An in-depth review of a conceptual technology model of a supply chain visibility hub
As economic success relies more and more on superior agility and collaboration capabilities, marketplace competition is being won and lost on the supply chain front.
Companies able to control supply chain costs, satisfy customer demand and bring products to market faster than their competitors succeed. At the same time, the disparity between top-performing and average organizations widens.
Clearly, despite widespread efforts to enhance operations among companies and their suppliers, partners and customers, a great deal of potential benefits and areas for improvement remain in supply chain operations, as yet untapped. Over the past several years, a wide range of technology initiatives have been implemented to improve supply chain processes. However, many have failed to live up to expectations or realize their full potential. There are several reasons for these shortfalls, including a lack of visibility into supply chain events; poor understanding and communication of business processes (both internally and with trading partners); and, most significantly, insufficient data quality.
This article will discuss how companies can implement a supply chain visibility platform as a foundation for improving and extending the return on investment (ROI) of existing supply chain systems. In addition, a visibility hub can drive more efficient collaboration among organizations, their customers, suppliers and trading partners. Finally, this article will show how companies can make dramatic enhancements to operational efficiency, without spending a great deal of time or money on new technology.
There are numerous definitions for supply chain visibility usually the description depends on the viewpoint of the particular vendor or industry analyst. Most supply chain practitioners, however, understand that by any definition, visibility into processes and data is critical today, and will only increase in importance in the future. For the purposes of this paper, supply chain visibility is defined as:
The integration point that senses and responds to process changes within the supply chain and collects, cleanses and disseminates supply chain data with trading partners and internal departments.
This point or hub exists on the boundary of the enterprise, integrating internal systems and extending those systems and business processes to supply chain partners and customers.
The Importance of Data
Each of these systems contains data that is critical to its individual business process. More importantly, this same data may also exist in varying levels of completeness in other systems and will be employed by end users of these systems to make informed business decisions. Companies are constantly challenged to synchronize data across disparate systems. This effort includes developing a process to push relevant data to the proper systems, identify discrepancies and correct errors. Process support is imperative and allows users to make timely decisions with confidence.
As a company matures, it becomes increasingly important to manage and improve this process. The first step in accomplishing it is to measure internal capabilities against a maturity model that can help identify an organization's collaboration readiness.
Many successful organizations will feature some capability in all categories. However, most have not yet achieved pervasive process and systems integration and collaboration.
Each integration capability is explained here:
* Companies at Level 1 are beset by siloed processes among different departments and supply chain systems. These companies attempt to drive out cost or enhance revenue at the department level, rather than through integrated processes.
* Level 2 companies have integrated processes across departments, so they feature some level of demand planning, which drives sourcing, logistics, sales, etc.
* Level 3 companies begin to enable further process integration by linking disparate systems and introducing technology to automate and standardize processes. They are also introducing true sales and operations planning. In addition, the organization begins to sense changes in operating conditions and responds proactively.
* At Level 4, an organization aligns business processes with key customers and suppliers. Additionally, improvements gained by aligning internal processes are externalized. This collaborative capability drives out cost and improves service levels through demand driven planning with key customers and suppliers by sharing forecasts, demand signals and key business events.
* Level 5 companies enable further process alignment with customers and suppliers, again by automating execution of processes and using technology to monitor business events and provide exception alerts. They also share information across their supply chain transparently.
As the processes are managed and visibility increases, results can be far-reaching within an organization. With quality data being properly captured, processed and stored, it can be used by all levels of an organization, improving execution as well as operational, tactical and strategic decision making.
Value Proposition of Supply Chain Visibility
Before discussing the hub's conceptual architecture, features and functionality, it is important to examine the value proposition for supply chain visibility. In general, supply chain improvement opportunities abound. Most can be placed into four distinct categories: revenue growth, inventory cost reductions, transportation cost reductions and reduction in distribution costs. The value proposition depicted in Table 1 illustrates the overall improvements possible within a typical supply chain by addressing its weaknesses and limitations.
New or upgraded systems may be necessary to realize full benefits. However, a significant ROI can be realized by expanding visibility across existing systems. Doing so results in increased awareness and extended collaboration opportunities, and can include:
* Identifying and including new data sets
* Improving the quality of existing data sets
* Using existing data sets in new ways
* Integrating siloed processes and systems more tightly
* Improving measurement and monitoring of process and system performance.
