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One of the long-standing issues in the field of corporate real estate management is the alignment of an organization’s real estate to its corporate strategy. In the last thirty years, fourteen Corporate Real Estate (CRE) alignment models have been made. In some of these CRE alignment models it is indicated that they strive for maximum or optimum added value. Even though extensive research into these existing CRE alignment models has provided us with valuable insights into the steps, components, relationships and variables that are needed in the alignment process, these models still fall short in two ways. Most models pay little to no attention to
1 The design of new CRE portfolios;
2 The selection of a new CRE portfolio that adds most value to the organization.
How a CRE manager is able to design and select an optimum alternative in an operational way remains a black box in many alignment models.
In CRE alignment models, the authors generally use either the stakeholder or the shareholder approach. Both approaches received criticism in the past. Kaplan and Norton (2006) state that the shareholder approach with purely financial measures of performance are not sufficient to yield effective management decisions. Jensen (2010) criticizes the stakeholder approach and states that managers in an organization need to define what is better and what is worse which forms the basis of making decisions. In his view, putting them in opposite positions is not correct because both are of a different nature. In fact, Jensen (2010, p. 33) states “ ... whether firms should maximize value or not, we must separate two distinct issues;
1 Should the firm [organization] have a single-valued objective?;
2 And, if so, should that objective be value maximization or something else ...?"
I agree with Jensen’s view that a single-valued objective function is needed, but argue that in our CREM domain a financial measure is not fully suitable. A financial measure is not suitable, because values (also referred to as qualities) of buildings fall in two general categories.
These categories are often interrelated and overlap in practice as explained by Volker (2010, p. 17), the categories are:
–– “technical, physical, hard, functional, objective or tangible qualities;
–– perceptual, soft, subjective, judgmental or intangible values.”
These intangibles are vital to CRE management but often suppressed. Real estate decision making therefore needs to be able to include all of these values in order to be purposeful. If they are treated separately, the restriction is that one effect can be more difficult to monetize than the other effect, as shown by Mouter (2012) and if multiple measures are used as in the stakeholder approach ”if you take one set of quantifiable impacts and one set of non-quantifiable impacts in an appraisal, one set will dominate” (Mishan, in Mouter, 2012, p. 10).
Research aim: The aim of this research is to enhance CRE alignment by improving CRE decision making in such a way that corporate real estate managers are able to determine the added value of a particular corporate real estate strategy quickly and iteratively design many alternative real estate portfolios.
Conclusions about developing the Preference-based Accommodation Strategy design and decision approach
This research successfully developed, tested and evaluated a new design and decision approach in corporate real estate alignment that makes it possible to design alternative CRE portfolios and then to select the portfolio that adds most value to the organization. The originality of this research to (1) define value as technically equivalent to preference and (2) use a design and decision approach for the alignment problem. This new approach is called the Preference-based Accommodation Strategy design and decision approach (PAS). PAS was developed and tested in accordance with the five stages of an operations research project. PAS is constructed upon fifteen basic concepts and definitions from management science, decision theory and design methodology.
Preference Measurement and Preference-Based Design are the most important basic concepts. By using the overall preference (value) score as overall performance measure, based on a single-valued objective function, CRE managers are able to select a new CRE portfolio that adds the most value to the organization. Following Barzilai (2010), all tangible and intangible values are categorized either as physical or nonphysical properties of an object. To enable the application of mathematical operations to these non-physical properties, such as preference, Barzilai (2010) developed a theory of (preference) measurement as well as a practical evaluation methodology Preference Function Modeling for constructing proper preference scales. To enable the design of alternatives the Preference-based Design method (Binnekamp, 2011) is used as particular technique in the domain of design and decision systems. By adjusting this method it can be used on portfolio level.
PAS is structured around three decision making rationalities (Kickert, in De Leeuw, 2002). The three components are; the steps (procedural rationality), the stakeholders & activities (structural rationality) and the mathematical model (substantive rationality) as shown in Figure S.1. The substantive rationality enables the decision maker to choose an alternative based on the bounded rationality perspective. The procedural rationality enables the decision maker to take into account the time perspective when selecting an alternative and the structural rationality enables that more than one decision maker is involved. By using all concepts past experience has benefited the development of PAS. For PAS to be operational all components are connected coherently.
