Corporate Real Estate alignment: A preference-based design and decision approach

  • Monique Arkesteijn TU Delft, Architecture and the Built Environment

Synopsis

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.

Author Biography

Monique Arkesteijn, TU Delft, Architecture and the Built Environment

In 1993 Monique was one of the first four graduate students of the Faculty of Architecture's Master track "Bouwmanagement & Vastgoedbeheer", the current department of Management in the Built Environment (MBE), at the Delft University of Technology. She graduated with distinction on ‘productivity and real estate, privacy and communication in offices’ at the "Rijksgebouwendienst" (Central Government Real Estate Agency). Her drive for real estate management lies in her focus on people and processes, which has guided her in her entire professional life.

She worked four years as consultant for Starke Diekstra / Arcadis and was involved in building projects in the Netherlands and the Netherlands Antilles. From 1998 to 2000 Monique was senior real estate consultant and partner of Diephuis Stevens, where she worked on projects ranging from 20 to 1000 workplaces with investments up to 50 million euros. During this period she obtained an Executive Master of Business Administration degree at TSM Business School (1998 – 2000). After working in practice for seven years, Monique travelled the world, and spent years in India, Brasil and La Gomera, Spain.

Since 2003 Monique works as assistant professor Real Estate Management for the department of Management in the Built Environment (MBE). In the beginning she combined her work as assistant professor with freelance consultancy. From 2010 she focused full time on her work at university.

Monique is a passionate teacher and loves interactive teaching. She is responsible for the BSc (Bachelor) course on briefing (350+ students) and has coordinated the Real Estate Management MSc (Master) course for many years. Monique specializes in corporate real estate alignment and divides her work in three main areas: first and foremost her work is about a design and decision approach to CRE alignment.

Her aim is to enhance CRE alignment by combining heart and head, when designing corporate real estate solutions. Next to that, she worked amongst others with Chris Heywood from the University of Melbourne on a systematic comparison of CRE alignment models in theory. Together with colleagues and graduate students she studies how CRE alignment is done in practice.

From 2013 to 2018 she was head of the real estate management section at MBE. With professor Alexandra den Heijer, Monique leads the Campus Research Team. Next to her work on CRE alignment she has focused on alignment for municipal and educational real estate. During the last 10 years she coordinated and/or participated in the think tank ‘Envisioning the Faculty of the Future’ (2009), Campus vision 2030 TU Delft (2010), Ownership of museum real estate (2012), Campus NL (2016), Campus tools (2017 - ongoing), European campus (2019). Monique has published more than 30 journal papers and books and received an "Outstanding paper award" for the paper Designing a preference-based accommodation strategy: A pilot study at Delft University of Technology in 2016 from the Journal of Corporate Real Estate.

Besides TU Delft Monique regards CoreNet Global as her second work family. CoreNet Global is the world’s leading association for corporate real estate with more than 11.000 members. She served on the Global Board from 2015 to 2019 after being involved in the Benelux chapter board as member and chairwomen for many years. Recently, together with Jose Zwerink, Monique started the foundation We- Women-Cooperate (WWC), which strives for sustainable progress for Indian women. By connecting people, ideas & products, WWC brings affordable and sustainable energy to India, giving women room for economic development.

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Details about this monograph

ISBN-13 (15)
9789463662260
Date of first publication (11)
2019-11-01
Rights
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.