enhanced intelligence analysis, awareness of the latest developments in data collection, and information analysis,
There are mainly four levels of Business Intelligence application in a Supply Chain Management, which are:
- Strategic Level: Strategic decisions are made at the top management level. To drive decisions Chief executives often require long term, historical, integrated information on environmental changes and industry trends that are combined with business performance. Insightful business decisions can create unprecedented success through adjusting Supply Chain direction.
- Tactic Level: At Tactic level, collective information is needed to provide visibility across multiple processes within a Supply chain. This facilitates actionable changes. Decision support systems are commonly used by the mangers at this level. Aggregated data across business units assist managers to make informed decisions, analyze business trends, and deliver promised services or products with a consistent quality.
- Operational Level: Operational Level Decisions require daily and real time data to satisfy customer demand on time. The line-manager is responsible for day-to-day business of a certain business process. Line managers use real time monitoring tools to access data and make timely decisions.
- R&D and Marketing Research Level: At R & D and data analysis level, professional staff members collect, organize and analyze data through data modeling and simulation. This to extracts supply chain information and uncovers knowledge of customers and competitors that are embedded in the supply chain process. They play a crucial role though they are not directly involved in daily decision making.
Thus, the presence of Business Intelligence not only enhances the efficiency of the Supply Chain but also aids in powerful decision making. Today, it has become a vital part of Decision-making at each and every level of Supply Chain Processes.
Need of Supply Chain Intelligence
There is a great need for Supply Chain Intelligence in the areas of strategic sourcing, production quality, warranty analysis, optimal distribution and demand management in an organization.
Spend Analysis – Procurement specialists can analyze trends over time, such as corporate spend history, budget performance, usage patterns and changes in supplier dependencies. SCI can highlight the way the commodities are purchased across affiliated suppliers, distributed to end consumers and affected by quality issues and warranty claims. It can thus leverage itself all through the contract negotiations,
Supplier Ranking – Ranking endows with an objective, repeatable and adaptable measuring system. It can reliably identify the best suppliers for the organization and respond effectively to changing business conditions. By using dynamic, weighted averages to add balance and flexibility, SCI can objectively narrow, measure and rank suppliers based on your specific needs.
Organizational Performance – SCI can introduce customer-specific business rules and models to emphasize exceptions to the agreed processes. It can drive organizational performance towards predefined business goals and strategies.
Trend Monitoring – Using SCI, procurement professionals can monitor key supply chain processes in real time. For direct goods, it may consist of quality and on-time delivery, whereas for indirect goods, it may consist of service-level factors. It can highlight the trends in an explicit supplier criterion that matter to specific audiences. It can thus help minimize every negative impact on the supply chain process.
Proactive Investigation – Automated analytical “filters” can alert one to the changing trends like – at-risk suppliers or emerging warranty issues These practical alerts will include e-mailed reports or graphs, a changed indicator in the scorecard, or even notification through a mobile device such as a phone or pager. It can thus provide visibility and lucidity.
Score carding – To visually present time-based key performance indicators (KPIs), SCI can provide a concise “dashboard”. A scorecard contains measures that can assist in describing external performance ant internal performance at all levels of the supply chain process.
Optimization – Optimization in the supply chain takes into account the “total cost to supply,” It comprises of, namely, quality/warranty issues, distribution from post-manufacturing to the consumer, inventory/service levels and trade promotions. Ranking considers each supplier in isolation and optimization examines suppliers in the cumulative way. This can thus reduce risk exposure and purchase costs and can increase negotiating leverage.
Product Profitability – This can support category management by item basis. It does so by looking at the impact of changes in product mix, distribution channels, shelf storage and other factors through multi-supplier networks…
Scenario Planning – It can assess all the options through “what-if” situations and can help find opportunities. It can also identify the potential for new and more efficient processes.
Demand Prediction – High-performance forecasting capabilities can provide accurate demand and promotions planning. The forecasts are based on data from ERP, SCM systems. It also considers a multitude of other internal and external information sources, with highest degree of data quality. It can
- Reduce inventory levels
- Monitor and improve service levels
- Predict purchase patterns
- Provide flow projections
Benefits of Supply Chain Intelligence
For several years Supply Chain Management and Business Intelligence have been top-of-mind concepts. With clear advantages offered by Supply Chain Intelligence the integration of SCM and BI tools are gaining acceptance across the globe. Through their union, companies can begin to benefit by identifying opportunities to enhance business performance.
