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40 Journal of Financial Planning | S E P T E M B E R 2 0 1 0 www.FPAjournal.org
Contributions
David B. Yeske, D.B.A., CFP®, holds an appointment as
Distinguished Adjunct Professor in Golden Gate
University’s Ageno School of Business and is a managing
director of Yeske Buie, a wealth management firm with
offices in Vienna, Virginia, and San Francisco, California.
The research reported in this article is based
on Yeske’s doctoral dissertation, the full text of which can
be found at http://ssrn.com/author=646759.
After four decades of growth anddevelopment, the financial plan-ning profession is still without an
overarching framework for organizing andtesting the strategy-making activities of itspractitioners. The profession lacks, inother words, a theory for where planningcomes from. This observation is not newand has been shared by a growing numberof academics and practitioners over thepast decade. In 2002, Guy Cumbie, thenchair of the Financial Planning Association(FPA), bemoaned the “embarrassinglygaping hole in the personal financial plan-ning profession’s body of knowledge in thearea of planning” (Accounting Today, 2002).Warschauer, meanwhile, has observed that“we have poor theory to guide the practiceof financial planning” (2002), while BlackJr. et al point out that “the PFP field hasevolved largely devoid of a theoreticalfoundation” (2002). This research is meantto begin to address this gap by developingan integrating framework for the strategy-making activities of financial planners andthen empirically testing that model againstappropriate measures of success.But how can we measure success?
A long-standing marketing message of theFinancial Planning Association declares that“Planning pays off.” But how do we knowthat’s true, and how might we measure it?Like many other professional services, afterall, financial planning possesses high cre-dence properties (Sharma and Patterson,1999), which means that the quality of theservice is difficult to judge, even after it hasbeen delivered. This is easy to see when youconsider that financial planners are rou-tinely asked to develop strategies for attain-ing goals that are many years or evendecades into the future. So, if we cannotwait decades to see whether a particular
approach to planning has “paid off,” whatcan we observe in the present that mightprovide us with a more immediate measure?The answer that has emerged over the lastdozen years through a series of research ini-tiatives within the financial planning profes-sion is centered on measures of client trustand relationship commitment. Client trust and commitment are attrac-
tive variables on which to focus, as any-thing that maximizes a client’s trust in thefinancial planner and commitment to thefinancial planning relationship can leaddirectly to positive outcomes. These includehigh acquiescence, a low propensity to
Finding the Planning in FinancialPlanningby David B. Yeske, D.B.A., CFP®
Y E S K E
• After four decades, the financial planning
profession still lacks an overarching
framework for organizing and testing
the strategy-making (that is, “planning”)
activities of its practitioners.
• An integrating framework is proposed
that consists of five modes of strategy-
making: planner-driven, data-driven,
policy-driven, relationship-driven, and
client-driven.
• Each of these five modes represents a
different relative role for the planner
and client in the planning process. The
modes also fall along a parallel dimen-
sion of planning versus emergence.
• The proposed model is tested against
measures of client trust and relation-
ship commitment, and the policy-
driven mode is found to be the most
powerful predictor of both.
• Client complexity is also analyzed as a
predictor of client trust and commit-
ment, and it is found that trust and com-
mitment are inversely related to the
complexity of a client’s circumstances.
• Finally, a factor analysis of planner
strategy-making activities shows that
planners in independent firms tend to
favor data- and policy-driven approaches
and those practicing at large financial
services firms tend to be more domi-
nant in the planner-driven mode.
Executive Summary
• After four decades, the financial planning
profession still lacks an overarching
framework for organizing and testing
the strategy-making (that is, “planning”)
activities of its practitioners.
• An integrating framework is proposed
that consists of five modes of strategy-
making: planner-driven, data-driven,
policy-driven, relationship-driven, and
client-driven.
• Each of these five modes represents a
different relative role for the planner
and client in the planning process. The
modes also fall along a parallel dimen-
sion of planning versus emergence.
• The proposed model is tested against
measures of client trust and relation-
ship commitment, and the policy-
driven mode is found to be the most
powerful predictor of both.
• Client complexity is also analyzed as a
predictor of client trust and commit-
ment, and it is found that trust and com-
mitment are inversely related to the
complexity of a client’s circumstances.
• Finally, a factor analysis of planner
strategy-making activities shows that
planners in independent firms tend to
favor data- and policy-driven approaches
and those practicing at large financial
services firms tend to be more domi-
nant in the planner-driven mode.
Executive Summary
Contributions
leave, a high degree of cooperation, andfunctional conflict (that is, the ability tomaintain a highly functional relationshipeven when conflicts arise) (Hunt andMorgan, 1994). These qualities tend to leadto long-lasting relationships and are associ-ated with greater client openness in disclos-ing personal and financial information,greater cooperation in implementing plan-ning recommendations, and a greaterpropensity to make referrals (Sharpe andAnderson, 2008). The concept of client trust and commit-
ment as key mediating variables first arosein the relationship marketing literature,notably in the work of Morgan and Hunt(1994), who attempted to identify theantecedents of trust and commitment.Among their proposed predictors wererelationship termination costs (that is,switching costs), relationship benefits,shared values, communication, and oppor-tunistic behavior.Christiansen and DeVaney (1998) subse-
quently applied this same model to finan-cial planners and found that relationshiptermination costs, relationship benefits,and shared values were all strong predic-tors of commitment. Shared values, com-munication, and opportunistic behavior,meanwhile, were strongly predictive oftrust, which itself was a strong predictor ofcommitment. Communication was thesingle most powerful antecedent to trustand commitment, acting directly on trustand through trust on commitment.Sharma and Patterson (1999) also
addressed the question of whichantecedents most influenced client trustand commitment within the financial plan-ning relationship. As noted, these authorsobserved that financial planning is a “highcredence” service that unfolds over time,leaving clients hard pressed to judge thequality of the advice in the presentmoment. They go on to explain:
After all, if clients have trouble evalu-ating outcomes, then it seems reason-able that interactions (“how” the serv-ice is delivered) and all forms of
communication will take on added sig-nificance as clients seek to minimizedissonance and uncertainty about theadviser they have chosen.