The coherence between the components is shown in a flowchart in Figure S.2. In the steps, decision makers define decision variables representing accommodation aspects that make the accommocation stratgy tangible and iteratively test and adjust these variables by designing new alternative real estate portfolios. The alternative design that adds most value to the organization, i.e. has the highest overall preference score, is the portfolio that optimally aligns real estate to corporate strategy. The activities that the participants perform are a series of interviews and workshops, while the system engineer builds the accompanying mathematical models. The approach overcomes the problems inherent to the current models and uses explicit scales for measuring preference, i.e. value, defined by stakeholders themselves.
Conclusions about testing PAS
PAS is tested successfully in three pilot studies. All pilot studies show that the stakeholders were able to perform all the steps and activities, including the steps to determine preference curves (step 2) and the design alternatives themselves (step 5). The stakeholders were able to design an alternative CRE portfolio with a higher overall preference than in the current situation Table S.1. An added value of 54, 17 and 5 (out of a 100) was achieved either by the stakeholders (in step 5a) or the optimization tool (in step 5b). In the last step, all stakeholders accepted that alternative as the final outcome. Next to that, there is an indication, based on the third pilot study, that the use of the preference curves in PAS improved the representation of the stakeholders preferences than in their current scorecard system.
In the first and third pilot, alternative CRE portfolios have been generated with an optimization tool (step 5b). Due to the nature of third pilot the brute force approach was used successfully in generating a global optimum (see Table S.1). In the first pilot, the algorithm (step 5b) was not able to generate a local optimum because a subset of the alternatives was infeasible. The feasible set of alternatives could not be characterized mathematically and was not available to the algorithm. The brute force approach is preferable to the search algorithm as it finds a global optimum instead of a local optimum but has as disadvantage that it often cannot be used when a pilot is too complex. In PAS, stakeholders design alternatives (step 5a), and use the PFM algorithm to rate them as has been done for the first two pilots.
Conclusions about evaluating PAS; iteration is the key
In all three pilots the stakeholders as well as the observers evaluated PAS very positively. According to the stakeholders, determining preferences and refining and adjusting them in collective workshops is the attractive part of PAS. The participants indicated that, whilst the method of determining preferences is easy, accurately determining which preference is related to a certain decision variable value is not.
Assigning preference scores to decision variable values can be arbitrary at first. By repeating the cycle of determining preferences and making designs a number of times, the stakeholders see the effect of the decisions made in the design, and how their preferences affect those decisions. In all pilot studies the decision makers used the opportunity to either add or remove decision variables and change curves, weights or constraints. The use of such a learning process in the context of work practice and problem solving is described by Schön (1987) as reflection in action.
Conclusions about reflecting upon PAS
PAS as design and decision approach can be used as add-on to existing CRE alignment management models. However, using PAS as add-on in these models creates methodical difficulties. The structure of these models is often not congruent with the PAS structure. To avoid these difficulties, PAS is also described both from a systems’ management perspective (De Leeuw, 2002).
The three pilot studies showed that PAS can be applied in different organizations, and for different types of problems with a different level of complexity. In comparison, the first two pilots were more complex because more stakeholders were involved and more interventions were possible. Applying this approach to multiple context-dependent cases has yielded more valuable results than just applying it to one case. Based on the results of this study, it is justified that PAS can be used for a wide range of real estate portfolio types.
One of the long-standing issues in the field of corporate real estate management is the alignment of an organization’s real estate to its corporate strategy. In the last thirty years, fourteen Corporate Real Estate (CRE) alignment models have been made. In some of these CRE alignment models it is indicated that they strive for maximum or optimum added value. Even though extensive research into these existing CRE alignment models has provided us with valuable insights into the steps, components, relationships and variables that are needed in the alignment process, these models still fall short in two ways. Most models pay little to no attention to
1 The design of new CRE portfolios;
2 The selection of a new CRE portfolio that adds most value to the organization.
How a CRE manager is able to design and select an optimum alternative in an operational way remains a black box in many alignment models.
In CRE alignment models, the authors...
One of the long-standing issues in the field of corporate real estate management is the alignment of an organization’s real estate to its corporate strategy. In the last thirty years, fourteen Corporate Real Estate (CRE) alignment models have been made. In some of these CRE alignment models...
