Performance measurement and indicators for water supply management: review and international cases

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Performance measurement review: a comparison between English and Italian companies

Il sistema di misurazione delle performance (PMS) ha ricevuto particolare attenzione dalla ricerca in ambito accademico e dalle aziende che ogni anno investono risorse nell’implementazione e nel miglioramento di questo strumento. I ruoli assegnati al PMS possono essere: misurazione della performance, implementazione della strategia, comunicazione, allineamento dei comportamenti, apprendimento e miglioramento. Queste differenti finalità sottolineano quanto sia strategica un’efficace implementazione di tale strumento. Negli ultimi anni le aziende si trovano a dover competere in ambienti sempre più turbolenti e mutevoli. La capacità di adattarsi al cambiamento è fondamentale, pertanto anche il PMS deve essere aggiornato per garantire un’implementazione di Key Performance Indicators (KPIs) che siano appropriati e rilevanti, considerando le nuove priorità aziendali e le condizioni al contorno. Questa tesi ha come obiettivo quello di analizzare la revisione del PMS, in quanto un inappropriato set di KPIs implementati possono causare un indebolimento del potenziale di tale strumento ed ancor peggio un fallimento degli investimenti riguardanti tale strumento. L’approccio metodologico di questa tesi è un multiple case-study. Per avere una visione più ampia di come viene sviluppata la revisione del PMS nella pratica si è deciso di inserire nel campione aziende di grandi dimensioni operanti in differenti settori industriali. Le informazioni raccolte attraverso le interviste, hanno permesso di fornire un contributo non presente in letteratura: una categorizzazione delle revisioni svolte dalle aziende e riflessioni su di esse. La limitazione di questo studio è legata ad un basso numero interviste svolte.

Comparison of performance measurement-systems used for order-picking

In consequence of rapidly changing market demands companies are permanently encouraged to review their own processes and structures and to modify them. Being one of these developments, order-picking is involved as part of an intra-logistics system. But to take appropriate actions, system performance and system costs have to be measured permanently. Concerning this the use of performance measurement-systems as further development of traditional systems of key figures is suitable. In this paper various performance measurement-systems are compared and their suitability for an implementation in order-picking systems is estimated. On the basis of the result of the evaluation a first concept of a performance measurement-system for order-picking will be developed by using typical key figures that are mentioned in academic literature. Finally, hints for a necessary detailed implementation and evaluation in practice will be given.

Vergleich von Performance Measurement-Systemen zum Einsatz für die Kommissionierung

Aufgrund sich schnell verändernder Anforderungen des Marktes sind Unternehmen ständig dazu aufgefordert, ihre eigenen Prozesse und Strukturen zu überdenken und ggf. anzupassen. Von diesen Entwicklungen ist auch die Kommissionierung als Teil eines Intralogistiksystems betroffen. Um allerdings geeignete Maßnahmen ergreifen zu können, müssen Systemleistungen und –kosten permanent gemessen werden. Hierzu eignet sich der Einsatz von Performance Measurement-Systemen als Weiterentwicklung traditioneller Kennzahlensysteme. In diesem Beitrag werden verschiedene Performance Measurement-Systeme gegenüber gestellt und hinsichtlich ihrer Eignung für den Einsatz in Kommissioniersystemen bewertet. Auf Basis der Ergebnisse der Bewertung erfolgt eine erste Konzeption eines Performance Measurement-Systems für die Kommissionierung unter Verwendung typischer Kennzahlen, die in der Literatur genannt werden. Abschließend werden Hinweise zur noch notwendigen detaillierten Umsetzung und Evaluation in der Praxis gegeben.

Performance measurement integrated information framework in e-Manufacturing

The implementation of Internet technologies has led to e-Manufacturing technologies becoming more widely used and to the development of tools for compiling, transforming and synchronising manufacturing data through the Web. In this context, a potential area for development is the extension of virtual manufacturing to performance measurement (PM) processes, a critical area for decision making and implementing improvement actions in manufacturing. This paper proposes a PM information framework to integrate decision support systems in e-Manufacturing. Specifically, the proposed framework offers a homogeneous PM information exchange model that can be applied through decision support in e-Manufacturing environment. Its application improves the necessary interoperability in decision-making data processing tasks. It comprises three sub-systems: a data model, a PM information platform and PM-Web services architecture. A practical example of data exchange for measurement processes in the area of equipment maintenance is shown to demonstrate the utility of the model.

Serving the American public : best practices in performance measurement : Benchmarking Study Report /

"June 1997."

Performance measurement : toward more effective government : hearing before the Committee on Governmental Affairs, United States Senate, One Hundred Second Congress, second session, on S. 20, to provide for the establishment, testing, and evaluation of strategic planning and performance measurement in the federal government, and for other purposes, May 5, 1992.

Shipping list no.: 93-0182-P.

Analysis of performance measurement and training requirements for driving decision making in emergency situations. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Future long-horizon performance measurement conditional on past survival

This paper examines the measurement of long-horizon abnormal performance when stock selection is conditional on an extended period of past survival. Filtering on survival results in a sample driven towards more-established, frequently traded stocks and this has implications for the choice of benchmark used in performance measurement (especially in the presence of the well-documented size effect). A simulation study is conducted to document the properties of commonly employed performance measures conditional on past survival. The results suggest that the popular index benchmarks used in long-horizon event studies are severely biased and yield test statistics that are badly misspecified. In contrast, a matched-stock benchmark based on size and industry performs consistently well. Also, an eligible-stock index designed to mitigate the influence of the size effect proves effective.

The impact of supply chain performance measurement systems on dynamic behaviour in supply chains

The amplification of demand variation up a supply chain widely termed ‘the Bullwhip Effect’ is disruptive, costly and something that supply chain management generally seeks to minimise. Originally attributed to poor system design; deficiencies in policies, organisation structure and delays in material and information flow all lead to sub-optimal reorder point calculation. It has since been attributed to exogenous random factors such as: uncertainties in demand, supply and distribution lead time but these causes are not exclusive as academic and operational studies since have shown that orders and/or inventories can exhibit significant variability even if customer demand and lead time are deterministic. This increase in the range of possible causes of dynamic behaviour indicates that our understanding of the phenomenon is far from complete. One possible, yet previously unexplored, factor that may influence dynamic behaviour in supply chains is the application and operation of supply chain performance measures. Organisations monitoring and responding to their adopted key performance metrics will make operational changes and this action may influence the level of dynamics within the supply chain, possibly degrading the performance of the very system they were intended to measure. In order to explore this a plausible abstraction of the operational responses to the Supply Chain Council’s SCOR® (Supply Chain Operations Reference) model was incorporated into a classic Beer Game distribution representation, using the dynamic discrete event simulation software Simul8. During the simulation the five SCOR Supply Chain Performance Attributes: Reliability, Responsiveness, Flexibility, Cost and Utilisation were continuously monitored and compared to established targets. Operational adjustments to the; reorder point, transportation modes and production capacity (where appropriate) for three independent supply chain roles were made and the degree of dynamic behaviour in the Supply Chain measured, using the ratio of the standard deviation of upstream demand relative to the standard deviation of the downstream demand. Factors employed to build the detailed model include: variable retail demand, order transmission, transportation delays, production delays, capacity constraints demand multipliers and demand averaging periods. Five dimensions of supply chain performance were monitored independently in three autonomous supply chain roles and operational settings adjusted accordingly. Uniqueness of this research stems from the application of the five SCOR performance attributes with modelled operational responses in a dynamic discrete event simulation model. This project makes its primary contribution to knowledge by measuring the impact, on supply chain dynamics, of applying a representative performance measurement system.