A management framework for performance management …

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TITLE OF THE PAPER: A Management Framework for Performance Management of Integrated Logistics Operations

Annual Conference of POMS, Chicago, IL, April 29 - May 2, 2005.

Author’s Name: Marco Busi


1. Norwegian University of Science and Technology, Department of Quality and Production Engineering

2. SINTEF Industrial Management, Department of Economics and Logistics

Address: S.P. Andersens v. 5, 7491 Trondheim, Norway

E-mail : marco.busi@ntnu.no

Phone: +47 92618768

Fax: +47 73597117

Co-author’s Name: Jan Ola Strandhagen


1. Norwegian University of Science and Technology, Department of Quality and Production Engineering

2. SINTEF Industrial Management, Department of Economics and Logistics

Address: S.P. Andersens v. 5, 7491 Trondheim, Norway

E-mail : Ola.Strandhagen@sintef.no

Phone: +47 73593800

Fax: +47 73597117

A management framework for performance management of integrated logistics operations

Marco Busi, Jan Ola Strandhagen

Marco.Busi@ntnu.no, Ola.Strandhagen@sintef.no

Department of Production and Quality Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

SINTEF Industrial Management, Trondheim, Norway


While companies are moving towards stronger collaborative relationships, performance management research is not keeping up the pace with this shifting focus. Practitioners’ dissatisfaction with today’s performance measurement systems (PMS) resides in their need to move from local to global focus. The objective of this paper is to define a framework that practitioners could use to monitor extended logistics operations’ performance. The rationale is a general lack of understanding of what collaboration means and implies on development of appropriate PMSs. The outcome is the management framework including: a collaborative enterprise wide PMS model; customizable lists of key performance indicators (KPIs) and related selection frameworks; a PMS design process. The authors discuss how the framework supports supply chain management (SCM), contributing to knowledge and supporting practitioners acting upon the emerging knowledge. This research employed action/constructive research strategies: the paper is based on major contributions from a wheel-suspension manufacturer and the feedback given while using the framework


Market and production globalization and the network- and knowledge-based economy are triggering continuous changes in the way companies are organized and the way they do business. After four decades of focusing on optimization of internal operations, companies have realized that they have to invest in integrating their internal operations with those of suppliers and customers.

In manufacturing, logistics accounts for an ever increasing percentage of the final product cost, ranging from 6% to 15% of the total turnover. Managers have finally realized that improving local node logistics and Supply Chain Management (SCM) performance represents an important leverage of competitiveness.

The research behind this paper hence focuses on the emerging focus -both in literature and industry- on managing performance of extended process within and beyond the single company and of the related flows of information, goods and knowledge within a network of companies

The starting point is the acknowledgement that over the past few years practitioners and academics alike have been noticing an increasing level of collaboration among companies not supported by the development of proper management processes and methods. In particular in the area of supply chain management and business performance measurement, a holistic approach to manage performance from a SCM perspective is still missing.

This paper aims to fill a number of the existing gaps in actual knowledge, concerning the dynamics, mechanisms and infrastructure needed for performance management of integrated business networks. To improve understanding of how performance should be measured and managed in this context of increasing collaboration, this paper answers two important questions: what has to be measured?; and how shall it be measured?

The authors first contextualize the research within existing scientific studies. Later, they discuss a comprehensive framework to support supply chain managers measure and manage performance of extended and integrated logistic processes.