The authors explored the links betweenperceptions of technical quality (what wasbeing delivered), functional quality (how itwas being delivered), and communicationeffectiveness on the one hand, and rela-tionship commitment on the other. Theyfound that a client’s perception of the tech-nical and functional quality of the planner’sadvice was positively correlated with theclient’s level of trust in the planner. Higherlevels of trust, in turn, were associatedwith higher levels of commitment to therelationship. Communication effectiveness,meanwhile, acted directly on trust andcommitment and also indirectly throughits effect on perceived technical qualityand functional quality.
Sharma and Patterson (2000) laterreturned to the examination of theantecedents of relationship commitment,examining the role of trust and a new vari-able: satisfaction. They tested the effect oftrust and satisfaction on commitment inlight of three contingencies: switchingcosts, the availability of attractive alterna-tives, and prior experience. They foundthat trust had the greatest effect on com-mitment when switching costs were high,perceived alternatives were low, and/orprior experience was low. In situations inwhich switching costs were low, perceivedalternatives were high and/or prior experi-ence was high, satisfaction was the domi-nant antecedent to commitment. Thiswork proved illuminating when unex-pected results turned up in the presentresearch, as will be described later.Sharpe, Anderson, White, Galvan, and
Siesta (2007) extended the work of
Y E S K E
www.FPAjournal.org S E P T E M B E R 2 0 1 0 | Journal of Financial Planning 41
Figure 1: Antecedents to Trust and Commitment—Christiansen & DeVaney
Relationship Switching Costs
Relationship Bene�ts Commitment
Trust
Opportunistic Behavior
Communication
Shared Values
Christiansen & DeVaney (1998)
erugiF
Relationship Switching Costs
n:1 atsurTTrotstnedecetnA
Relationship Switching Costs
esnaitsirhC—tnemtimmoCdn
Christiansen & DeVaney (1998)
yenaVVaeD&ne
Christiansen & DeVaney (1998)
Relationship Bene�ts
Opportunistic Behavior
Communication
Shared Values
Commitment
Trust
Figure 2: Technical Quality, Functional Quality, and Communication Effectiveness
Communication E�ectiveness
Functional Quality
Relationship Commitment
Trust
Technical Quality
Sharma & Patterson (1999)
erugiF
eness
:2
tivecffEunc F,, Fyy,ualital QechnicTTechnic
Sharma & Patterson (1999)
ommunic and C,, and Cyy,ualittional Qunc tion aommunic
Communication E�ectiveness
Functional Quality
Technical Quality
Relationship Commitment
Trust
Relationship Commitment
Contributions
Christiansen and DeVaney (1998) andSharma and Patterson (1999, 2000) byfocusing solely on the communicationdimension. They derived the communica-tion elements to be examined from thelife planning literature and organized itinto three dimensions: communicationtasks, communication skills, and commu-nication topics. They found that the fol-lowing were most highly valued by finan-cial planning clients:
Communication tasks• Systematic process to clarify goals andvalues
• Explaining how advice reflects goalsand values
Communication skills• Eye contact, body language, verbalpacing
• Facilitating difficult conversationsabout money
Communication topics• Client values and quality of life• Initiating conversations about lifechanges
In discussing the virtues of the life plan-ning approach to client interactions, theauthors state: “Using a life planning
perspective, the planner’s role shifts frommaximizing a client’s investment returns tohelping the client utilize financialresources to construct a meaningful life.”
Developing the Model: Themes from theFinancial Planning Literature
As one surveys the financial planning litera-ture of the past 40 years, three major themesor clusters naturally emerge. The oldest and
largest of these is the “quantitative tools”cluster. To a significant degree, this clusterrepresents the adaptation of traditional toolsof financial and economic analysis to indi-viduals and families. These offerings includesuch things as Warschauer’s (1981) uniformrisk-liquidity balance sheet and Hopewell’s(1997) introduction of stochastic modeling,especially Monte Carlo analysis. FollowingHopewell, stochastic modeling became aregular topic in the literature, including fur-ther forays by Kautt and Hopewell (2000)and Kautt and Wieland (2001). Other exam-ples of this cluster are scenario planning(Ellis, Feinstein, and Stearns, 2000), discreteevent simulation (Houle, 2004), and sensi-tivity simulations (Daryanani, 2002).A second thread running through the
financial planning literature involvesprocess-oriented techniques. These gener-ally take the form of decision rules and aremeant to provide a framework for rapiddecision-making in the face of changingexternal circumstances. As elsewhere, thisarea has seen the direct adoption by finan-cial planners of tools and techniques devel-oped in other fields, including, for exam-ple, the use of investment policies (Boone
and Lubitz, 1992, 2004).Another example is policy-based financial planning, anidea first proposed by Hallmanand Rosenbloom (1987) andlater developed by Yeske andBuie (2006). Policy-basedfinancial planning involves thedevelopment of statements(policies) that capture whatclients intend to do and howthey intend to do it in terms
not limited to the present circumstances.Policies are meant to be enduring touch-stones that keep clients anchored to anappropriate course of action, especially inturbulent environments. As such, it isimportant for clients to see their ownvalues, beliefs, and goals reflected in thepolicies if they are to fully embrace them.Also found within this process-oriented
cluster are concepts such as opportunisticrebalancing (Daryanani, 2008) and safe
withdrawal rates, especially thoseapproaches that incorporate active decisionrules or policies (Guyton, 2004; Guytonand Klinger, 2006). As with policy-basedfinancial planning, and unlike approachesinvolving static withdrawal rates, the deci-sion rules developed by Guyton andKlinger are most efficacious with the activeunderstanding and participation of clients. The third major theme within the finan-
cial planning literature directly addressesthis need for a deeper understanding ofclients’ beliefs, values, and motivations.This area has been variously called interiorfinance, financial life planning, and lifeplanning. Examples include the work ofWagner (2002) in the area of interiorfinance (a term he coined), Kinder’s(2000) Seven Stages of Money Maturity,Kinder and Galvan’s (2005) EVOKEsystem, and Kahler’s (2005) financial inte-gration framework. Carol Anderson andMitch Anthony, meanwhile, coined theterm “financial life planning,” and muchwork has been done under that label(Diliberto and Anthony, 2003; Anthony,2005; Diliberto, 2006).One notable aspect of the work being
done on the interior dimension is that it isnot limited to offering new perspectivesbut has generated many specific tools andtechniques for improving the discoveryprocess. On this point, it’s worth recallingthat one of the key findings of the Sharpe,Anderson, White, Galvan, and Siesta(2007) research was that clients place ahigh value on a “systematic process forclarifying goals and values.” When viewed as a whole then, much of
the financial planning literature seems tonaturally fall into the following categories:• Quantitative tools• Process-orientation• Interior dimension
Developing the Model: Perspectives fromStrategic Management
No overarching framework has been pro-posed for how the three major themes foundwithin the financial planning literature
42 Journal of Financial Planning | S E P T E M B E R 2 0 1 0 www.FPAjournal.org
Y E S K E
“It is important for clients to see
their own values, beliefs, and goals
reflected in the policies if they are to
fully embrace them.”
