Business Commons^™

Aligning Performance Metrics With Business Strategy, Ravi Kathuria, Lorenzo Lucianetti

Business Faculty Articles and Research

Purpose

This study examines whether different strategy archetypes deploy specific performance metrics to support their strategic goals and priorities. If so, does alignment of strategy and metrics positively impact organisational performance?

Design/methodology/approach

The conceptual framework and hypotheses are couched in Contingency Theory. The role of business strategy as a moderating variable is tested using MANOVA, followed by post hoc pairwise comparisons. The results are based on cross-sectional survey data from 372 manufacturing and service organisations in Italy.

Findings

The overall contingency effect of business strategy in selecting and deploying performance metrics and their effect on organisational performance is supported. …

Herding And Anchoring In Macroeconomic Forecasts: The Case Of The Pmi, John B. Broughton, Bento J. Lobo

Business Faculty Articles and Research

We test if analysts display multiple biases in forecasting the Institute for Supply Management’s (ISM) manufacturing Purchasing Manager’s Index (PMI). We adopt a test that does not require knowledge of the forecaster’s prior information set and is robust to rational clustering, correlated forecast errors and outliers. We find that analysts forecast the PMI poorly and display multiple biases when forecasting. In particular, forecasters anti-herd and anti-anchor. Anti-herding supports a reputation-based notion that forecasters are rewarded not only for forecast accuracy but also for being the best forecast at a single point in time. Anti-anchoring is consistent with forecasters overreacting to …

Optimizing Product Line Designs: Efficient Methods And Comparisons, Alexandre Belloni, Robert Freund, Matthew Selove, Duncan Simester

Business Faculty Articles and Research

We take advantage of recent advances in optimization methods and computer hardware to identify globally optimal solutions of product line design problems that are too large for complete enumeration. We then use this guarantee of global optimality to benchmark the performance of more practical heuristic methods. We use two sources of data: (1) a conjoint study previously conducted for a real product line design problem, and (2) simulated problems of various sizes. For both data sources, several of the heuristic methods consistently find optimal or near-optimal solutions, including simulated annealing, divide-and-conquer, product-swapping, and genetic algorithms.