Analysis of strategic plans to assess planning for sustainability of comprehensive community initiatives

In order to achieve the intended impact on a community, comprehensive community initiatives must sustain programs once they have been implemented. However, planning for sustainability is challenging and is rarely incorporated in the planning process of an initiative. The current study examined 19 5-year plans developed during the planning phase of the Comprehensive Strategy for Serious, Violent and Chronic Juvenile Offenders. Quantitative and qualitative methods were employed to assess the extent to which the construct of sustainability was incorporated. The plan analysis was supplemented with results from other components of the complex evaluation design implemented as part of the process evaluation of Comprehensive Strategy. Results suggested that sustainability was not accounted for during the planning phase of this initiative. The implications of these findings, including the importance of planning for sustainability in order to achieve sustainability, are discussed.     

Ten steps to making evaluation matter

This paper proposes ten steps to make evaluations matter. The ten steps are a combination of the usual recommended practice such as developing program theory and implementing rigorous evaluation designs with a stronger focus on more unconventional steps including developing learning frameworks, exploring pathways of evaluation influence, and assessing spread and sustainability. Consideration of these steps can lead to a focused dialogue between program planners and evaluators and can result in more rigorously planned programs. The ten steps can also help in developing and implementing evaluation designs that have greater potential for policy and programmatic influence. The paper argues that there is a need to go beyond a formulaic approach to program evaluation design that often does not address the complexity of the programs. The complexity of the program will need to inform the design of the evaluation. The ten steps that are described in this paper are heavily informed by a Realist approach to evaluation. The Realist approach attempts to understand what is it about a program that makes it work.     

Freezing the Master Production Schedule Under Demand Uncertainty

Managing the trade-off between achieving a stable master production schedule (MPS) and being responsive to changes in customer requirements is a difficult problem in many firms where providing a high level of customer service is viewed as an important competitive factor. One alternative for managing this trade-off is to freeze an agreed portion of the MPS. This paper investigates the impact of adjustments in the design parameters of MPS freezing methods on two performance measures (MPS lot-sizing cost and stability) under stochastic demand conditions in a rolling planning horizon environment given a service level target. Simulation experiments are reported which indicate that many of the conclusions regarding the design of MPS freezing methods obtained under deterministic demand conditions hold under stochastic demand.     

Using Exploratory Spatial Data Analysis to Leverage Social Indicator Databases: The Discovery of Interesting Patterns

With the proliferation of social indicator databases, the need for powerful techniques to study patterns of change has grown. In this paper, the utility of spatial data analytical methods such as exploratory spatial data analysis (ESDA) is suggested as a means to leverage the information contained in social indicator databases. The principles underlying ESDA are illustrated using a study of clusters and outliers based on data for a child risk scale computed for countries in the state of Virginia. Evidence of spatial clusters of high child risks is obtained along the Southern region of Virginia. The utility of spatial methods for state agencies in monitoring social indicators at various localities is discussed. A six-step framework that integrates spatial analysis of key indicators within a monitoring framework is presented; we argue that such a framework could be useful in enhancing communication between State and local planners. Given cost considerations, the original color figures have been printed in black and white in this article. The color figures can be obtained from http://www.chs.med.ed.ac.uk/rubhc/evaluation/     

Characterizing order processes of using inventory policies in supply chains

This study characterizes order processes under (R,nQ) inventory policies. We show first that the order distribution at an installation is stationary when it uses an (R,nQ) control policy, for any arbitrary stationary distribution of customer demand. We then quantify variance amplification and show that variance of orders is never less than the demand variance. Finally, we extend the analysis to the case where the supply chain comprises of one distributor and N retailers serving customers.     