Contributions
might be meaningfully incorporated into acomplete theory of strategy-making byfinancial planners. A review of the strate-gic planning literature, however, offereduseful perspectives for organizing thesethree lines of development.Two themes that emerge explicitly from
the strategic management literature andimplicitly from the financial planning liter-ature involve the concepts of rationalityand involvement. Rationality refers to thedegree to which planning can be formal-ized, quantified, and controlled, whileinvolvement refers to the relative rolesplayed by the participants in the planningprocess. In the case of strategic manage-ment, the two groups that define thedegree of involvement or the roles dimen-sion are top managers and all other organi-zational participants (Hart and Banbury,1994). In the financial planning context,relative involvement or roles are dividedbetween the financial planner and theclient. The rationality dimension can alsobe thought of as the role of planning versusemergence in the development of strate-gies. This refers to the dynamic tensionbetween classical, deterministic notions ofthe planning process and the more itera-tive, adaptive approaches proposed bythose who believe the world is too chaoticfor highly structured methodologies(Mintzberg and Waters, 1985). Hart (1992) proposed an integrative
framework for the strategy-making processthat offered resonance for thinking aboutthe financial planning process. His modelconsisted of five broad approaches to strategy-making that were distinguished bythe relative roles of top managers andother members of the organization. Thesemodes emerged from three themes thatHart found in the strategic managementliterature: rationality, vision, and involve-ment. Hart’s five modes fall along the dualdimensions of planning versus emergenceand roles/involvement. Our three financialplanning clusters cannot only be seen tofall along the planning versus emergencespectrum, they can just as clearly be seento fall along the related dimension of rela-
tive roles or involvement as described byHart. It’s clear that the role of the financialplanner is the dominant one wheneverthere’s an emphasis on quantitative tools,just as, at the opposite end of the involve-ment spectrum, the techniques found inthe life planning literature require theactive participation and engagement ofplanner and client. Process-orientedapproaches fall midway between these two,requiring greater participation by clientsthan the quantitative tools techniques, butmore formal planning on the part of thefinancial planner than is found in pure lifeplanning approaches.Brews and Hall (1999) also explored the
issue of formal planning versus incremen-talism (emergence) and how both aremoderated by environment. What theyfound is that formal planning is a neces-sary element of successful firm adaptationin stable and chaotic environments, whilepolicy-based approaches are most effectivewhen conditions are unstable. Theirresults suggest that it’s not a matter ofplanning versus emergence so much asplanning and emergence. Or as Brews andHall put it, “Instead of being the antithesisof incrementalism, formal specific plan-ning may be a necessary precursor to suc-cessful incrementalism ... both are neces-sary, neither is sufficient.” This notion ofplanning as a function of the complexity ofthe environment was also explored in thepresent research.In the next section, we will describe a
framework in which the dominant modesof strategy-making by financial plannersare organized in terms of the planningversus emergence dynamic and the relativeroles and involvement of planner andclient in the process.
An Integrative Framework for Strategy-Makingby Financial Planners
As just noted, the dominant themes foundin the financial planning profession’s bodyof knowledge can readily be organizedalong the planning versus emergence spec-trum. If we also wish to explore the rela-
tive roles of financial planner and client,however, we must first enumerate thoseroles and activities that are part of theplanning process. Combining the activitiesimplicit in CFP Board’s six-step processwith two additional functions or activitiesthat have been proposed as part of anexpanded discovery process, namely“vision” (Kinder, 2000; Kahler, 2005;Diliberto, 2006) and “exploration” (Kinderand Galvan, 2005), yields the followingseven roles: 1. Vision2. Exploration3. Goal-setting4. Analysis5. Strategy formation6. Implementation7. ReviewStarting with the relative roles or
involvement dimension, the financialplanning literature would seem to suggestfive distinct modes of strategy-making:three corresponding to the main clustersalready identified in the literature andtwo more that represent extreme end-points. These five modes have been titled:planner-driven, data-driven, policy-driven, relationship-driven, and client-driven. And just as was the case withstrategic planning, when financial plan-ning is organized along this roles/involve-ment dimension, we also find it fallingnaturally along the rationality dimension. The five modes and the related focus of
each can be found in Figure 3, along with alist of the relative roles and responsibilitiesof planner and client associated with eachmode. Table 1, meanwhile, lists some ofthe key tools and techniques associatedwith each mode.As noted earlier, the three lines of devel-
opment that clearly dominate the financialplanning literature are related to quantita-tive tools, process-orientation, and interiordimension. In our proposed strategy-making framework, these correspond to thedata-driven, policy-driven, and relationship-driven modes, respectively. We’ll begin ourdetailed description with these threemodes, which fall along the center of our
Y E S K E
www.FPAjournal.org S E P T E M B E R 2 0 1 0 | Journal of Financial Planning 43
Contributions
planning-versus-emergence and planner-client roles/responsibilities dimensions.
Data-Driven Mode. The data-drivenmode has quantitative analysis as its focus.The financial planner is the dominantplayer in this mode because of the trainingand expertise needed to use and interpretthe sophisticated techniques that are itsdominant characteristic. In considering therelative roles of financial planner andclient, we must first consider the fact thatthese quantitative tools are designed todeliver optimal solutions based on objec-tive goals. Goal-setting, therefore, is where
the process begins. And for the client, thisis also where the process ends. For all therest, these tools and techniques requireexpert knowledge, both in their applicationand the interpretation of results. Likewise,strategies based on quantitative analysistend to possess a high technical contentand therefore require expert knowledge toimplement and review.
