AHP and INNOVATION STRATEGY as PROJECT PORTFOLIO MANAGEMENT
The following technical report with some improvement describes the "chapter 9" of the project called: "Strategic Management of Technological Innovation Concerning The Battery Electric Vehicles (BEV)" The "Chapter 9" [1] agglutinates all chapters of "case 4" in which the BEV project introduces a real company case study (Workhorse Group Inc. Chapter 9 takes performances of Analytic Hierarchy Process (AHP) method which has developed by professor Thomas L. Saaty in the 1970s. Also, the following report proposes to contribute an optimizing decision making framework for some authentic MultipleCriteria Decision Making (MCDM) circumstances. Furthermore, the "supplementary resources" are available in the attachment of the Battery Electric Vehicles project. Remark that the ".sdmod" stands for the formats of "SuperDecisions Software" The ".sdmod" formats adopted in "part c" of the project concerning the definition of AHP Tree and the related arguments regarding the Innovation Strategy as Project Portfolio Management (PPM) Also, the "PPM F.xls" file format includes the "Solver" and the results of "part a" and "part b" PART A CATEGORIZE THE R&D The "part a" began with introducing the Workhorse case study and some questions base on the available information. Questions require researchers to categorize the Workhorse R&D segments and try to organize their innovation activities. Also, the section asks a question concerning the dimension of the appropriate projects to set the differences among those innovative projects. Besides, the "part a" requires an applied research and a basic financial analysis among the mentioned projects portfolio. Finally, the "part a" of the research ask to distinguish between the platforms, products, and customized projects. However, the henceforth part of following technical report is based on the information available on Workhorse Group Inc. website [2] and the FORM 10 K [3] of the UNITED STATES, SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549, December 2015. Also, in this part the market researchers try to categorize the Workhorse R&D and its innovation activities (Fig. 9.1) In addition, the Excel file (PPM F.xls) available in attachment illustrates the Workhorse Inc. financing condition and monitoring its core or implemented research approach, between Workhorse Inc. project responsibilities (see Fig. 9.3 and Fig. 9.4) PART B NEXT GENERATION PROJECT The "part b" works amid introducing the interest of the Amedeo family (fiction name) to evaluate the Workhorse's R&D projects, based on real data. In appropriate, they desire to examine and assess the development activities of latest versions of two leading Workhorse product the "lines A and B" The Fig. 9.2 outlines the project portfolio while the projects A1, A2, A3, B1 and B2 are platform project, and they possess a "Next Generation Project" (A#.1 or B#.2) Ordinarily, the 45 Full Time Equivalent (FTE) resources are available for the R&D activities, and resources can be increased up to 10 by using external resources at an additional cost of approximately four (4) kEUR per man/month. Also, "part b" ponders on the project portfolio shown in Fig. 9.2, concerning the two products A and B by analyzing and computing the Expected Commercial Value (ECV) and the Productivity Index (PI) indicators for each project. Besides, it tries to find out a succinct graphical representation for the portfolio such as bubble charts, pie charts, resource workload charts by employing the appropriate variables. In addition, "part b" attempts to optimize the Workhorse project portfolio with a math programming model utilizing the Excel Solver. The Objective Functions might maximize the ECV of selected projects and minimize the cost of overtime. Recognizing that the Resource Capacity Constraints requirement includes the possibility of using overtime human resources. Furthermore, by constraining the Next Generation Projects, those tasks can not be activated if in the previous year of the corresponding new product has not been launched. Another challenge occurs when the designers investigate to take out those constraints and recount the optimal solutions. Do the results change? If yes, in what terms might be considered a value of the new product development for the projects? Also, extra difficulty transpires during the evaluation of new profitability regarding the immediate termination of the product A. The question is what the financial consequences would be? PART C AHP TREE AND CRITERIA STRATEGIC ALIGNMENT The "part c" defines an AHP Tree to illustrate the Criteria Strategic Alignment into the company objectives (see Fig. 9.5) In this recent part, the crucial challenge is that how the circumstances might be modified if the enterprise business strategy distinguished as a "Definitely Cost Oriented" strategy? Page of 5 1 (c) Sajjad Khaksari (2017) Torino WORKHORSE GROUP INC. R&D ORGANIZATION Financing Conditions Workhorse Inc. as