Corporate Real Estate
Corporate real estate is real estate that is necessary for an organization to conduct its business. CRE can be owned or leased space and is different than commercial real estate. CoreNet Global (2015) describes that in commercial real estate, real estate is core business, and the goal is to provide a risk adjusted return to the investor; whereas, in corporate real estate, real estate supports the business function. Corporate real estate represents the demand side or user side of real estate, while commercial real estate focuses on the supply side to meet that demand.
CRE function lacks tools to deliver the most business impact
Sharp (2013) concluded based on 636 survey responses that CRE teams face barriers to meet present challenges. The barriers are “C-suite resistance to capital expenditure; the sometimes small and fragmented structure of the CRE function; inadequate access to deep data and analytics to measure value; and a fundamental skill and knowledge gap within CRE teams ... . Furthermore, many CRE departments lack the tools and training to effectively identify, shape and execute the broader business strategies that would ultimately deliver the most business impact. Only 28 percent regard themselves as ‘well equipped’ to meet the various tactical and strategic demands now being placed upon them” (Sharp, 2013, pp. 232-233).
What if CRE departments were better equipped
... with an approach that enables them to choose the best CRE strategy and portfolio design that adds most value to all stakeholders in the organization?
Corporate Real Estate
Corporate real estate is real estate that is necessary for an organization to conduct its business. CRE can be owned or leased space and is different than commercial real estate. CoreNet Global (2015) describes that in commercial real estate, real estate is core business, and the goal is to provide a risk adjusted return to the investor; whereas, in corporate real estate, real estate supports the business function. Corporate real estate represents the demand side or user side of real estate, while commercial real estate focuses on the supply side to meet that demand.
CRE function lacks tools to deliver the most business impact
Sharp (2013) concluded based on 636 survey responses that CRE teams face barriers to meet present challenges. The barriers are “C-suite resistance to capital expenditure; the sometimes small and fragmented structure of the CRE function; inadequate access to deep data and...
Corporate Real Estate
Corporate real estate is real estate that is necessary for an organization to conduct its business. CRE can be owned or leased space and is different than commercial real estate. CoreNet Global (2015) describes that in commercial real estate,...
This dissertation aims to enhance CRE alignment by approaching alignment as a design and decision process as is explained in chapter 1. The current state of the art in CRE alignment modeling is summarized in paragraph 2.1. This sets the context of this research and will show that CRE alignment is complex and multidimensional. Thereafter, an assessment of CRE alignment models from a design and decision perspective is made in paragraph 2.2. Based on this perspective I identified the scientific gap of this PhD research. Most of the work in this chapter has been published before in the last 10 years. Figure 2.1 shows the timeline of the important publications related to the two topics that this chapter addresses:
1 State of the art of modelling CRE alignment processes;
2 Assessment of structure models of CRE alignment from a design and decision perspective.
As can be seen in the figure below, the different topics have evolved at the same time. I have chosen to structure the chapter around the two topics and not follow the order of publication. Because the topics have evolved over time this causes some redundancy in and between paragraph 2.1 and 2.2. In the last paragraph 2.3 conclusions, they are brought together.
But before showing the state of the art, CRE and CREM are defined. Corporate real estate is a specific type of real estate. CoreNet Global (2015) describes it as the real estate necessary to conduct business—the bricks and mortar of office buildings, manufacturing plants and distribution centres, retail stores, and similar facilities. It can include owned or leased space, buildings, and infrastructure, such as power plants or even airport runways. Corporate real estate is closely related to commercial real estate, however, there is a distinct difference in business objectives. In the commercial real estate world, the business is the real estate. The goal for commercial real estate is to provide a risk adjusted return to the investor; whereas, in corporate real estate real estate supports the business function. In other words, corporate real estate represents the demand side or user side of real estate, while commercial real estate focuses on the supply side to meet that need.
Corporate real estate is seen since 30 years by (Joroff, 1993) as the fifth resource of the business that needs to be managed besides capital, human resources, IT and communication. One of the big challenges in corporate real estate management is reducing the gap between the high speed of business and the slow speed of real estate, i.e. between the so-called dynamic real estate demand and the relatively static real estate supply. A decade later (Krumm et al., 2000, p. 32) described CREM as
“The management of a corporation’s real estate portfolio by aligning the portfolio and services to the needs of the core business (processes), in order to obtain maximum added value for the business and to contribute optimally to the overall performance of the corporation”.