Of course, exact opportunities will vary by company, but specific examples that typically result in positive returns include:
* Sharing demand data with customers and suppliers
* Enabling advance shipment notifications and visibility into in-transit shipments
* Proof of deliveries
* Developing more accurate visibility into customers' inventory levels
* Tracking partner compliance.
Although obviously not exhaustive, these examples represent opportunity for continuous improvement. They do so because integrating visibility and collaborative capabilities with existing supply chain systems improves an organization's performance, and thus its ability to achieve these results.
Having established a basis for defining a supply chain visibility value proposition, and having determined how to measure the effectiveness of an organization's collaborative readiness, it is possible to describe the conceptual technology model of a supply chain visibility hub. It is also important to remember how to handle inherent data quality issues that arise during integration efforts.
The visibility hub comprises three main pieces:
1. The trading partner network
2. The event manager engine, which supports alerting, visibility and collaboration
3. The visibility data repository, which supports execution and planning.
Trading Partner Network
The trading partner network provides physical connections and interfaces between supply chain partners, as well as several other critical features, including data validation and partner compliance. The physical network itself consists of several technologies, which:
* Manage physical connections with trading partners, and monitor and report on their conditions in the network.
* Provide for secure transmission of electronic data interchange (EDI) and other data over the Internet by using AS2, HTTPS or Secure FTP. The network should also support transmission via value-added networks (VANs).
* Support service-oriented architectures to exploit Web Service access to logistics services providers and adapt to legacy applications.
* Deliver Web forms to capture and transmit information globally for trading partners who lack sophisticated systems or are low-volume providers.
The network is responsible for validating the transmission of data at two levels the structure of the transaction and the content of the transaction. The structure of the transaction deals with how well the message adheres to any standard or agreed-upon format. For example, EDI advanced shipment notification 856 has all required fields and is a properly structured X.12 VICS 856 ASN. The system should have the capability to collect non-structured data such as forecasts from the sales team, or operational capacities from manufacturing or distribution.
Validating transaction content is more complicated and deals with its business value.
This is the most critical step in the network, for here the rules of data quality are enforced in a central location before data is moved into business applications. Data quality rules are applied to:
* Validate codes
* Enforce required fields (required for business content, not the standard being used)
* Normalize time zones and currencies
* Validate transaction dependencies and event sequences.
Moreover, any rules engine that validates content must also be able to alert a human who can investigate data integrity questions. If a transaction is critical to downstream systems, the workflow needs to drive a path-to-resolution process that will enable an alert to correct data errors and process the transaction. Data owners and data stewards must be identified and are responsible to monitor and execute processes that ensure data quality.
It is also recommended that key performance indicators and scorecards are developed for all trading partners, so the quality of information sent can be measured and tracked. This has proven to be one of the easiest ways to improve data quality and should be part of any partner compliance program.
For example, a large retailer was able to drive its data quality metrics with trading partners to 98 percent. It did so by clearly defining standard operating procedures for suppliers, using scorecards to measure effectiveness and applying incentives for data quality. Incentives included penalties for non-compliance, but more importantly, also featured rewards like early payment for meeting data quality targets. The program was put in place by a joint effort from Sourcing, Logistics, IT and Inventory Management.
The event manager is the next part of the application architecture. It is designed to increase confidence in supply chain planning predictions by continuously monitoring certain planned events, and eventually comparing the plan to the actual event. The event manager captures all event messages as they occur and processes them against a planned set of events. It performs several important functions, including:
* Event management
* Path to resolution
* Alert management
* Collaboration and integration.
Key supply chain events are typically planned (either manually or with a decision support system). With increased visibility, these events can be monitored closely by updated event messages, which make use of the timeliest information. An event message can represent a revised prediction of a planned event, or the actual execution of an event. By continually capturing event messages, the event manager allows supply chain partners and key stakeholders to gain visibility into an event's actual status. This increases their ability and effectiveness to manage the pipeline, because decisions are made on timely information not just the plan. Visibility not only exposes an issue, but pinpoints its cause, enabling a more focused path to resolution.
By using event messages, along with defined business rules (e.g., a revised date falls after a planned date), alerts can be generated and sent to appropriate parties, so actionable items can be identified and dealt with quickly. Alerts can appear in a variety of forms, such as an e-mail, text message or simply a color coding on a user interface. For example, a buyer may want to be notified via e-mail when an ASN arrives featuring a stock-keeping unit (SKU) quantity that differs significantly from what was ordered.