Policy-Driven Mode. The policy-drivenmode has decision rules as its focus. Thereis greater balance in the roles of financialplanner and client. In part, this is becauseclients’ interior dimension, their vision and
personal values, are an explicit input to theprocess (Yeske and Buie, 2006). Clients arealso more deeply involved in implementa-tion, because the purpose of decision rulesis to put the clients more in control oftheir financial decision-making (Yeske andBuie, 2006; Guyton and Klinger, 2006).Finally, clients have a greater role in reviewas well, because policies and other decisionrules are meant to be durable guides in theface of cyclical changes, while it is onlyfundamental change in client circum-stances or values that will trigger a need torevisit and revise.
Relationship-Driven Mode. The focus ofthe relationship-driven mode is explorationand learning. Of necessity, the client role isexpanded even further as they engage in adynamic and iterative process of explo-ration and discovery (Kinder, 2000; Kahler,2005; Kinder and Galvan, 2005; Diliberto,2006). This strategy-making mode is notfocused on analysis, strategy development,or implementation, but toward enhanceddiscovery at the beginning of the process(or whenever it is being revisited) andimproved communication throughout. Themore technical aspects of financial plan-ning tend to be taken for granted. In anycase, the client is of necessity a full partici-pant in all but the analysis and strategydevelopment activities, although the clientis expected to actively validate any strate-gies that might be recommended (Anthesand Lee, 2001).While the three categories just described
appear robust and are well represented inthe literature, they are also incompletewhen viewed along the planner-clientroles/responsibilities dimension. There aretwo more modes that are readily observedat work in the world that must beaccounted for. These remaining modes rep-resent extreme end-points on the interac-tion spectrum and can be described asplanner-driven at one end and client-driven at the other. Interestingly, whilethese modes do not occupy much of thefinancial planning literature, which tendsto be aspirational in nature, there is reasonto believe that they may actually be the
44 Journal of Financial Planning | S E P T E M B E R 2 0 1 0 www.FPAjournal.org
Y E S K E
Table 1: Tools & Techniques Associated with Modes of Strategy-Making
Client-DrivenRelationship-DrivenData-DrivenPlanner-Driven Policy-Driven
ValidationLearningQuantitative
AnalysisSolutions Decision Rules
Tools/Tech
niqu
es
Generic strategies
Turnkey programs
O�-the-shelf solutions
“Canned plans”
Ratio analysis
Monte Carlo simulations
Sensitivity analysis
Real options
Discrete eventsimulation
Life-cycle investing
Scenario learning
Portfolio optimization
Financial planning policies
Safe withdrawal rates
Investment policies
Rebalancing rules
Integral �nance
7-States of Money Maturity
EVOKE
Financial life planning
Appreciative inquiry
Financial integration
Behavioral �nance
Motivational interviewing
Values-based planning
On-demand hourly
HR education
Online advice
T1lbT ols & T
Mhtied tciaechniques A
ingaky-Mttrdes of S
echn
ique
s
tions
ensitivit
echniques A:1elbaTTa TTechniques Aols & oTTo
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earL
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es
regtnIs
estmenvnIy
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lo are C
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ingaky-Megtatrdes of So
ly
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ear tionalidaVValida
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HR educaoney
hourdemand On-e
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esting
optimiza
ning
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eal options
sis
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anned plansC“
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VValues-based planning
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optimizaolio
cle
tene ev
tion
g
alues-based planning
e
y
e planning
niweirvetnilan
�nancal
aregtinancial in
e inquirtiv
inancial lif
Figure 3: Planner-Client Roles and Responsibilities
Planner-Driven Data-Driven Policy-Driven Relationship-Driven Client-DrivenFocus Solutions-Based Quantitative Analysis Decision Rules Learning Validation
Vision VisionGoal-Setting Goal-Setting Goal-Setting Goal-Setting
Strategies Analysis Analysis Exploration Analysis Implementation Strategies Strategies
Implementation ImplementationReview Review Vision
Goal-SettingExplorationVision
AnalysisGoal-SettingStrategiesExploration
ImplementationVision
ReviewGoal-Setting Goal-Setting
Implementation Review
Client Roles & Responsibilities
Plan
ner R
oles
& R
espo
nsib
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s
Solutions-Based
erugiF
Goal-Setting
Plan
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& R
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FocusPlanne
Analysis
t Roles and Resp:3 lienlanner-CP
Goal-SettingGoal-Setting
QuantitativeSolutions-BasedData-Driven-DrivenrPlanne
Learning
onsibilitiest Roles and Resp
isionVisionVVision
Relationship-DrivenDecision RulesPolicy-Driven Relationship-Driven
LearningPolicy-DrivenDecision Rules
alidationVValidationClient-DrivenRelationship-Driven
ImplementationStrategies
Goal-Setting
Plan
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oles
& R
espo
nsib
ilitie
sPl
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r Rol
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s
ImplementationGoal-Setting
ReviewImplementationImplementation
StrategiesImplementationAnalysisStrategies
Goal-SettingGoal-Setting
Review Implementation
Goal-SettingisionVVision
ImplementationExploration
Goal-SettingisionVVision
ReviewImplementation
StrategiesExplorationAnalysis
Goal-SettingGoal-Setting
Client Roles & Responsibilities
ReviewImplementation
StrategiesAnalysis
ExplorationGoal-Setting
isionV
Analysis Client Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & ResponsibilitiesClient Roles & Responsibilities
AD
45
Contributions
most representative of actual practiceamong those engaged in the delivery offinancial advice.
Planner-Driven Mode. The planner-driven mode is focused on solutions. Inthis mode, the financial planner sets thedirection (Diliberto, 2006) and controlsthe process. The client enters the processprimarily as a consumer of financial serv-ices and products. Because this modeinvolves the use of generic strategies, turn-key programs, and off-the-shelf solutions,the client does not even enter the processat the goal-setting level. More often, it isthe planner’s preconceptions that deter-mine the direction of advice. While theplanner-driven mode can be found withsolo practitioners and other independentplanning firms, it would be expected to bethe dominant form for large financial serv-ices companies offering financial planningservices (Anthes and Lee, 2001).
