Multi-enterprise collaborative decision support system

doi:10.1016/j.eswa.2012.01.029

Expert Systems with Applications

Volume 39, Issue 9, July 2012, Pages 7637-7651

https://doi.org/10.1016/j.eswa.2012.01.029 Get rights and content

Abstract

The increasing level of collaboration among firms has necessitated the emergence of decision support tools that span firm boundaries. This essentially translates to decision support systems that seamlessly communicate and operate with disparate system characteristics. We propose and develop a multi-enterprise collaborative decision support system for SCM that aids in this process. The multi-enterprise collaborative decision making and support proposed and implemented in this study helps decision makers within and across organizational boundaries to generate more accurate, effective and timely decisions. We contend that this line of research is being well demonstrated in practice, and there is support for organizations requiring such support in their decision making environments. This study contributes to both the fields of ERP, DSS, and the decision making and support aspect of multi-enterprise collaboration. Decision makers in a multi-enterprise collaborative environment need flexible systems that allow for seamless integration among all members of organizational supply networks without being dependent on the knowledge of the users. Within such a system, decision makers from all across supply networks can access, and flexibly use decision making components, explore a range of what-if scenarios and make the best decision for their organization and their customers, partners, etc. based on the results.

Highlights

► We propose and develop a multi-enterprise collaborative DSS for SCM. ► MECDSS helps decision makers within and across organizational boundaries. ► MECDSS helps seamless integration among organizational supply networks. ► Decision makers can access and flexibly use decision making components. ► MECDSS helps decision makers explore a range of what-if scenarios.

Introduction

In the business environment that exists today, efficient and effective decision support is essential for accurate decision making. Decision makers do not have time to locate the necessary data or information in a data warehouse application, other data applications, or worse still an ERP system. They demand decision support tools which support them in coming up with the best alternative to problems or business requirements. In addition, these decision support tools and applications need to be open and flexible enough to not only provide support within their own organization, but also beyond the boundaries of the organization. This multi-enterprise collaboration is increasingly becoming a vital element in the decision support process because decision making should ideally have no boundaries. Decision makers within an organization should be able to span right across their entire supply network and collaborate with other decision makers in order to obtain the right information, knowledge, tools, technologies, etc. that will assist them in coming up with the best decision for their organization and even in some cases the supply network as a whole.

There are a host of applications that serve some aspects of this problem. However they are expensive, and are often provided as part of a suite of applications from a single vendor such as SAP and Oracle. There is a need for a decision making lifecycle that can be applied to any business problem or requirement. In addition, this type of lifecycle should be supported by flexible and open decision support frameworks and architectures that allow decision makers within and across organizations to leverage their supply networks and take advantage of all the tools, technologies, standards, and systems available in order to make the best choice.

Organizations and their decision making processes are increasingly becoming multi-enterprise collaborative (MEC) in nature. However, a majority of academic and commercial research, frameworks, architectures, and systems are focused towards the transaction processing aspect of multi-enterprise collaboration. More recently, vendors including Microsoft, SAP and Oracle have introduced tools and systems that support the decision support side of MEC. The shift of marketplace applications and academic research towards this area of research is still at its early stages and perspectives and insights are continually being gained as new applications and implementations are rolled out.

Decision makers within organizations and across supply networks need the ability to utilize decision making components (e.g., data, models, solvers and data and process visualizations) to integrate business needs with appropriate technological environments. This is critical in dynamic environments where disparate organizational systems and personnel interact in decision-making processes. Research and implementations need to address decision support dimensions to support multi-enterprise collaborative decision making and support. These include heterogeneity in terms of breadth and depth of data, complexity in terms of models, solvers and data/process visualizations, distribution with regards to reach and range, versatility of domains and paradigms, flexibility, reusability and extensibility.

Although recent research has generated contributions in terms of framework, architecture, and implementation, there are still areas where gaps remain. These include the following:

•
A majority of existing architectures are platform-dependent simply because they require components that operate in-concert with them to be developed on the same operating platforms as the architecture itself. This reduces their flexibility, versatility and extensibility.
•
They lack the ability to provide true flexibility with regards to the integration of decision-making components. They instead require an Application Programming Interface (API) that is limited in nature to achieve integration with other systems across organizational boundaries.
•
Because of its high complexity, flexible mapping between decision making components to support ad-hoc multi-enterprise collaborative integration in a changing business environment is not common.
•
Reusability of decision making components in order to reduce the need for expert knowledge is also limited.
•
Heterogeneity of data in terms of being able to not only connect to any ERP system but also any other system/database is not as flexible and open as it should be. For example, multi-enterprise collaborative decision-making is made more difficult as vendor-specific ERP applications do not allow full integration with rival applications, making it difficult to have complete visibility resulting in not being able to make the best decision for the problem at hand.
•
There is a limitation in terms of the type of communication standards/protocols that are employed to connect to other tools/ applications/systems that reside on different platforms in other organizations across supply networks. For example, Oracle BPEL Process Manager is limited to the use of Web Services only, as a service provider to integrate decision-making processes across multiple enterprises.
•
Finally, frameworks, architectures and implementations lack the support for a generic multi-enterprise collaborative decision-making model and lifecycle that can be applied to any paradigm or platform.