a national Ohio based has a competitive core competence Workhorse Inc. Project Portfolio Workhorse R&D and innovation activities Fig. 9.1: Workhorse Group Inc. R&D Organization Fig. 9.1: Workhorse Group Inc. R&D Organization Fig. 9.2: Representation of the Project Portfolio Fig. 9.3: A Screenshot of Excel File with Solver Parameters Window LP Method Fig. 9.4: A Screenshot of Excel File with Final Results X* ECV AHP Innovation Strategy as Project Portfolio Management (c) Sajjad Khaksari (2017) The decision making in a complex environment is an extremely complex issue specially when distress is genuine and mis designing might generate financial collapses, human resource opposes, and environmental damages. In that complex, knotty, and complicated condition, the Analytic Hierarchy Process (AHP) [4] for Decision Making and the Analytic Network Process (ANP) [5] might assist project managers to optimize their decisions. The Analytic Network Process (ANP) is the most comprehensive framework for the analysis of societal, governmental and corporate decisions that is available to the decision maker. AHP and ANP methods allow analyzers to include all the factors and criteria, tangible and intangible that have bearing on making the best decision. In fact, Analytic Hierarchy Process (AHP) is a decision making framework used for Multiple criteria decision making (MCDM) [6] which is a sub discipline of operations research because explicitly estimates multiple conflicting criteria in decision making. Therefore, the AHP is a structured technique for organizing and analyzing complicated decisions, based on mathematics and psychology. It was developed by Thomas L. Saaty in the 1970s [7] and has been extensively studied and refined since then [8] In addition, Thomas L. Saaty supervised the Super Decisions software that implements the ANP for decision making [9] in networks and makes it available free to researchers and educators at www.superdecisions.com [10] Also, in the section of "Sample Models" from the SuperDecisions website, examples of some models developed with the SuperDecisions software are available and organized by model type and by subjects. Extending into the sub subject of the "Automobile industry" [11] some interesting cases are developed concerning the Ford Explorer Decision, Porsche SUV Decision, and Alternative Fuel. However, in this technical report the Workhorse Inc. innovative projects, referred as a Case Study and the AHP method with SuperDecisions Software served as a framework to optimize analyzing phenomena [12] The structure of case demonstrates the strategic criteria concerning the Project Portfolio Management (PPM) deal with Amedeo's family dilemmas. The following AHP structure provides the case judgement based on the basic information, knowledge, pairwise comparison, and reasons to derive the position of priorities to which the company aspire to allocate and spread their efforts and their enterprise resources. Although the Amedeo's family as many other pioneer companies are not as thrilled about the old technologies in vehicle industry because of their looking forward customer's needs and because of their market competency forecasting system. They as other pathfinder companies, regularly face the remarkably complex problems concerning the ordering schedules and prioritizing the various strategic or innovative decisions (Multi decisions) [13] The critical various criteria such as Product Design, Financial Factors (ECV, PI, NPV) Forecasting the future Marketshare, Technical or Financial Risks, and after all the Resource Commitments. In that striking critical circumstances, the AHP method might assists the companies to reduce significantly their frustration of lost and help them to increase their profits (as a strategic goal) The AHP technique and the SuperDecisions demands users to introduce three (3) fundamental CLUSTERS concerning Goal, Criteria, and implemented Alternatives. The following Fig. 9.6 illustrates the screenshot of Main Network window from the AHP for Workhorse Inc. case study in environment of SuperDecisions V3.0 [14] Also, Fig. 9.6 includes the three (3) mentioned above clusters and the complete implementation of the project. As mentioned previously in abstract the supplementary resource file format called "AHP Workhorse.sdmod" is available in the attachment of the BEV [15] project. Notice that the ".sdmod" stands for the SuperDecisions file format. The Fig. 9.6 shown the GOAL CLUSTER including its "1Goal Node" and its four (4) strategic criteria: RISK, CONTRIBUTION, COSTS, and PROFIT (Summed up according to Fig. 9.5) The full criteria for the projects simplified in these only four routs. However that is evident these criteria have some sub criteria such as Planned Costs, Sunk Costs, and Cost to Production concerning COST node. Putting sub criteria into a hierarchical model might improve its accuracy, and it can improve the syntonization and sensitization of results. Belatedly, the third CLUSTER includ