Client-Driven Mode. The focus of theclient-driven mode is validation. The finan-cial planner enters the relationship at thelevel of analysis and possibly strategy-making. This leaves all the other elementsof the planning process to the client,though it is by no means a certainty thatclients will carry out those other activities(that is, vision, goal-setting, exploration,implementation, and review). The processis client-driven because the client decideswhere, when, and under what circum-stances the planner is invited into theprocess. The specific forms under whichthis mode can be found range from hourlyon-demand planning offices, where theplanning engagement begins and ends withthe office appointment (Lee, 2002), toweb-based advice. In the case of web-basedadvice, planners may charge an hourly (orper minute) fee or “bid” a fixed-fee basedon a detailed client request.While the five strategy-making modes
described above are cohesive and well-represented in the literature, there is nosuggestion being made that individualplanners or firms will possess capabilitiesin only one mode. Indeed, it is assumedthat more often than not financial planners
or firms possess capabilities in multiplemodes, employing different modes andcombinations as circumstances warrant.
Relating Strategy-Making Capabilities to ClientTrust and Commitment
Having proposed the foregoing frameworkfor explaining the strategy-making activi-ties of financial planners, the next step wasto empirically test it with financial plan-ners and their clients. Specifically, twohypotheses were tested:1. Because prior research suggested thata more balanced level of planner andclient involvement in the planningprocess would be positively related totrust and commitment (Christiansenand DeVaney, 1998; Sharma and Pat-terson, 1999, 2000; Sharpe et al,2007), we proposed that the data-,policy-, and relationship-driven modeswould be more predictive of clienttrust and commitment than the lessbalanced planner- and client-drivenmodes. This hypothesis was tested byregressing the trust and commitmentvariables on each of the 5 strategy-making predictor variables in turnusing ordinary least squares (thus, 10regression models were estimated).Univariate regression was choseninstead of multiple regression due tothe relatively small sample size formatched planner-client responses (seethe Methodology section below).Hypothesis 1: The data-driven, policy-
driven, and relationship-driven modes ofstrategy-making will be more correlatedwith client trust and commitment thanwill the planner-driven and client-drivenmodes.
2.Wagner (1999) has suggested thatplanning strategies need not be com-plex for those whose circumstancesare simple, while Langrehr (1991)identified the factors that added to thecomplexity of a client’s life circum-stances and must be accounted for inthe planning process. A significantpart of the financial planning litera-
ture is devoted to planning for changeand transition, voluntary and other-wise (Diliberto and Anthony, 2003;Anthony, 2005; Diliberto, 2006). Itwas proposed that client trust andcommitment would be greater forclients with complex circumstancesthan for those whose circumstancesare simple. Testing client complexityseparately from strategy-makingmodes allowed for the use of a muchlarger dataset as all of the clientresponses could be used (n=325). Hypothesis 2: Client trust and commit-
ment will be positively related to thecomplexity of a client’s circumstances.
A factor analysis was also performed in order to explore how the proposed strategy-making modes were actually usedby planners as a function of firm size andmode of practice.
Methodology
Financial planner members of FPA whohad not opted out of research solicitationswere invited to participate in a survey, andthose who participated were also asked toinvite some or all of their clients to partici-pate in a companion survey. A uniquenumerical identifier was provided to eachplanner participant and by having clientsenter this number into their own survey,client and planner responses could bematched. The planner questionnaire col-lected information related to mode of prac-tice, relative roles of planner and client,tools and techniques employed, and size offirm. The client questionnaire collectedresponses related to client trust and rela-tionship commitment, and the complexityof family and financial circumstances. Theinvitation went to 14,756 members andwas repeated three times over the course offive weeks.The necessity of using the financial plan-
ner respondents as the gateway to theirclients would suggest a significant opportu-nity for bias in the client sample. Therewas every reason to believe that plannerswould direct only their “best” clients to the
46 Journal of Financial Planning | S E P T E M B E R 2 0 1 0 www.FPAjournal.org
Y E S K E
Contributions
survey, not least because planners wouldreason that clients with whom they have amarginal relationship would have a lowpropensity to participate. Mitigating thispotential bias was evidence from Chris-tiansen and DeVaney (1998), Sharma andPatterson (1999, 2000), and Sharpe andAnderson (2007) that planners have a ten-dency to overestimate the strength ofclient loyalty, often based on longevity ofrelationship alone. Sharma and Patterson(2000), for example, found that clients willremain with planners long-term even whentheir satisfaction is low when they perceiveswitching costs to be high, alternatives tobe few, or they have not had prior experi-ence with other advisers. It was alsoexpected that a credible promise ofanonymity would allow clients to revealmore nuanced opinions than might other-wise be expected. Finally, to the degreethat any such bias exists across the entiresample, which is the most likely eventual-ity, the relative effects would not be biased.The planner responses allowed each
planner to be assigned a score for each ofthe five proposed strategy-making modes.Firm size was measured by number ofadvisers employed. Client responses allowed each client to
be assigned a score representing theirdegree of trust in their planner and a sepa-rate score for relationship commitment.These constructs were adapted from Chris-tiansen and DeVaney (1998), Sharma andPatterson (1999, 2000), and Sharpe et al(2007). Information related to size offamily, income, industry of employment,number and complexity of employee bene-fits, types of investments, and estatearrangements was collected (a total of 23variables) and used to construct a “clientcomplexity” index (Langrehr, 1991).
Results
Completed questionnaires were collectedfrom 360 planners (a 2.5 percent responserate) and 343 clients. The client responsescould be mapped to 35 planners, a smallerthan ideal sample size, but minimally large
enough for testing purposes. The scores forthe five modes of strategy-making werelargely uncorrelated with each other (cor-relation coefficients ranged from 0.06 to0.35). See Tables 2 and 3 for a summary ofplanner and client scores.The first hypothesis stated that the data-
driven, policy-driven, and relationship-driven modes of strategy-making would bemore strongly associated with trust andcommitment than the planner-driven andclient-driven modes. With trust as thedependent variable, only the data-drivenand policy-driven modes had the predictedlarger coefficients than the planner-drivenand client-driven modes. The policy-drivencoefficient was actually four times the sizeof the next largest (data-driven) and was theonly coefficient that was statistically signifi-cant at the 0.05 level. With commitment asthe dependent variable, the data-, policy-,and relationship-driven modes all produced
the predicted larger coefficients comparedto the planner- or client-driven modes. Yetagain, however, only the coefficient on the
Y E S K E
Will the dollar remain the world’sreserve currency for the foreseeable
future?