One could say that the authors position CRE alignment in this definition as the raison d’être of CREM. Other authors (Heywood & Arkesteijn, 2017) position CRE alignment as one of the activities that CREM needs to perform. In this research, CREM will be seen as a wide range of activities that must be performed by the corporate real estate manager, while the alignment of CRE with the business will be seen as one of CREM’s activities and is referred to as CRE alignment.
This dissertation aims to enhance CRE alignment by approaching alignment as a design and decision process as is explained in chapter 1. The current state of the art in CRE alignment modeling is summarized in paragraph 2.1. This sets the context of this research and will show that CRE alignment is complex and multidimensional. Thereafter, an assessment of CRE alignment models from a design and decision perspective is made in paragraph 2.2. Based on this perspective I identified the scientific gap of this PhD research. Most of the work in this chapter has been published before in the last 10 years. Figure 2.1 shows the timeline of the important publications related to the two topics that this chapter addresses:
1 State of the art of modelling CRE alignment processes;
2 Assessment of structure models of CRE alignment from a design and decision perspective.
As can be seen in the figure below, the different topics have evolved at the same time. I have chosen to...
This dissertation aims to enhance CRE alignment by approaching alignment as a design and decision process as is explained in chapter 1. The current state of the art in CRE alignment modeling is summarized in paragraph 2.1. This sets the context of this research and will show that CRE alignment...
In this chapter, using basic concepts and definitions from management science, decision theory and design methodology, I shall outline the methodological aspects, characteristics and features of the Preference-based Accommodation Strategy (PAS) design and decision system, which I developed for the formation of a corporate accommodation strategy.
This outline serves first and foremost as a simple way of representing and modeling the PAS design decision system. It also enables the methodological characteristics of PAS design and decision making to be set out in a way that allows analysis and evaluation of the suitability of the applications of this system in real life corporate accommodation strategy processes. Finally, it should be possible to incorporate past experience into the framework, and to generalize and summarize it in order to benefit the further development of the PAS design decision system. The PAS design decision system will be referred to as PAS.
In chapter 2 the existing alignment models were assessed on eight different assessment criteria and it has become clear that decision making receives very little attention in the models. The two main problems were that (1) it remained unclear how alternative CRE strategies are made on portfolio and building level and (2) most problems occur when selecting an alternative; none of the models has an overall performance measure that incorporates both quantitative and qualitative criteria, and uses correct measurement. Although in paragraph 2.2 all assessment criteria have been introduced, some of the concepts will be explained in this chapter. In chapter 2.3 the models have been assessed on their use of correct measurement for instance. In paragraph 3.2 it will be explained what correct measurement is and why it is important.
The chapter is structured as follows:
–– Fifteen basic concepts underlying the PAS design system are explained in paragraph 3.1;
–– Preference measurement as core concept is explained in more detail in paragraph 3.2;
–– Preference-Based Design as other core concept is explained in more detail in paragraph 3.3;
–– A comparison of the foundations in different scientific field in given in paragraph 3.4;
–– The chapter ends with a conclusion and comparison in paragraph 3.5.
In this chapter, using basic concepts and definitions from management science, decision theory and design methodology, I shall outline the methodological aspects, characteristics and features of the Preference-based Accommodation Strategy (PAS) design and decision system, which I developed for the formation of a corporate accommodation strategy.
This outline serves first and foremost as a simple way of representing and modeling the PAS design decision system. It also enables the methodological characteristics of PAS design and decision making to be set out in a way that allows analysis and evaluation of the suitability of the applications of this system in real life corporate accommodation strategy processes. Finally, it should be possible to incorporate past experience into the framework, and to generalize and summarize it in order to benefit the further development of the PAS design decision system. The PAS design decision system will be referred to as PAS.
In...
In this chapter, using basic concepts and definitions from management science, decision theory and design methodology, I shall outline the methodological aspects, characteristics and features of the Preference-based Accommodation Strategy (PAS) design and decision system, which I developed for...
