Spreadsheets as Decision Support Tools Case Study on Automatic Trend Lines

2015 ◽  
Author(s):  
Daniel Homocianu
Keyword(s):  
Decision Support ◽  
Decision Support Tools ◽  
Support Tools

Decision Support Tools for Managing Unpredictability in the Supply Chain

2000 ◽  
Author(s):  
Carol Vesier
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Inventory Management ◽  
Production Scheduling ◽  
Capital Investment ◽  
Investment Strategy ◽  
Decision Support Tools ◽  
Business Outcomes ◽  
Support Tools

Abstract Effectively managing unpredictability requires decision support tools that can predict the financial and business outcomes of various supply chain strategies. This paper will discuss the role of these decision support tools and their characteristics as well as review a case study. In the case study, decision support tools facilitated development of strategies that increased after tax profit by $140 Million. These strategies included: • Reliability improvement strategy: Identifying the reliability improvements that offered the biggest profitability impact. • Supply chain strategy: Defining inventory management and production scheduling rules that ensured order shipment within two days. • Capital investment strategy: Defining when new capacity should come on line as well as the minimum capital investment.

scholarly journals Exploring Public Sector Managers’ Motivations in Deploying Decision Support Tools to the Street Level

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Chris McIntyre
Keyword(s):  
Decision Support ◽  
Public Sector ◽  
Digital Tools ◽  
Decision Support Tools ◽  
Structured Interviews ◽  
Senior Managers ◽  
Street Level ◽  
Support Tools ◽  
Public Sector Managers

This article explores the motivations of public sector managers in developing and deploying digital tools to support decision making at the front lines of public service delivery. Two digital decision support tools created by New Zealand’s Ministry of Social Development are presented as a case study, drawing primarily on semi-structured interviews with senior managers. Results provide empirical evidence that public sector managers deploy digital tools not to curtail, but to support street-level bureaucrats’ discretion. Managers appear to be motivated not by increased control over front-line staff, but, rather, by improving clients’ experience of the system and decreasing longterm service costs.

scholarly journals Creating the data basis to adapt agricultural decision support tools to new environments, land management and climate change—A case study of the RiceAdvice App

2020 ◽  
Vol 206 (4) ◽  
pp. 423-432 ◽  
Author(s):  
Marc Cotter ◽  
Folkard Asch ◽  
Bayuh Belay Abera ◽  
Boshuwenda Andre Chuma ◽  
Kalimuthu Senthilkumar ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Land Management ◽  
Decision Support Tools ◽  
Data Basis ◽  
Support Tools

scholarly journals Livestock feed intake assumptions in decision support tools; A stocktake of the current science and assumptions used by livestock models

2015 ◽  
Vol 77 ◽  
pp. 19-22
Author(s):  
P. Frater ◽  
S. Howarth ◽  
G.J. Mcewen
Keyword(s):  
Decision Support ◽  
New Zealand ◽  
Scientific Knowledge ◽  
Feed Intake ◽  
Decision Support Tools ◽  
Livestock Feed ◽  
Support Tools ◽  
Metabolisable Energy ◽  
Current Science

Decision Support Tools (DSTs) and models are becoming increasingly important to make informed decisions. The aim of this review was to understand how the scientific assumptions behind related pasture-based DSTs used in New Zealand interrelate. Using modelled feed intake of grazing sheep as a case study, we reviewed the metabolisable energy (ME) assumptions of relevant New Zealand models. Although the DSTs were largely dependent on a common model, there were some discrepancies between them. We raise two concerns: 1. In New Zealand, pasture-based livestock models to predict ME intake are highly dependent on equations developed in Australia, not validated in New Zealand. 2. The minor discrepancies between models make collaboration difficult - this is particularly pertinent to farmer-targeted DSTs. Closer collaboration between DST companies and research institutions is required to agree on consistent, robust equations aligned with the latest scientific knowledge.

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