Yes, because there are no viable alterna-tives. You can only go so far with gold. Intheory, the best alternatives are the euroand the Japanese yen—but give me a break.They look much worse. As a consequence,the dollar looks good. Plus the UnitedStates is also the one major economy that,come next year, is in a position to have ameaningful discussion about its budgetdeficit in a way that will dominate its polit-ical agenda. That’s what Obama is doingwith the bipartisan fiscal deficit commis-sion, which is going to come out with rec-ommendations right after the elections.Some of them will be politically unfeasible,like probably a value-added tax. But clearly,the only reason the Obama administrationis doing this is because they want thedeficit and the national debt to be on theagenda. I don’t see this discussion happen-ing in Europe, because of a lack of coordi-nation and the huge problems they arehaving internally now. And I don’t see thathappening now in Japan because the DPJparty is very vulnerable and can’t set such apolitically difficult agenda. All of that islikely to make the dollar stronger. Therewill be lots of folks looking to diversifyaway from the dollar, but they won’t havethe option. So the dollar still looks good.
How do you watch for developmentsthat are off the radar screen—and do
you see any countries at risk of blowing up?
One of the reasons our firm has been suc-cessful is that you have a lot of smart econ-omists and strategists working on WallStreet, but you don’t have political scien-tists who focus on the political risks thatreally matter to markets. I’d like to believethat having our kind of research expertisedoes make a difference. It’s not a questionof CIA-style political intelligence, becausein a globalized world, all the data you needis available. The problem is with informa-tion overload—knowing which pieces of
information matter and knowing how toread them. One situation I’m worried about now is
North Korea. They’ve had some difficultinternal situations with currency reform.Earlier this year, they executed theirfinance minister. They apologized to theirpeople for the state of their economy.That’s unheard of in North Korea. Andthen, all of a sudden, a South Korean shipis sunk. The South Korean financial mar-kets haven’t been affected by those eventsyet, but I’m worried about that. Thesekinds of situations don’t make headlinesuntil something sudden and dramatic hap-pens, but this is one that we should be con-cerned about now.
And what are your clients most wor-ried about?
In the near term, they’re most worriedabout Europe, the possibility of European
contagion, and the sustainability of theeuro. In the longer term, they are worriedabout China and U.S.-China relations, andthey worry about whether they’ll be able todo business effectively in China, and therelative incompatibility of the U.S. andChinese business models, given the frictionbetween free-market and state-driven capi-talism. They’re concerned about the ulti-mate economic strength of China andwhether it will be possible for them to dobusiness there. They’re concerned aboutcyber-security, in terms of their exposureto China. And they’re worried about thechanging regulatory and tax environmentin the U.S.
Richard F. Stolz is a financial writer and publishing con-
sultant based in Rockville, Maryland.
www.FPAjournal.org J U L Y 2 0 1 0 | Journal of Financial Planning 19
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www.FPAjournal.org S E P T E M B E R 2 0 1 0 | Journal of Financial Planning 47
Table 3: Client Trust & Commitment Scores
Mean
Trust (maximum 27.4 2.9possible score = 30)
Commitment 35.1 4.1(maximum possible score = 42)
Std-Dev
e = 42)
:3elbaTTa
e = 30)
or scossible(maximum pt ommitmenC
orossible scpust (maximum rT
ossible
esort ScommitmenCust & rTt lienC
v
e = 30)
ed-DtSean
4.135.1
2.927.4 ust (maximum
M
Table 2: Planner Strategy-Mode Scores
Mean
Planner-Driven 11.8 3.6
Data-Driven 12.8 3.8
Policy-Driven 13.9 2.8
Relationship-Driven 17.1 3.5
Client-Driven 8.6 3.3
Std-Dev
n
n
D
n
:2elbaTTa
e
evirD-tneilC
-pihsnoitaleR
evirD-yciloP
evirD-ataD
virD-rennalP
3
8
5
8
esorde ScoMy-egtatrlanner S P
v
6
ed-DtSean
.36.8
.31.71nevirD
.29.31
.38.21
.38.11ne
M
Contributions
policy-driven mode was statistically signifi-cant at the 0.05 level (see Table 4 andFigure 4).The second hypothesis stated that there
would be a positive correlation betweenclient complexity and trust and commit-ment. It was found, however, that trustand commitment were actually inverselyrelated to the complexity of a client’s cir-cumstances. This finding was significant atthe 0.01 level for trust and 0.001 level forcommitment. While this was the oppositeof the hypothesized relationship, it couldbe explained with reference to prior
research. Sharma and Patterson (2000)found that client trust and commitmentwere (indirectly through a “satisfaction”construct) influenced by three factors:perception of attractive alternatives (advis-ers or firms), perception of switchingcosts, and the number of prior advisers.Because the factors that went into thecomplexity score (for example, income,complexity of financial and estate arrange-ments) would tend to be correlated withgreater financial sophistication, it could beargued that the greater the complexity of aclient’s circumstances, the greater the
client’s perception of both attractive alter-natives and low switching costs. Thisinterpretation is consistent with Sharmaand Patterson’s (2000) findings and wouldsuggest that financial planners should con-sider their more sophisticated—and typi-cally largest— clients to be most at risk forchanging advisers.
Results of Factor Analysis
When we performed a factor analysis of theresponses related to mode of strategy-making from all 360 planner respondents,five distinct factors emerged, all with Eigenvalues > 1. While two of the factors corre-sponded to two of our original strategy-making modes—planner-driven and client-driven—the data-driven and policy-drivenmodes merged into a single factor, whichwe will refer to as the “data-policy” factor.The remaining two factors represented thebifurcation of the relationship-driven mode,one factor consisting entirely of statementsrelated to client interaction and the othercomposed entirely of formal tools and tech-niques used in the discovery process. Wewill refer to the latter as the “systematic-relationship” factor (see Figure 5). When we examined these factors in light
of firm size and mode of compensation,several distinct patterns emerged. The data-policy factor and the systematic-relationshipfactor were primarily associated with inde-pendent, fee-only financial planners. Theplanner-driven and relationship-driven fac-tors, meanwhile, were primarily associatedwith advisers working in large financialservices firms, predominantly compensatedon a fee-and-commission basis. Finally, theclient-driven factor was most associatedwith planners working in smaller firmswith mode of compensation evenly dividedbetween fee-only and fee-and-commission.