One of the long-standing issues in CREM is the alignment of an organization’s real estate to its corporate strategy as I have shown in chapter 2. CRE alignment is even defined by some as the raison d’être of CREM, as the range of activities undertaken to attune corporate real estate optimally to corporate performance. Even though extensive research into existing CRE alignment models has provided us with valuable insights into the steps, components and variables that are needed in the alignment process, these models still fall short in two ways. Most models pay little to no attention to the design of a new portfolio and to the selection of a new portfolio that adds the most value to the organization.
The Preference-based Accommodation Strategy approach is a design and decision support tool to remedy these shortcomings and thereby enhance CRE alignment. The basic concepts and definitions for PAS have been explained in chapter 3. In this chapter, PAS is presented in its main development phases.
The research methods to develop, test and evaluate PAS are explained in paragraph 4.1. In paragraph 4.2 the main concepts and the three components of PAS are explained. Subsequently, these three components are discussed; the steps of PAS in paragraph 4.3, the stakeholders & activities in paragraph 4.4 and the generic mathematical model in paragraph 4.5. In the last paragraph 4.6, the coherence between the three components is explained as well as the conclusion.
One of the long-standing issues in CREM is the alignment of an organization’s real estate to its corporate strategy as I have shown in chapter 2. CRE alignment is even defined by some as the raison d’être of CREM, as the range of activities undertaken to attune corporate real estate optimally to corporate performance. Even though extensive research into existing CRE alignment models has provided us with valuable insights into the steps, components and variables that are needed in the alignment process, these models still fall short in two ways. Most models pay little to no attention to the design of a new portfolio and to the selection of a new portfolio that adds the most value to the organization.
The Preference-based Accommodation Strategy approach is a design and decision support tool to remedy these shortcomings and thereby enhance CRE alignment. The basic concepts and definitions for PAS have been explained in chapter 3. In this chapter, PAS is presented in its...
One of the long-standing issues in CREM is the alignment of an organization’s real estate to its corporate strategy as I have shown in chapter 2. CRE alignment is even defined by some as the raison d’être of CREM, as the range of activities undertaken to attune corporate real estate...
The focus in this chapter is on the component steps of PAS (see Figure 5.1 and Figure 5.2). CRE alignment is achieved, as has been shown in chapter 4, if stakeholders can use PAS successfully. PAS is successful if the stakeholders are able to perform each step of PAS. I assume that the stakeholders can perform steps 1 (specifying decision variables), 3 (assigning weights) and 4 (determining design constraints) because these type of steps are part of other multi criteria decision analysis as well. However, it is not known if stakeholders are able to perform the new step 2 (determining preferences) and step 5a (design alternatives) and are willing to select the alternative with the highest overall preference score in step 6. Preferably, this new alternative has a higher overall preference score than the overall preference score in the current situation. However, if the boundary conditions are strict this is not always possible. PAS has been tested in three pilots.
This chapter has the following structure:
–– TU Delft pilot for the food facilities in paragraph 5.1;
–– TU Delft pilot for lecture halls in paragraph 5.2;
–– Oracle’s pilot for office locations in paragraph 5.3;
–– Pilot study comparison and conclusion in paragraph 5.4.
The focus in this chapter is on the component steps of PAS (see Figure 5.1 and Figure 5.2). CRE alignment is achieved, as has been shown in chapter 4, if stakeholders can use PAS successfully. PAS is successful if the stakeholders are able to perform each step of PAS. I assume that the stakeholders can perform steps 1 (specifying decision variables), 3 (assigning weights) and 4 (determining design constraints) because these type of steps are part of other multi criteria decision analysis as well. However, it is not known if stakeholders are able to perform the new step 2 (determining preferences) and step 5a (design alternatives) and are willing to select the alternative with the highest overall preference score in step 6. Preferably, this new alternative has a higher overall preference score than the overall preference score in the current situation. However, if the boundary conditions are strict this is not always possible. PAS has been tested in three pilots.
This...
The focus in this chapter is on the component steps of PAS (see Figure 5.1 and Figure 5.2). CRE alignment is achieved, as has been shown in chapter 4, if stakeholders can use PAS successfully. PAS is successful if the stakeholders are able to perform each step of PAS. I assume that the...
PAS consists of three main components; steps, stakeholders & activities, and mathematical models, as explained in chapter 4. In this chapter, the stakeholders & activities are the focal point (see Figure 6.1). By explaining the interactive design process in detail, the reader understands how the stakeholders perform the activities to achieve alignment between the organization and the corporate real estate portfolio.