The Value of Using Scheduling Information in Planning Material Requirements*

Current research and practice in the field of production and inventory planning is dominated by hierarchical, material requirements planning-based methods. The objective of this research is to determine the merits of a major redirection for the design of manufacturing planning systems—a direction that more directly exploits the capabilities of modern computer technology. We test the relative performance of two fundamentally different classes of manufacturing planning systems: (1) those that make no use of sequencing and scheduling information in the planning of material deliveries (for example, traditional MRP-based systems), and (2) those that use sequencing and scheduling information to plan delivery of materials. We first derive an analytical expression for the expected benefit (in terms of flow time reduction) of using scheduling information for a single machine system. We then describe and test a simple heuristic for predicting the improvement that could be realized in more complicated multimachine systems, under certain conditions. Results from controlled simulation experiments, over a wide range of operating environments, suggest that although the value of scheduling information is influenced by the operating environment, it could be substantial.     

MEASURING MASTER PRODUCTION SCHEDULE STABILITY UNDER ROLLING PLANNING HORIZONS

Maintaining a stable master production schedule (MPS) is difficult for many firms, especially when material requirements planning is used to manage production operations. This paper is concerned with the problem of measuring MPS stability, and the impact on stability of three important decision variables in managing the MPS within a rolling-horizon framework in a make-to-stock environment: the method used to freeze the MPS, the proportion of the MPS frozen, and the length of the planning horizon for the MPS. Simulation experiments conducted to determine the impact of these decision variables, as well as other important product demand and cost characteristics, on MPS stability are reported. The results indicate MPS stability can be influenced by managerial action directed toward management of the MPS as well as changes in important product cost and requirements characteristics.     

The impact of inter-organizational information systems-enabled external integration on capabilities of buyer–supplier dyads

Increasingly, firms are adopting two major supply chain management initiatives: to undertake external integration with supply chain partners and to implement inter-organizational information systems (IOSs). However, academic researchers have not adequately investigated effects of these types of initiatives. Using empirical data from 154 buyer–supplier dyads, we examined the direct and indirect effects (through external integration) of IOS usage on capabilities of buyer– supplier dyads. We found that external integration plays a mediating role in the relationship between IOS usage and capabilities of buyer– supplier dyad. This is the first study to investigate the effects of IOS usage and external integration on capabilities of buyer–supplier dyad.     

Matching deprivation mapping to urban governance in three Indian mega-cities

Recent discussions of poverty recognize its multi-dimensional character, focusing on multiple sources of deprivation that poor households experience. However, for urban planners and politicians to implement intervention programs effectively in mega-cities, knowledge on sources and spatial patterns of multiple deprivations is needed. Disaggregated analysis potentially allows them to target programs to specific locations, set priorities in line with local needs, and be efficient in the use of funding. This article maps multiple deprivations of households in three Indian mega-cities, at the electoral ward level. It uses the livelihoods approach to address the following questions: 1) Is there a spatial concentration of deprivations within cities and do poverty levels differ between them? 2) Do cities differ in the types of deprivations? and 3) do these cluster within the city? The paper compares Delhi, Mumbai and Chennai, using a multi-criteria model within a geographical information system developed for identifying hotspots of multiple deprivation. It further links the results of deprivation mapping to questions of urban governance by comparing deprivation results with data on slums currently used to target anti-poverty programs. Finally, the opportunities of using spatial data for improving priorities and efficient use of funds in poverty programs are analyzed.     

Revenue Management in Order‐Driven Production Systems

This article investigates the effectiveness of a tactical demand‐capacity management policy to guide operational decisions in order‐driven production systems. The policy is implemented via a heuristic that attempts to maximize revenue by selectively accepting or rejecting customer orders for multiple product classes when demand exceeds capacity constantly over the short term. The performance of the heuristic is evaluated in terms of its ability to generate a higher profit compared to a first‐come‐first‐served (FCFS) policy. The policies are compared over a wide range of conditions characterized by variations in both internal (firm) and external (market) factors. The heuristic, when used with a Whole Lot order‐processing approach, produces higher profit compared to FCFS when profit margins of products are substantially different from each other and demand exceeds capacity by a large amount. In other cases it is better to use the heuristic in conjunction with the Split Lot order‐processing approach.