The architecture of the event manager enables integration with internal systems and maps business processes across the organization's external boundaries. The event manager masks external processes from internal processes and systems, easing the transition to a collaborative environment. Complex supply chain processes can be mapped to include design collaboration, request for quote/request for proposal (RFQ/RFP), purchase order management and demand signaling, based on point-of-sale data. By linking these processes, a total supply chain picture can be created and monitored from customer to supplier to service provider and back to customer. Visibility across the total supply chain tightens integration between individual systems by giving each access to the actual status of events on which it depends.
Visibility Data Repository
Finally, data collected in the visibility data repository is integrated into existing supply chain applications, data marts or a corporate data warehouse. The visibility repository provides data to execution and planning systems, thus improving performance in supply chain execution and operational planning. It can also accumulate supply chain execution results and historical data for longer-term tactical and strategic decisions. With all supply chain stakeholders working from a common data source, decision making and planning can realize significant improvements.
The visibility hub centralizes reliable information and business processes, thereby empowering a company to make informed operational, tactical and strategic decisions.
Where to Begin?
Clearly, this white paper describes a large, complex implementation. Knowing where to begin is often a significant challenge. In general, a crawl, walk, run strategy is the best method to implement a supply chain visibility project.
Start with a business process assessment and data strategy to determine the organization's preparedness to implement such a complex project. During this phase, it is important to develop high-level metrics to understand how well a process performs and to determine opportunities and objectives. This data can be used to develop a graph of processes that show returns-versus-risk, which can help establish implementation priorities. Low-hanging fruit can be harvested quickly and easily, while other opportunities may require careful planning and execution. Assessments should be scoped as eight- to 12 week projects, with full-time resources committed.
Implementation phases should be scoped in 12- to 16-week increments, although some complex processes may take longer. Large projects should be broken into small, incremental and easily managed components. This not only allows a more focused approach, it also enables an organization to realize incremental returns quicker.
Companies should develop key metrics for such a project, including critical success factors and key performance indicators for trading partners and internal processes. Doing so enables an organization to monitor its visibility implementation continuously, address problems and identify areas for improvement.
Sidebar: Defining the Value of Data Quality
Over the years, numerous systems have been implemented to improve supply chain performance. However, because of poor data quality, potential ROI has not been realized.
A focus on data quality is core to any visibility hub project. With superior data, the results described in this paper can be achieved through a continuous improvement campaign that incorporates all departments, and includes trading partners.
Data visibility becomes valuable when integrated with existing supply chain systems and other legacy applications. Study after study has shown that inferior data quality leads businesses to make poor decisions, hinders returns on systems investments and thwarts user adoption. A study (by the Data Warehouse Institute) determined that poor data quality cost businesses over $600 million annually.
Can Data Quality Be Defined and Measured?
It is useful to define data quality in terms of three key measures: completeness, accuracy and timeliness. Data is complete if all required elements are present to give value to a business transaction. Accuracy measures quality of content. In other words, are the data elements present in the transaction correct? Timeliness can be calculated by whether a transaction arrived in time for it to be actionable. Trading partner data becomes valuable in a typical visibility application when data meets these criteria more than 90 percent of the time.
Where Does Data Go Bad?
There are numerous ways data can be corrupted or misinterpreted. Data that comes from external organizations and various other sources will often turn up in a variety of formats.
For example, data can arrive from many external organizations, such as outsource manufacturers, logistics service providers and transportation companies, customers, and others. Much of this data may be created manually, or feature semantic differences that can cause confusion.
Transaction sequence errors can occur as well. For example, a shipment update is received before an advance shipment notice is processed. Change control in trading partner systems also impacts data, as does use of improper code tables.
In addition, standard operating procedures may not be communicated or understood well by trading partners, which can also lead to incomplete or wrong data. In short, supply chain data emanating from another organization is always suspect.
About the Author: With more than 27 years of experience in IT, software development and management, Mark Carleo is a recognized industry leader, entrepreneur and supply chain expert, as well as the leader of Collaborative Consulting's Supply Chain Practice.
Carleo co-founded an application service provider company in the supply chain visibility market. Earlier, he was a partner with a large, global professional services organization, with a focus on consumer and industrial products. Carleo has extensive experience in distribution and warehouse management systems, material-handling equipment and systems, logistics, supply chain management, and outsourcing. He also serves on the board of advisors at a start-up RFID company.