Research Methodology

The research behind this paper was applied in nature. At different stages of research, deduction and induction[1] were used interchangeably. Given the research problem and the type of research questions, this research mainly employed plant-based, single-case study, qualitative and constructive research strategies. Thanks to the legal agreement between the authors and a Norwegian manufacturer within a European research project the authors have had the possibility: to carry out numerous observations; to engage in numerous brainstorming and project meetings where ideas where discussed together with the other partners in the project[2]; to be part of the implementation of the research outcomes (i.e. to implement and test them); to evaluate the outcomes of the research, both independently (i.e. based on his opinions) and dependently (i.e. based on the opinions of the other partners involved in the project); to generate theory that is at the same time grounded in theory and grounded in practice; and to publish major milestones and hence collect feedback from both practitioners and academics

Scientific and practical relevance of this research

To cope with today’s increasing competitive marketplace, companies have, and should, become more collaborative (Burgess et al., 1997; Fawcett and Magnam, 2002; Bititci et al., 2004). The trend in manufacturing has moved towards the optimisation of the total product value chain. Instead of simply focusing on the internal manufacturing processes, enterprises are becoming increasingly aware of the importance of their relationships with their business partners. This would explain why the many issues relating to technology, standards, modelling and management of these enterprise networks have become among the most urgent issues in management research agenda. Manufacturing companies seem doomed to become “ […] collaborative agile enterprise, which will be able to continuously and quickly change its organization, process, people, products, facilities, information systems, performance measures, business partners and so on to adapt in to a continuously changing business environment” (Bititci and Carrie, 1998; Jagdev and Browne, 1998; Papazoglou et al., 2000).

Even though industries are moving toward being more collaborative, for a number of reasons the transaction from single-inward-looking company to global-integrated-collaborative enterprise is filled with threats and pitfalls, and initiatives that fall right into them. As a matter of fact, a number of authors question whether collaboration does in reality lead to success and in what measure (e.g. Burges et al., 1997; Brinkerhoff, 2002). Among the hindering factors, the most significant are: (1) a general lack of a structured approach toward implementing the needed collaborative culture (e.g. Wognum and Faber, 2002); (2) a general tendency to focus on single-firms’ processes instead of collaborative extended processes (e.g. Holmberg, 2000; Sabath and Fontanella, 2002); and (3) a general scepticism regarding trust over information sharing (e.g. Fliedner, 2003). Most studies conclude suggesting future research to look into the methods, tools and techniques that can be used to manage collaboration between enterprises (Greis and Kasarda, 1997).

The fact that extended processes and their integrated management are still not well understood has indeed a negative impact on understanding performance management of collaborative processes. Negative impact which is generally translated in the inability to select measures which take into consideration both internal and external performance and that are able to foster proactive decision making (e.g. Holmberg, 2000). Most recent studies conclude that, despite the multidisciplinary approach taken, researchers have not efficiently enough embarked upon developing a collaborative process for measuring and managing performance of extended processes (Beamon, 1999; Rafele, 2004; Barratt, 2004; Schmitz and Platts, 2004).

The study of literature clearly pointed out the lack of appropriate performance management theories, models and tools (e.g. Holmberg, 2000; Yeniyurt, 2003). A performance management framework was needed to support performance mangers:

• Measuring performance

• Managing performance

• Managing through performance (top-down and bottom-up performance management)

• Building the performance measurement system

• Clarifying performance measurement boundaries

• Specifying performance measurement dimensions or views

In the remaining of the paper, the authors present the results of their work in this area. The authors use the term collaborative enterprise (CE) to refer to an integrated network of enterprises, where processes and operations are extended beyond single nodes boundaries and supply chain management activities are carried out collaboratively (see also Bititci and Carrie, 1998; Jagdev and Browne, 1998; Papazoglou et al., 2000).

Proposal for an integrated performance management framework

In today’s collaborative enterprise business models, management and support processes are extended vertically, i.e. these are carried out at both the single-node and the business network level; information related to management and support processes flows from the single-nodes upward to the network level. Operate processes, on the other hand, are extended horizontally, i.e. these are carried out at each single node level and extended to the others nodes in the chain. In this case, information related to operate processes flows from the very first supplier to the very last customer and vice-versa.