We focus on two equally important generic objectives from which specific objectives are derived. The first is to design a flexible framework and architecture that aids decision making activities within and across organizations. The second is to illustrate the flexibility and validity of the framework and architecture designed by implementing it via a Multi-Enterprise Collaborative Decision Support System (MECDSS). These generic objectives have five specific objectives:

1.
Identify and define appropriate and accurate system dimensions with respect to decision support.
2.
Investigate ways and means by which current DSSG and Specific DSSs do and do not address these system dimensions, from the perspective of multi-enterprise collaboration.
3.
Leverage the strengths of existing frameworks, architectures, and implementations to formulate and propose a MEC decision support model, decision making lifecycle, MECDSS framework, and a MECDSS architecture that addresses some of the gaps in the decision support dimensions.
4.
Implement the proposed model, lifecycle, frameworks, and architecture via a specific scenario using a relevant implementation platform that is able to utilize appropriate decision components.
5.
Evaluate the proposed model, lifecycle, framework, architecture, and implementation environment against the original decision support dimensions.

To this end, this paper contributes the following to the selected area of research:

1.
Identification and synthesis of problems and issues with regards to decision making and support in the area of multi-enterprise collaboration.
2.
Identification of the requirements for the design of an open and flexible system that overcomes the identified problems and issues.
3.
Proposal of an open and flexible multi-enterprise collaborative decision making and support model and lifecycle process. The lifecycle process should guide decision makers from the identification of problems right through implementation of the resulting system.
4.
Design of a domain-independent multi-enterprise collaborative decision support conceptual and system framework, and architecture that overcome the problems identified in (1); fulfill the requirements for an open and flexible multi-enterprise collaborative system identified in (2); and support the multi-enterprise collaborative decision support model and lifecycle proposed in (3).

Section snippets

Multi-enterprise collaboration

Firms face a variety of demands from an increasingly competitive marketplace. These demands are forcing decision makers to share information beyond the confines of their internal environment (e.g., Jinhua and Xiangyang, 2006, Liu, 2007, Rahman et al., 2010). In order to stay competitive, we believe firms need to address a number of areas. First, firms need to share information with their supplier-facing partners. Second, they need to gather information from their customer-facing partners (i.e.

Multi-enterprise collaborative architecture

More and more, companies are looking at Service Oriented Architectures (SOA) and their accompanying interfaces as an architectural blueprint and set of standards for addressing the integration requirements involved in creating multi-enterprise collaborative applications (Yuen, 2010). The Business Process Execution Language (BPEL) for Web Services has become the cornerstone of SOAs. This addresses common application requirements within and across organizations in an open, flexible, and standard

Problems, issues, and requirements for multi-enterprise collaborative decision making and support

We first identify the problems and issues drawn from a survey of commercial and academic DSSs and DSS Generators that are designed for decision support. The section concludes by drawing from these problems and issues in order to come up with a set of requirements for multi-enterprise collaborative decision making and support. The following are the problems and issues identified through the systems survey:

•
Domain and paradigm versatility are dimensions that are not addressed well by most systems.

Implementation domain

We consider a Supply Chain Management scenario to the implementation of the MECDSS. Specifically within this domain, a supplier selection scenario is implemented using the implementation platform. According to Probert and O’Regan (2002), Supply Chain Intelligence systems complement the capabilities of ERP systems, and SCM applications, and build on them with respect to three key areas including rich and deep analytical capabilities on cross-functional supply chain areas, the integration of

MEC decision making and support model

We present a MECDSS conceptual framework that represents a high-level look at how the integration of ERP systems and DSSs can help set the foundation for multi-enterprise collaboration and decision support. This conceptual framework is shown in Fig. 3. This MECDSS conceptual framework consists of a supply network which builds on the ideas proposed in the MEC decision support model but adds a high level system/technology side to it. The internal environment (which may be the decision making

Design of the MECDSS architecture

Aside from an implementation of a system, one of the lowest levels of abstraction that can be presented when discussing information systems is an architectural diagram. In this section we present the MECDSS architecture (Fig. 5) and discuss each of its component parts that combine to make it work.

The database layer sets the platform for the collection and maintenance of the raw data received by the firm. Typically, an enterprise (depending on its size) will have a number of databases that are

MECDSS architecture -- implementation

There are two parts that make up an implementation environment: the implementation platform and the implementation domain.

MECDSS for Supply Chain Management

We chose to demonstrate our concepts in a Supply Chain Management (SCM) environment since it neatly touches a number of points across the supply network and truly illustrates the power of multi-enterprise collaborative decision making and support.

Conclusion

We conclude that multi-enterprise collaborative decision making and support will help decision makers with and across organizational boundaries to make more accurate, effective and timely decisions. In particular, through the power of Web Services offered by the Oracle BPEL Process Manager tool, we illustrated an aspect of the MECDSS framework and architecture, and how it supports the decision making lifecycle. In addition, we were able to address some of the requirements in the area of

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Multi-enterprise collaborative decision support system

Abstract

Highlights

Introduction

Section snippets

Multi-enterprise collaboration

Multi-enterprise collaborative architecture

Problems, issues, and requirements for multi-enterprise collaborative decision making and support

Implementation domain

MEC decision making and support model

Design of the MECDSS architecture

MECDSS architecture -- implementation

MECDSS for Supply Chain Management

Conclusion

What are enterprise systems and why do they matter?

Intelligent decision support methods: The science of knowledge work

Web services architecture overview: The next stage of evolution for e-Business

IBM developerWorks

The study on multi-enterprise collaborative resource planning based role-driven component-oriented methodology

Proceedings of the IEEE International Conference on Industrial Informatics

mySAP.com Industry Solutions: New strategies for success with SAP’s Industry Business Units