The stakeholders & activities are displayed in the left column of the flowchart in Figure 6.2. There, the stakeholders that are involved are divided in three types: the responsible management (RM), the stakeholders (S) and the facilitator and systems engineer (F & SE). They need to perform two types of activities: interviews and workshops. In the activity interviews, the stakeholders perform steps 1 to 4. In the activity workshops, the stakeholders perform step 5. They design an alternative corporate real estate portfolio and continue designing other alternatives until they mutually agree that the best possible alternative has been made. The activities are finished when, in the last interview, each stakeholder individually confirms the selection of the best alternative.
The results of the three pilots have been discussed in chapter 5 including the final input the stakeholders have given in the interviews for steps 1 to 4. The best alternative the stakeholders have chosen in step 6 was also presented. This alternative was designed interactively and iteratively in the workshops in step 5. However, how the stakeholders have designed this alterative has not yet been explained. Since, interactively and iteratively designing alternatives in the mathematical models is a major component of PAS this design process is explained in this chapter. This chapter shows the interfaces that the stakeholders can use when designing alternatives including instructions on how to navigate the model.
This chapter presents the pilots as follows:
–– Pilot study 1: TU Delft’s food facilities in paragraph 6.1;
–– Pilot study 2: TU Delft’s lecture halls in paragraph 6.2;
–– Pilot study 3: Oracle’s office locations in paragraph;
–– And the pilot study comparison and conclusion in paragraph 6.4.
For each pilot study, in the first subparagraph, the design interfaces that the stakeholders have at their disposal, are explained. In the second subparagraph, the stakeholders workshop set up is discussed in which they use the interface to design alternatives. Lastly, in the third subparagraph, the iterative process is discussed. The iteration takes place between step 5 (designiWng alternatives) and step 1 to 4 (variables, curves, weights and constraints).
PAS consists of three main components; steps, stakeholders & activities, and mathematical models, as explained in chapter 4. In this chapter, the stakeholders & activities are the focal point (see Figure 6.1). By explaining the interactive design process in detail, the reader understands how the stakeholders perform the activities to achieve alignment between the organization and the corporate real estate portfolio.
The stakeholders & activities are displayed in the left column of the flowchart in Figure 6.2. There, the stakeholders that are involved are divided in three types: the responsible management (RM), the stakeholders (S) and the facilitator and systems engineer (F & SE). They need to perform two types of activities: interviews and workshops. In the activity interviews, the stakeholders perform steps 1 to 4. In the activity workshops, the stakeholders perform step 5. They design an alternative corporate real estate portfolio and continue designing...
PAS consists of three main components; steps, stakeholders & activities, and mathematical models, as explained in chapter 4. In this chapter, the stakeholders & activities are the focal point (see Figure 6.1). By explaining the interactive design process in detail, the reader...
The focus in this chapter is on the component mathematical models of PAS (see Figure 7.1 and Figure 7.2). PAS can only be performed if the system engineers are able to build a mathematical model of the problem situation for each of the pilot studies. In this chapter, I will show that the system engineers were able to do this for all three pilots.
Typically, a subset of the alternative is infeasible. When the feasible set of alternatives can be characterized mathematically, the PFM algorithm can search an optimal alternative within this set (either by an exhaustive search or by sampling, depending on the size of the feasible set). Otherwise, if a characterization of the feasible set is not available to the algorithm, the group decision makers – the stakeholders - can propose possible feasible alternatives for consideration. The algorithm can then rate these alternatives.
This chapter has the following structure:
–– TU Delft pilot for the food facilities in paragraph 7.1;
–– TU Delft pilot for lecture halls in paragraph 7.2;
–– Oracle’s pilot for office locations in paragraph 7.3;
–– Pilot comparison and conclusion in paragraph 7.4.
The mathematical models are explained for each of the pilots as follows: the model structure (first subparagraph), the model formulas (second subparagraph) and the optimization tool (third subparagraph).
Recall, that in step 5 alternatives are generated in two separate ways:
A The group of decision makers self-designs alternatives, use the design constraints to test the feasibility of the design alternatives, and use the PFM algorithm to yield an overall preference score of these feasible design alternatives;
B The system engineer generates feasible design alternatives and uses the PFM algorithm to find the feasible design alternative with the highest overall preference score.