Performance management of integrated business networks should hence monitor the flow of information related to management and support processes between the collaborative enterprise management team and the single units; and the flows of goods and information related to operate processes among the single units being part of the collaborative enterprise. The authors more precisely define performance management of integrated logistics and SCM operations in collaborative enterprise as the process of using inter-organizational systems (IOSs) to collaboratively measuring performance of supply chain management processes and using these measurements to enable decision-makers to proactively and strategically manage the collaborative enterprise itself.

To support collaborative enterprise performance management, the authors have hence developed an integrated framework consisting of a set of models, processes, theoretical guidelines and practical tools to guide and support practitioners in measuring integrated processes performance. Figure 1 highlights the following applications and elements of the framework:

1. Design of the Global Performance Management Solution: a set of models and processes to design a performance measurement system for the integrated set of companies closely working together. It includes:

a. The Global PMS design process

b. The Global Balanced Scorecard Model

c. The Global PMS model

2. Use of the Global Performance Management Framework: a performance dashboard which act as the core of the framework. It displays the defined performance indicators and gives access to the general application provided by the framework.

3. Maintenance of the Global Performance Measurement System: it provides decision makers with a set of electronic questionnaires used to keep the solution up-dated with changing needs of the companies users.

4. Global Performance Management Support: it provides users with a comprehensive and interactive guide for self-training, including training material on the use of the dashboard and the theoretical concepts of measuring and managing performance of integrated operations.


Figure 1 - The framework for collaborative performance management

Design of the global performance management solution

In today’s collaborative enterprises performance management and measurement must be carried out at two levels.

• The single-node level: for local performance management

• The collaborative enterprise level: for global performance management

Based on the global performance measurement system model in Figure 3, the authors suggest in Figure 2 a two-level performance measurement system design process. Highlighted in the figure are: the sequence of steps for both the single node as well as the collaborative enterprise level; the outcome of each step; and the links between one step and the others.


Figure 2 - The global performance measurement system model


Figure 3 - The design process for a two levels PMS

KPI selection frameworks

Whilst there has been much documented concerning guidelines and rules for the choosing of performance measures, there is no recognised methodology in place that allows an organisation to select performance measures in a step-wise, logical fashion. Existing performance measurement frameworks can only go so far; usually, once a large list of measures has been collected there is a requirement to utilize brainstorming sessions, ranking scales, research and analysis to achieve a serviceable and useful list of performance indicators. The absence of a formalised set of performance measurement selection guidelines may have much to do with this. The diverging and often contradictory needs of firms in different business environments are not amenable to the creation of a performance measurement selection tool. When it is not obvious which measures should be adopted by a company, generic guidelines to select performance measures can be difficult to create, never mind implement. Performance measurement selection guidelines are also complicated by the fact that the most relevant measures for a company to adopt change over time.

Adapting existing work by Medori and Steeple (2000) the authors suggest in the PMS design process to use the following two frameworks for KPIs selection:

1) KPIs selection at the local node level: concerned with the supplier-, internal-, and customer-perspective of the CE-balanced scorecard model:

• Stage 1: Define the company’s mission and strategy.

• Stage 2: Determine the importance of the competitive priorities for each perspective

• Stage 3: Derive critical success factors and customer requirements from the company’s strategy

• Stage 4: Select measures

• Stage 5: Implementation of KPIs

• Stage 6: Periodic Review

2) KPIs selection at the CE level, as implemented by the CE host: concerned with the CE-perspective in the CE balanced scorecard model.

• Stage 1: Develop the CE direction and requirements plan

• Stage 2: Translate the plan into competitive priorities

• Stage 3: Select measures

• Stage 4: Implement the CE KPIs

• Stage 5: Transmit the developed CE KPIs

• Stage 6: Periodic Review

Use of the framework

A performance dashboard is designed as the access portal to the different applications provided in the framework. It displays the defined performance indicators and gives access to the general application provided by the framework. It should be thought of as a general collaboration platform that sits on top of existing information management systems, gathering and feeding data and information from and to defined databases.