It offers an array of advantages:
- SCI gives complete visibility into all orders, shipments, status, inventories, and production output and consumption rates across the extended supply chain. Visibility includes visibility of processes (collaborative planning, demand forecasting, inventory control, balancing of resources with requirements, product tracing) and visibility of relationships (CRM, contractual compliance).
- With SCI, information can arrive before the goods, allowing the recipient to prepare for their arrival. Moreover, communication can be multipoint and can leap-frog members in chain.
- SCI allows measurement and analysis of specific supply chain activities that create profitability for the chain. For example, measures of the value of excess inventory, total cycle time, defect-free goods to total goods, and demand forecasting accuracy can lead to performance improvements and cost savings.
- SCI provides single window for all data reporting and analysis which ensures that the reports or figures accessed from anywhere are uniform and provide the same data.
- It also provides a consolidated view of the company including its supply chain. This helps reduce the traditional limited view of the supply side of operations.
- Through this approach BI system also acts as an intermediary between the organization’s SCM and CRM systems. This move helps the company manage its supply to match the customer demands. It can also help the company tailor product attributes to match changing customer needs.
- While the BI can help business managers evolve a new product line, the SCM helps coordinate with the suppliers to meet the changed production requirements.
Other than the above mentioned benefits SCI also has several specific advantages in:
All Operations of the Supply Chain
- Reduces total cycle time from supplier to consumer
- Provides supply chain visibility
- Caters product traceability
- Balances resources with requirements
- Enhances communication, collaboration, planning and forecasting
- Analyzes supply chain performance
Procurement
- Measures supplier performance and negotiates performance-related contracts
- Provides sourcing of new suppliers globally
- Simplifies and streamlines of procurement operations
- Shares master production schedule with suppliers so that suppliers can meet production needs
- Reduces purchase price of raw materials
Production
- Administers just-In-Time scheduling of jobs and production
- Accommodates order prioritization
- Detects critical events using alerts
- Improves product quality by tracing defective goods
- Develops collaborative new products.
Warehousing
- Reduces raw material inventory levels
- Reduces finished goods inventory levels
- Prepares vendor managed inventory
- Arranges cross-docking of shipments to allow goods to move along the supply chain without the need for warehousing
Logistics
- Measures of delivery performance
- Provides sourcing of new logistics providers competitively
- Gives room to just-In-Time deliveries
- Predicts of delivery outcomes for each transport segment
- Fulfillment
- Forecasts customer needs
- Provides real time response to customer demand and feedback
- Proactively replenishes before stocks runs out
- Reduces price markdowns and returns
- Measures product performance by retail location
Bringing supply chain management and business intelligence together across the enterprise is challenging. But it enables far more significant benefits than the sum of the parts. Supply chain management and business intelligence have been promoted so far in namely FMCG, retail, resources, manufacturing or financial services industry. But it has been done so in isolation.
“In isolation, these two concepts can only affect that part of a business at which they are directed”, says Katzen, Senior Executive, Accenture.
An integrated supply chain intelligence system will bring a marked increase in the visibility of each link in the supply chain. Therefore success and failures will become equally visible to all parts of the business in a rapid interval of time.
Challenges of Supply Chain Intelligence Implementation
Implementing SCI is a multifarious process. There are a number of challenges implicated in integrating information, systems and partners across the supply chain.
Data Integration
The assimilation of data from legacy systems, varied platforms and different database technologies that do not “speak the same language” makes data integrity tricky. Therefore data integrity can arise as a major issue.
Supply chains are made up of associates who do business in incongruent ways. This greatly affects the complexity of SCI projects. Moreover several factors must be integrated into the data warehouse. They are
- The usual structured data from transactional systems
- The unstructured data from supplier and customer relationships
- Third-party research data such as market trend
Data integration is the number one challenge in SCI implementations. Integrating data from multiple sources is very complex and the cost of the extract-transform-load (ETL) process is often underestimated.
Increased Quantity of Data
Apart from the company data, data from the extended supply chain has to be fed into the data warehouse. . The consequence of this comes out as a tremendous increase in the amount of data that needs to be incorporated and stored.
Business Alignment
Trust and commitment as well as open channels of communication between all the partners are a must for an SCI implementation to be successful. These factors are critical as both the flow of information and the flow of materials must be optimized to reduce the total cycle time from raw material to sale of goods. This requires partners in the supply chain to “think and act as one”. Changes to business thinking and re-engineering of business processes to ensure uniformity across the chain must also include smaller partners.
Supply Chain Volatility
Supply Chains are turning out to be increasingly unstable in a dynamic global environment. SCI actually contributes to this by allowing companies to observe the performance of partners and switch to added profitable relationships. SCI implementations have to deal with constantly changing sources of data from new supply chain partners as well as new business cultures.