The decision makers are able to design alternatives (step 5a) with the model that is explained in the first and second subparagraphs. The system engineer is able to generate alternatives (step 5b) with the optimization tool is, as is explained in the third subparagraph.
The mathematical models for the pilot studies have been built by the system engineer and the facilitator. The author had the role of the facilitator. The system engineer for the first pilot was Binnekamp, for the second pilot it was Valks with the aid of Barendse, and for the third pilot the system engineers were De Visser with the guidance of De Graaf. Valks and De Visser cooperated in this study as graduate students with the author as their main mentor and Binnekamp, Barendse and De Graaf as their second and/or third mentors.
The focus in this chapter is on the component mathematical models of PAS (see Figure 7.1 and Figure 7.2). PAS can only be performed if the system engineers are able to build a mathematical model of the problem situation for each of the pilot studies. In this chapter, I will show that the system engineers were able to do this for all three pilots.
Typically, a subset of the alternative is infeasible. When the feasible set of alternatives can be characterized mathematically, the PFM algorithm can search an optimal alternative within this set (either by an exhaustive search or by sampling, depending on the size of the feasible set). Otherwise, if a characterization of the feasible set is not available to the algorithm, the group decision makers – the stakeholders - can propose possible feasible alternatives for consideration. The algorithm can then rate these alternatives.
This chapter has the following structure:
–– TU Delft pilot for the food...
The focus in this chapter is on the component mathematical models of PAS (see Figure 7.1 and Figure 7.2). PAS can only be performed if the system engineers are able to build a mathematical model of the problem situation for each of the pilot studies. In this chapter, I will show that the...
In this chapter the evaluation of PAS will be discussed. The use of PAS has been extensively reported in chapters 5 (steps), 6 (stakeholder & activities) and 7 (mathematical model). The use of PAS has been successful, this means that stakeholders are able to use PAS. In this chapter the evaluation of the stakeholders of PAS is discussed. This answers the question if the stakeholders want to use PAS.
Recall, that PAS comprises of steps, stakeholders & activities, and mathematical models. The activities consist of a sequence of interviews and workshops and a simultaneous design and calibration of the mathematical model. The pilots resulted in a final design alternative and a final mathematical model.
The evaluation is given per pilot study and this chapter has the following structure:
–– TU Delft pilot for the food facilities in paragraph 8.1;
–– TU Delft pilot for lecture halls in paragraph 8.2;
–– Oracle’s pilot for office locations in paragraph 8.3;
–– Pilot comparison and conclusion in paragraph 8.4.
In each of these paragraphs, the four types of measurements that Joldersma and Roelofs (2004) use, will be addressed.
In the first subparagraph the stakeholders’ evaluation is discussed. Here, the first three measurements were addressed: (1) experiences with PAS, (2) attractiveness of PAS and (3) participants’ observations on effectiveness of PAS. In general, it is not indicated which particular stakeholder gave feedback if their role in the organization was not relevant for the remark. Only in cases where the role and background of the stakeholder was relevant to their remarks, it is indicated which particular stakeholder gave these remarks. In the second subparagraph, the fourth measurement, namely the observers’ perceptions of the effectiveness of PAS is reported.
In the text, the frequently mentioned positive aspects and areas of improvement are underlined and will be used in the conclusion and pilot comparison.
In this chapter the evaluation of PAS will be discussed. The use of PAS has been extensively reported in chapters 5 (steps), 6 (stakeholder & activities) and 7 (mathematical model). The use of PAS has been successful, this means that stakeholders are able to use PAS. In this chapter the evaluation of the stakeholders of PAS is discussed. This answers the question if the stakeholders want to use PAS.
Recall, that PAS comprises of steps, stakeholders & activities, and mathematical models. The activities consist of a sequence of interviews and workshops and a simultaneous design and calibration of the mathematical model. The pilots resulted in a final design alternative and a final mathematical model.
The evaluation is given per pilot study and this chapter has the following structure:
–– TU Delft pilot for the food facilities in paragraph 8.1;
–– TU Delft pilot for lecture halls in paragraph 8.2;
–– Oracle’s pilot for...