The dashboard displays the indicators defined or selected using the two frameworks previously presented. It is used to monitor the flow of information and goods at both the local as well as global level, through:

• Electronic and integrated measurement of KPIs along the whole collaborative enterprise.

• Display of the KPIs values and trends in a user-friendly fashion

• Display of the collaborative enterprise process model, with highlighted relevant KPIs

• Display of virtual meeting rooms, which allow managers located far from each other to carry out virtual meetings and undertake action real time that affect the KPIs used.

• Unification of the several information database repositories

Maintenance of the performance management system

In order to control the administrative issues surrounding the PMS in the CE, questionnaires and checklists tailored to the requirements of the collaborative enterprise are a necessity. An intra-organisational checklist or questionnaire is not really subject to the same requirements; internal performance measurement has usually been arranged as a company-wide initiative with individual functions within the company subject to standardised measurement rules and regulations implemented at the company-wide level. However, extending the concepts of performance measurement and management to the collaborative enterprise requires crossing company boundaries, and attempting to introduce specific initiatives across a range of firms that may be geographically, as well as culturally, diverse. This situation, if not managed properly, may give rise to a number of specific problems, such as: decentralised reporting leading to inconsistencies; deficient insight in cohesion between KPIs; uncertainty about what to measure (Lohman et al., 2003)

The authors suggest the following set of questionnaires and checklists to be used in order to provide some administrative regulation in these areas. They should be seen as a set of performance management tools that support the PMS design process and the selection frameworks developed earlier.

• Self assessment checklist for local node level: to provide comprehensive feedback concerning the development and use of the collaborative enterprise performance management concept. The self assessment checklist is to be filled in by each participating local-node.

• External assessment checklist for collaborative enterprise level: developed for external analysis of the local node in the collaborative enterprise. This checklist presents generic questions that may be proposed as an external assessment analysis for each collaborative enterprise node participating in the collaborative enterprise PMS. It is suggested that for each node this assessment checklist be completed by a selected member -usually the initiator of the network- upon a regular basis. This external assessment procedure helps gain a wider perception of individual collaborative enterprise node commitment and perseverance to the collaborative enterprise PMS.

• Collaborative enterprise performance measurement design questionnaire: developed to deal with setting-up issues in the collaborative enterprise PMS. This questionnaire is of use to the network initiator when setting-up a CE PMS, asking some basic questions of participating nodes that require positive answers. The CE-host assessment checklist is to be filled out by the initiator with the co-operation of the participating (or aspirant) local-nodes


The literature study carried out prior this paper revealed that industries are facing an increasing level of business partners’ integration. When partners work closely together processes must be re-engineered. Operations control crosses the traditional company boundaries and extends to the whole network processes. It was highlighted that there is the need to develop new theories and tools to support performance management of integrated processes. The paper presented a framework for integrated performance management of extended processes. The authors shortly presented the various application of the framework, highlighting how this last support: building the PMS at the local-node and the global collaborative enterprise level; monitoring and managing the performance of the collaborative enterprise and its nodes; periodically reviewing and updating the PMS at both the local-node and the collaborative enterprise level. This paper aimed at increasing understanding of collaborative enterprise performance measurement and management practices, and presenting a tool that practitioners could use to monitor their local logistics activities and global SCM processes.


Barratt, M. (2004), Understanding The Meaning Of Collaboration In The Supply Chain, in Supply Chain Management: An International Journal, Vol. 9, No 1, pp 30-42.

Beamon, B. M. (1999), Measuring Supply Chain Performance, in International Journal Of Operations & Production Management, Vol, 19 No. 3, pp. 275-292.

