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Description
The ever-changing economic landscape has forced many companies to re-examine their supply chains. Global resourcing and outsourcing of processes has been a strategy many organizations have adopted to reduce cost and to increase their global footprint. This has, however, resulted in increased process complexity and reduced customer satisfaction. In order to meet and exceed customer expectations, many companies are forced to improve quality and on-time delivery, and have looked towards Lean Six Sigma as an approach to enable process improvement. The Lean Six Sigma literature is rich in deployment strategies; however, there is a general lack of a mathematical approach to deploy Lean Six Sigma in a global enterprise. This includes both project identification and prioritization. The research presented here is two-fold. Firstly, a process characterization framework is presented to evaluate processes based on eight characteristics. An unsupervised learning technique, using clustering algorithms, is then utilized to group processes that are Lean Six Sigma conducive. The approach helps Lean Six Sigma deployment champions to identify key areas within the business to focus a Lean Six Sigma deployment. A case study is presented and 33% of the processes were found to be Lean Six Sigma conducive. Secondly, having identified parts of the business that are lean Six Sigma conducive, the next steps are to formulate and prioritize a portfolio of projects. Very often the deployment champion is faced with the decision of selecting a portfolio of Lean Six Sigma projects that meet multiple objectives which could include: maximizing productivity, customer satisfaction or return on investment, while meeting certain budgetary constraints. A multi-period 0-1 knapsack problem is presented that maximizes the expected net savings of the Lean Six Sigma portfolio over the life cycle of the deployment. Finally, a case study is presented that demonstrates the application of the model in a large multinational company. Traditionally, Lean Six Sigma found its roots in manufacturing. The research presented in this dissertation also emphasizes the applicability of the methodology to the non-manufacturing space. Additionally, a comparison is conducted between manufacturing and non-manufacturing processes to highlight the challenges in deploying the methodology in both spaces.
ContributorsDuarte, Brett Marc (Author) / Fowler, John W (Thesis advisor) / Montgomery, Douglas C. (Thesis advisor) / Shunk, Dan (Committee member) / Borror, Connie (Committee member) / Konopka, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
This report will provide an analysis of frontier market equity-based investment funds with respect to bivariate correlation analysis, global integration analysis, and US optimized portfolio statistics. My analysis has indicated strong diversification benefits of including frontier market equities in a US portfolio, given its low correlation to US equity concentrated portfolios especially portfolios that would consist of midcap and smallcap stocks. With the drawbacks of the bivariate correlation test, an additional global integration analysis has been included to reaffirm the value frontier markets offer in the form of integration. Integration is a second layer of the diversification analysis. I find that when analyzing frontier markets (FM) against developed markets (DM) there exhibits significantly less integration as compared to emerging markets against developed markets. This analysis goes one step further and quantifies integration of specific frontier market funds against the broader emerging and developed markets. This study finds that iShares MSCI frontier 100 ETF (Ticker: FM) exhibits the least integration amongst Guggenheim Frontier Markets ETF (Ticker: FRN), Templeton Frontier Markets A (Ticker: TFMAX), and Morgan Stanley Frontier Emg (Ticker: MFMIX). Lastly, this analysis covers the inadequacy with using Sharpe ratios and minimum volatility parameters to achieve portfolio optimization under a Monte-Carlo style 1000 portfolio simulation with frontier market funds in a broader US equity portfolio but finds better results when using a US equity and US bond combination portfolio. Overall, this analysis of frontier markets and frontier market funds has shown there still exists significant diversification benefits to US Investors when they engage in FM investments, specifically through diversified FM investment funds.
ContributorsHardy, Gunner Laine (Author) / Pruitt, Seth (Thesis director) / Brada, Josef (Committee member) / W.P. Carey School of Business (Contributor) / Economics Program in CLAS (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05