In this chapter the evaluation of PAS will be discussed. The use of PAS has been extensively reported in chapters 5 (steps), 6 (stakeholder & activities) and 7 (mathematical model). The use of PAS has been successful, this means that stakeholders are able to use PAS. In this chapter the...
By now, the PAS design decision method is familiar and it is known that:
1 The Preference-Based Design procedure could be adapted and implemented into an accommodation strategy formation project so that it can be used at real estate portfolio level in CRE alignment process (see chapter 4);
2 The stakeholders were able to perform all PAS design decision steps and accepted the outcome (see chapter 5 and 6);
3 The facilitator and the systems engineers were able to represent the pilots in mathematical decision models (see chapter 7), and;
4 The stakeholders evaluated PAS design decision method positively (see chapter 8).
In paragraph 9.1 it is shown that the PAS design decision method can be used as add-on to current CRE alignment management models. However, using the PAS method as add-on in these models creates managerial and methodical difficulties. The structure of these models is often not congruent with the structure of the PAS method (see chapter 2). An add-on of the PAS method in an alignment model does not fit well. To avoid these difficulties in the pilot studies a specific CRE alignment management system is set up which is congruent with the PAS design decision system: the PAS design decision management system.
The PAS design decision method has been structured from a decision making perspective around Kickert’s three rationalities (components) (in De Leeuw, 2002). To complete PAS, PAS is described solely as design method in paragraph 9.2. In paragraph 9.3 the PAS management system is structured from a systems’ management perspective. From this perspective the three components can be described from the organizations’ point of view as well as the CRE manager and facilitator that executes PAS. Management as such is seen as steering in this thesis as is explained in chapter 3. PAS management system is defined based on a systems perspective as following the chosen basic concepts and definitions as explained in paragraph 3.1.14 and 3.1.15.
By now, the PAS design decision method is familiar and it is known that:
1 The Preference-Based Design procedure could be adapted and implemented into an accommodation strategy formation project so that it can be used at real estate portfolio level in CRE alignment process (see chapter 4);
2 The stakeholders were able to perform all PAS design decision steps and accepted the outcome (see chapter 5 and 6);
3 The facilitator and the systems engineers were able to represent the pilots in mathematical decision models (see chapter 7), and;
4 The stakeholders evaluated PAS design decision method positively (see chapter 8).
In paragraph 9.1 it is shown that the PAS design decision method can be used as add-on to current CRE alignment management models. However, using the PAS method as add-on in these models creates managerial and methodical difficulties. The structure of these models is often not congruent with the structure of the PAS method (see...
By now, the PAS design decision method is familiar and it is known that:
1 The Preference-Based Design procedure could be adapted and implemented into an accommodation strategy formation project so that it can be used at real estate portfolio level in CRE alignment process (see chapter...
Even though extensive research into existing CRE alignment models has provided us with valuable insights into the building blocks, components and variables that are needed in the alignment process, these models still fall short in two ways. Most models pay little to no attention to (1) the design of new CRE portfolios and (2) the selection of a new CRE portfolio that adds the most value to the organization. With the development of a new approach, the Preference-based Accommodation Strategy design and decision approach (PAS), I address the deficiencies of the previous alignment models that either place too much emphasis on financial measures or lack clarity in decision making due to the difficulties of quantifying the intangible and subjective. In this chapter the main research question will be answered and recommendations for further research are formulated.
How can the Preference-based Accommodation Strategy design and decision approach (PAS) successfully be developed and tested on corporate real estate portfolio level in order to enhance CRE alignment?
Even though extensive research into existing CRE alignment models has provided us with valuable insights into the building blocks, components and variables that are needed in the alignment process, these models still fall short in two ways. Most models pay little to no attention to (1) the design of new CRE portfolios and (2) the selection of a new CRE portfolio that adds the most value to the organization. With the development of a new approach, the Preference-based Accommodation Strategy design and decision approach (PAS), I address the deficiencies of the previous alignment models that either place too much emphasis on financial measures or lack clarity in decision making due to the difficulties of quantifying the intangible and subjective. In this chapter the main research question will be answered and recommendations for further research are formulated.
How can the Preference-based Accommodation Strategy design and decision approach (PAS) successfully be developed...
Even though extensive research into existing CRE alignment models has provided us with valuable insights into the building blocks, components and variables that are needed in the alignment process, these models still fall short in two ways. Most models pay little to no attention to (1) the...