Product Portfolio Restructuring: Methodology and Application at Caterpillar

2017 ◽  
Vol 27 (1) ◽  
pp. 100-120 ◽  
Author(s):  
Masha Shunko ◽  
Tallys Yunes ◽  
Giulio Fenu ◽  
Alan Scheller-Wolf ◽  
Valerie Tardif ◽  
...  
Keyword(s):  
Product Portfolio ◽  
Portfolio Restructuring

scholarly journals SUPPORT FOR MANAGING PARTLY CONFIGURABLE MODULAR SYSTEMS

2021 ◽  
Vol 1 ◽  
pp. 2791-2800
Author(s):  
Jarkko Pakkanen ◽  
Teuvo Heikkinen ◽  
Nillo Adlin ◽  
Timo Lehtonen ◽  
Janne Mämmelä ◽  
...  
Keyword(s):  
Portfolio Management ◽  
Product Variety ◽  
Added Value ◽  
Modular System ◽  
Product Management ◽  
Design Decision ◽  
Product Portfolio ◽  
Modular Systems ◽  
Engineer To Order ◽  
The Impact

AbstractThe paper studies what kind of support could be applied to the management of partly configurable modular systems. The main tasks of product management, product portfolio management and product variety management are defined. In addition, a partly configurable product structure and modular system are defined. Because the limited support in the literature for managing partly configurable modular systems, the article reviews previous product development cases in which authors have been involved on lessons learnt basis, i.e., if the methods and tools used in the cases could provide support for the research objective. As a result, the existing definition of the modular system should be extended by the concepts of non-module and design decision sequence description when dealing with partly configurable modular systems. This is because engineer-to-order should be made possible in cases where it brings clear added value to the customer compared to completely pre-defined solutions that may limit the customer's interest in the offering. Tools to assess the impact of changes to the product offering are required. These should be taken into account in frameworks that are used in method and tool development.

scholarly journals Is Investing in Companies Manufacturing Solar Components a Lucrative Business? A Decision Tree Based Analysis

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 499
Author(s):  
Sebastian Klaudiusz Tomczak ◽  
Anna Skowrońska-Szmer ◽  
Jan Jakub Szczygielski
Keyword(s):  
Renewable Energy ◽  
Energy Production ◽  
Manufacturing Sector ◽  
Energy Systems ◽  
Product Portfolio ◽  
New Approach ◽  
Renewable Energy Systems ◽  
Pv Systems ◽  
Depth Analysis ◽  
A Company

In an era of increasing energy production from renewable sources, the demand for components for renewable energy systems has dramatically increased. Consequently, managers and investors are interested in knowing whether a company associated with the semiconductor and related device manufacturing sector, especially the photovoltaic (PV) systems manufacturers, is a money-making business. We apply a new approach that extends prior research by applying decision trees (DTs) to identify ratios (i.e., indicators), which discriminate between companies within the sector that do (designated as “green”) and do not (“red”) produce elements of PV systems. Our results indicate that on the basis of selected ratios, green companies can be distinguished from the red companies without an in-depth analysis of the product portfolio. We also find that green companies, especially operating in China are characterized by lower financial performance, thus providing a negative (and unexpected) answer to the question posed in the title.

The Product Portfolio and Man's Best Friend

1982 ◽  
Vol 25 (1) ◽  
pp. 84-95 ◽  
Author(s):  
Donald C. Hambrick ◽  
Ian C. MacMillan
Keyword(s):  
Product Quality ◽  
High Performance ◽  
Product Portfolio ◽  
Best Friend

Boston Consulting Group's Dogs reconsidered: Their efficiency, superior product quality, and focus mean high performance.

scholarly journals Determination of a Customer Value-oriented Product Portfolio

Procedia CIRP ◽  
2016 ◽  
Vol 50 ◽  
pp. 82-87 ◽  
Author(s):  
Eric Rebentisch ◽  
Günther Schuh ◽  
Michael Riesener ◽  
Max Gerlach ◽  
Paul Zeller
Keyword(s):  
Customer Value ◽  
Product Portfolio

Artificial intelligence based prediction models: sales forecasting application in automotive aftermarket

2021 ◽  
pp. 1-13
Author(s):  
Mert Girayhan Türkbayrağí ◽  
Elif Dogu ◽  
Y. Esra Albayrak
Keyword(s):  
Artificial Intelligence ◽  
Computational Intelligence ◽  
Prediction Models ◽  
Predictive Analytics ◽  
Demand Characteristic ◽  
Product Portfolio ◽  
Ann Model ◽  
Nonlinear Relationships ◽  
Relationship Of ◽  
Automotive Aftermarket

Automotive aftermarket industry is possessed of a wide product portfolio range which is in the 4th rank by its worldwide trade volume. The demand characteristic of automotive aftermarket parts is volatile and uncertain. Nevertheless, the cause-and-effect relationship of automotive aftermarket industry has not been defined obviously heretofore. These conditions bring automotive aftermarket sales forecasting into a challenging process. This paper is composed to determine the relevant external factors for automotive aftermarket sales based on expert reviews and to propose a sales forecasting model for automotive aftermarket industry. Since computational intelligence techniques yield a framework to focus on predictive analytics and prescriptive analytics, an artificial neural network model constructed for Turkey automotive aftermarket industry. Artificial intelligence is a subset of computational intelligence that focused on problems which have complex and nonlinear relationships. The data which have complex and nonlinear relationships could be modelled successfully even though incomplete data in case of implementation of appropriate model. The proposed ANN model for sales forecast is compared with multiple linear regression and revealed a higher prediction performance.

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