Review and Summary
The financial planning profession, nowreaching the end of its fourth decade, hasuntil now lacked a framework for organizingand testing the strategy-making activities of
Y E S K E
Table 4: Regression Results for Trust and Commitment as a Function ofStrategy-Mode Scores
Constant R2 F Ratio t-statDependent Variable: Trust
Planner-Driven 0.016 5.278 0.01 0.325 0.57 0.573
Data-Driven 0.02 5.219 0.016 0.526 0.725 0.473
Policy-Driven 0.079* 4.371 0.141 5.401* 2.324* 0.026
Relationship-Driven 0.009 5.312 0.003 0.101 0.318 0.753
Client-Driven –0.001 5.476 0 0.001 –0.23 0.982
Planner-Driven 0.003 4.984 0 0.011 0.107 0.916
Data-Driven 0.018 4.787 0.013 0.439 0.662 0.512
Policy-Driven 0.074* 3.99 0.12 4.490* 2.119* 0.042
Relationship-Driven 0.011 4.823 0.005 0.154 0.393 0.697
Client-Driven –0.02 5.193 0.012 0.388 –0.623 0.538
*p<0.05
Sig. tCoefficient
Dependent Variable: Commitment Constant R2 F Ratio t-stat Sig. tCoefficient
en
en
en
y-M:4elbaTTa
egtatrSession Results fRegr
en
tsurTTr:elbairaVVatnednepeD C
ivrtionship-DelaR
ivry-DolicP
ivrta-DaD
ivrlanner-DP
0.016
0.003
0.141
esorde Scoy-Mommitmenust and CrTTror ession Results f
0.01
2RtonstanCtefficieno
5.312 0.009
4.371 0.079*
5.219 0.02
5.278 0.016
0.473
0.753
0.026
tion ofunct as a Fommitmen
0.573
tt-statioaF R t.igS
0.318 0.101
2.324* 5.401*
0.725 0.526
0.57 0.325
*p<0.05
C
en
en
en
en
en
en
tnemtimmoC:elbairaVVatnednepeD
ivrt-DlienC
ivrtionship-DelaR
ivry-DolicP
ivrta-DaD
ivrlanner-DP
ivrt-DlienC
t
0.013
0.012
0.005
0.12
0
0
efficieno 2RtonstanC
5.193 –0.02
4.823 0.011
3.99 0.074*
4.787 0.018
4.984 0.003
5.476 –0.001
t
0.512
0.538
0.697
0.042
0.916
0.982
.. tigStt-statioaF R
–0.623 0.388
0.393 0.154
2.119* 4.490*
0.662 0.439
0.107 0.011
–0.23 0.001
Figure 4: Coefficients from Regressing Trust and Commitment on Strategy-Mode Scores
–0.04
–0.02
0
0.02
0.04
0.06
0.08
Planner-Driven Data-Driven Policy-Driven Relationship-Driven
Client-Driven
Trust Commitment
48 Journal of Financial Planning | S E P T E M B E R 2 0 1 0 www.FPAjournal.org
Contributions
its practitioners. The present research has,for the first time, offered such an integra-tive framework for organizing the strategy-making activities of financial planners andtested it empirically. Because financialplanning possesses high credence charac-teristics, the issue of how to test any propo-sitions related to different practices hasoften been problematic. A growing body ofresearch, however, has shown that meas-ures related to client trust and commit-ment can be used as a proxy for a host ofmore subtle factors that come into play inthe financial planning engagement. Thesemeasures were used to validate the pro-posed integrative framework. The model/framework itself posits five
distinct modes of strategy-making that fallalong the spectrum of the relative roles ofplanner and client, beginning with theplanner-driven mode in which the plannerdominates the engagement, and endingwith the client-driven mode, in which theclient’s role is dominant. In between thesetwo extremes fall the data-driven, policy-driven, and relationship-driven modes.These three modes correspond to the threethemes found in the financial planning liter-ature: quantitative tools, process-orientation,and interior dimension. In addition to therelative roles dimension, the five modes fallnaturally along a second dimension of plan-ning versus emergence. Prior work relating client trust and com-
mitment to modes of communication,topics of discussion, and perceptions offunctional and technical quality within theplanning relationship (Christiansen andDeVaney, 1998; Sharma and Patterson,1999, 2000; Sharpe and Anderson, 2006)had shown that greater involvement byclients and richer communication betweenclient and planner led to greater trust andcommitment on the part of clients. Thissuggested that the proposed five modes ofstrategy-making would be associated withdistinctly different levels of client trust andcommitment because each represented adifferent level of involvement and commu-nication between clients and planners. Finally, client complexity was proposed
as an additional factor influencing trustand commitment, with greater complexityassumed to be associated with greater plan-ning needs, which in turn would give riseto greater trust and commitment.Taken as a whole, the data are consistent
with the proposed strategy-making modeland its implications for client trust andcommitment. The findings with respect tothe relationship between the policy-drivenmode of strategy-making and client trustand commitment were statistically signifi-cant and consistent with the proposedmodel. The finding of a strong inverse rela-tionship between client complexity andclient trust and commitment was at oddswith the original prediction, but could beshown to be consistent with prior research(Sharma and Patterson, 2000) related toclient satisfaction as a mediator of trustand commitment.The results of the factor
analysis further confirmed keyelements of the proposedtypology, while adding nuanceto our understanding of howthe model must be adjusted toaccount for firm size andmode of compensation.Among other things, the factoranalysis made clear the stronglinkages between the policy- and data-driven modes, which are themselves con-sistent with proposed theories for a policy-based approach to financial planning.In the end, the proposed integrative
framework offers a strong foundationupon which to base future empiricalexaminations of the strategy-making activ-ities of financial planners. It also offers a
new way to think about measuring plan-ner competence in terms of skills in dif-ferent modes of strategy-making, holdingout the possibility for developing assess-ment tools that would aid financial plan-ners in achieving the most appropriatemix of knowledge and technical skills tobest serve their clients.