Security Issues
SCI needs partners across the supply chain to have easy access to information. This situation creates a security dilemma. The data in the enterprise data warehouse is often valuable, highly sensitive and t must be shared in order to create efficiencies across the chain.
The need for better supply chain intelligence has created challenges for established vendors of BI platforms and SCM applications. Some have made progress. Business Objects, Cognos, Oracle (PeopleSoft EPM) and SAP are now incorporating prepackaged supply chain-centric analytical applications.
Cognos supports distributed decision-making with business event management alerts. Hyperion provides master data management services. However, no BI vendor supports trading partner visibility and detailed supply and demand scenario planning. This requires the integration of trading partner data and the mixing of planning information with transaction information. For these needs business users must turn to players like IBM, Kalido, SAQQARA and Tibco for trading partner MDM; Interlace, Kinaxis or SymphonyRPM for scenario planning; and RiverOne, see Commerce or Viewlocity for trading partner visibility.
Software Requirements for Supply Chain Intelligence
Software that supports SCI has several base requirements such as:
Packaged Analytic Application – Ideally, SCI is facilitated by a packaged analytic application through focused functionality for manufacturing specialists. This way, the prepackaged application delivers high value out of the box without need for undue amounts of development. This would also be the case with a general analytic platform. Furthermore, a packaged analytic application for SCI encapsulates best practices for manufacturers and others involved in supply chain issues, whereas basic critical platforms cannot. An analytic application for SCI should include functions for analyzing historic supply chain and manufacturing performance. It should also facilitate analysis that helps to forecast material and production line needs.
Professional Services – A packaged analytic application (for any purpose, not just SCI) can never be as firmly packaged as applications for ERP, CRM or SCM. This is because source data required for analysis varies greatly from one corporation to another. The data integration process is different for each deployment of a given analytic application. In addition, each corporation has a unique collection of business entities, so the data model that represents these in the analytic application must be customized for each deployment. Hence, a software vendor providing an analytic application for SCI must also provide a healthy mix of professional services to aid with customizing the application for each customer, as well as providing training, support and project management. The consultants should have experience and training in manufacturing, supply chain domains and technical areas such as data warehousing and analytic application development.
Domain Expertise – The primary value proposition of any analytic application for SCI is the domain expertise it encapsulates. Therefore, anyone evaluating an SCI application should look for proof of domain expertise in the product as well as in the vendor. For instance, the software vendor should have executives, developers and consultants who have demonstrable experience and successes in manufacturing (both process and discrete) and other supply chain-intense industries. The application should have functions designed specifically for SCI, such as data models, analytic algorithms for product life cycle information, shop floor data and parametric test equipment data (whether from the factory or the field).
Build versus Buy – A packaged analytic application for SCI is faster to install and customize (months instead of years) than built-from-scratch supply chain decision support solutions. Besides, many organizations decide to build their own applications because they cannot find commercially available ones that satisfy their requirements. However, the customization process of an SCI application ensures that most of the customer’s unique requirements are met.
Supply Chain BI modeling
The demands of our global economy are forcing companies and entire supply chain to adopt more flexible and responsive modes of operation. Interdependence of companies and economies, and the rapid and unexpected pace of events call for responses from companies that are faster and well thought out. In order to achieve SCI objectives we need a supply chain-wide business excellence model that will provide consistent framework for establishing, modeling, managing, measuring, and improving supply chain processes. SCI model is based on the global supply chain excellence which unifies:
- Business domain (modeling, people, existing supply chain and business process models, best practices, and quality management models),
- Functional domain (information technology infrastructure, modern object-oriented development methods, and patterns)
- Methodology for supply chain process integration.
Conclusion
These days, it seems globalization touches every business. It is changing the way manufacturers and distributors operate their supply chains. Outsourcing, contract manufacturing, shorter lead times and more regulations are facts of life. Organizations must identify and define the requirements for the actionable information that are needed to manage and improve each process of the integrated supply chain.
Manufacturers are benefitting by using business intelligence to enhance the integrated supply chain. Business intelligence project teams should collaborate very closely with the supply chain management process design and operations teams. This ensures that their informational requirements are clearly understood and designed into the solution.
Companies that do use supply chain BI to enhance profits and coordinate promotions are able to improve sales planning and supplier performance, and, as a result, they gain flexibility to meet changes in demand.
The demands of our global economy are forcing companies and the entire supply chain to adopt more flexible and responsive modes of operation. Both the interdependence of companies and economies, and the rapid and unexpected pace of events call for responses from companies that are faster and also more well thought out than what was required in the past.
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