Bititci, U.S., Carrie, A.S., (1998), Integrated Performance Measurement Systems: Structures And Relationships, EPSRC Final Research Report, Grant No. GR/K 48174, Swindon UK

Bititci, U.S., Martinez, V. Albores, P., Parung, J. (2004), Creating And Managing Value In Collaborative Networks, in International Journal Of Physical Distribution & Logistics Management, Vol. 34 No. ¾, pp. 251-268

Brinkerhoff, J. M., (2002), Assessing And Improving Partnership Relationships And Outcomes: A Proposed Framework, in Evaluation And Program Planning, Vol. 25, pp. 215-231.

Buckley J., Buckley M. And Chiang H. (1976), Research Methodology & Business Decisions, National Association Of Accountants, 919 Third Avenue, New York, N.Y. 10022 And The Society Of Industrial Accountants Of Canada, 154 Main St., Hamilton, Ontario, Canada.

Burgess, T.F., Gules, H.K., Tekin, M. (1997), Supply-Chain Collaboration And Success In Technology Implementation, Integrated Manufacturing Systems, Vol. 8, No. 5, pp. 323-332

Eisenhardt, K.M., (1989), Building Theories From Case Study Research. Academy Of Management Review, Vol 14(4), PP 532-550.

Fawcett, S.E., Magnan, G.M. (2002), The Rhetoric And Reality Of Supply Chain Integration, International Journal Of Physical Distribution And Logistics Management, Vol. 32, No. 5, pp. 339-361.

Fliedner, G. (2003), CPFR: An Emerging Supply Chain Tool, In Industrial Management & Data Systems, Vol. 103 No. 1, pp. 14-21

Greis, N.P., Kasarda, J.D. (1997), Enterprise Logistics In The Information Age, California Management Review, Vol. 39, No. 3, pp. 55-78.

Holmberg, S. (2000), A System Perspective On Supply Chain Measurement, International Journal Of Physical Distribution & Logistics, Vol. 30, No. 10, pp. 847-868.

Jagdev, H S , Browne, J (1998), The Extended Enterprise: A Context For Manufacturing, Production Planning & Control, 9 (3), 216-229.

Papazoglou, M P, Ribbers, P, Tsalgatidou, A (2000), “Integrated Value Chains And Their Implications From A Business And Technology Standpoint, Decision Support Systems, 29, 323-342.

Lohman, C., Fortuin, L., And Wouters, M. (2003), Designing A Performance Measurement System: A Case Study. European Journal Of Operational Research, In Press, Corrected Proof.

Medori, D. And Steeple, D. (2000), “A Framework For Auditing And Enhancing Performance Measurement Systems, International Journal Of Operations And Production Management, Vol. 20, No. 5, pp. 520-533.

Rafele, C. (2004), “Logistic Service Measurement: A Reference Framework, Journal Of Manufacturing Technology Management, Vol. 15, No. 3, pp. 280 -290.

Sabath, R. And Fontanella, J. (2002), “The Unfulfilled Promise Of Supply Chain Collaboration, Supply Chain Management Review, July-August, pp. 24-29.

Schmitz, J., Platts, K.W., (2004), “Supplier Logistics Performance Measurement: Indications From A Study In The Automotive Industry, International Journal Of Production Economics, Vol. 89, pp. 231-243.

Wognum, P.M., Faber, E.C.C. (2002), “Infrastructures For Collaboration In Virtual Organisations, International Journal Of Networking And Virtual Organizations, Vol. 1, No. 1.

Yeniyurt, S. (2003), A Literature Review And Integrative Performance Measurement Framework For Multinational Companies, Marketing Intelligence & Planning, Vol. 21, No. 3, pp. 134-142.


[1] The terms “deductive” and “inductive” are often use as synonymous of “fact finding” and “fact testing” (Buckley et al., 1976) and are usually related respectively to the nomothetic and ideographic approaches.

[2] The importance of having research teams involving multiple researchers is addressed in Eisenhardt (1989). Key advantages of this tactic are: (1) to enhance the creative potential of the research; (2) to enhance confidence in the findings; (3) to view the phenomenon from different perspectives; (4) to ensure objectivity of observations and interpretations.


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