Implications and Suggestions for FutureResearch
One of the useful tools that might be devel-oped using the proposed framework wouldbe a competency assessment tool for finan-cial planners. Such a tool would allowplanners to determine whether they pos-sessed the right competencies to the rightdegree to be most effective in their workwith clients. The profession’s body of
knowledge could be mapped to each of thestrategy-making modes, especially thethree modes most associated with clienttrust and commitment (data-, policy-, andrelationship-driven). Development of sucha model would be aided by further workvalidating the modes themselves and estab-lishing in a more robust way the relation-ship between each mode and client trust
Y E S K E
Figure 5: Five Significant Factors (Eigen Value >1)
Planner-Driven Data-PolicyRelationship-
DrivenSystematic-Relationship Client-Driven
Large Financial Services Firms/
Fee-and-Commission
Independent Planning Firms/Predominantly
Fee-Only
Large Financial Services Firms/
Fee-and-Commission
Independent Planning Firms/Predominantly
Fee-Only
Independent Planning Firms/
Equally Fee-Only and Fee-and-Commission
Planner-D
erugiF
inancial ge FLar
D
ors (E:5 tact Fanignifice SivF
inancial
Relayolicta-PDaenrivPlanner-D
ge Ft LarndependenI
tionship
alue >1)VValue >1)igen ors (E
Rela-ticemastyS
enrivD-tionshipRela
inancial t ndependenIge F
enrivt-DlienC
t ndependenI
ommissionC-and-eeF
es FvicerSinancial ge FLar
ommission ommissionOnly CeeF
vicerSge FLar
-eeFtly edominanrP
ms/irlanning FPt ndependenI
-and-ms/ ires F
inancial
ommission OnlyE
-eeFtly edominanrP
ms/irlanning FPt ndependenI
-and-eems/ires Fvic
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ommissionC-and-eeand F
Only -eequally FEms/irlanning FP
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www.FPAjournal.org S E P T E M B E R 2 0 1 0 | Journal of Financial Planning 49
“The findings with respect to the
relationship between the policy-driven
mode of strategy-making and client
trust and commitment were
statistically significant …”
Contributions
and commitment. Such an assessment toolwould be able to provide not just a score-card of where a planner stood in terms ofcompetency within each mode, but a pre-scription for how to improve. In the end,the kind of assessment tool proposed couldbecome the standard framework for ensur-ing that practitioners have attained and aremaintaining a minimum level of compe-tence across all modes of strategy-making.In this context, it is worth noting that CFPBoard conducts a job survey of CertifiedFinancial Planner™ (CFP®) practitionersevery five years and uses the results tomodify the topic areas (currently number-ing 96) that must be covered in anyapproved educational program. Thisprocess only captures what planners areactually doing, however, not what theyshould be doing. So, unlike CFP Board’spurely descriptive survey, which captureswhat is, and does not explicitly aim toimprove practice (only to ensure that certi-fication standards are in line with whatpractitioners believe is important), researchfocused on the proposed assessment toolwould have the explicit aim of improvingpractice among financial planners.There are many more testable hypothe-
ses that flow from the proposed modelthan those addressed in this research ornoted in the previous section. Among themare questions related to the most appropri-ate blend of strategy-making skills as afunction of a client’s position in the life-cycle, family composition, job, or other“structural” factors. Also, exploring ques-tions related to how well the model can beapplied across teams of financial plannersmight yield useful insights for ensemblefirms, which are growing in importancewithin the profession. With the CFP standard spreading glob-
ally via the Financial Planning StandardsBoard (FPSB), which licenses 115,000 cer-tificants in 23 territories (not counting the59,000 certificants in the United States),and the promulgation of financial planningstandards by the International StandardsOrganization (ISO), it would be of greatinterest to test the applicability of the pro-
posed framework in other geographicregions. Validation across national bound-aries would have significant implicationsfor the development of the global profes-sion of financial planning.
References
Anthes, William L., and Shelley A. Lee.2001. “Experts Examine Emerging Con-cept of ‘Life Planning.’” Journal of Finan-cial Planning (June).
Anthes, William L., and Shelley A. Lee.2002. “The Financial Psychology of 4Life-Changing Events.” Journal of Finan-cial Planning (May).
Anthes, William L., and Bruce Most. 2000.“Frozen in the Headlights: The Dynam-ics of Women and Money.” Journal ofFinancial Planning (September).
Anthony, Mitch. 2005. Your Clients for Life:The Definitive Guide to Becoming a Suc-cessful Financial Life Planner. 2nd ed.Kaplan Business.
Black Jr., Kenneth, Conrad S. Ciccotello,and Harold D. Skipper Jr. 2002. “Issuesin Comprehensive Financial Planning.”Financial Services Review 11: 1–9.
Boone, Norman, and Linda Lubitz. 1992.“Developing an Investment Policy State-ment for the Qualified Plan.” Journal ofFinancial Planning (April).
Boone, Norman, and Linda Lubitz. 2004.Creating an Investment Policy Statement:Guidelines and Templates. Denver: FPAPress.
Certified Financial Planner Board of Stan-dards Inc., Guide to CFP Certification(1998—2002).
Christiansen, T., and S. A. DeVaney. 1998.“Antecedents of Trust and Commitmentin the Financial Planner-Client Rela-tionship.” Financial Counseling and Plan-ning 9, 2.
Daryanani, Gobind. 2002. “Sensitivity Sim-ulations, a Faster Alternative to MonteCarlo.” Journal of Financial Planning(September).
Diliberto, Roy. 2006. “Uncovering andUnderstanding Your Clients’ History,
Values, and Transitions.” Journal ofFinancial Planning. (December).
Garrett, Sheryl. 2007. Garrett’s Guide toFinancial Planning. 2nd ed. NationalUnderwriter.
Guyton, Jonathan. 2004. “Decision Rulesand Portfolio Management for Retirees:Is ‘Safe’ Initial Withdrawal Rate TooSafe?” Journal of Financial Planning(October).
Guyton, Jonathan, and William Klinger.2006. “Decision Rules and MaximumInitial Withdrawal Rates.” Journal ofFinancial Planning (March).
Hallman, Victor G., and Jerry S. Rosen-bloom. 1987. Personal Financial Plan-ning. 4th ed. New York: McGraw Hill.
Hart, Stuart. 1992. “An Integrative Frame-work for Strategy-Making Processes.”The Academy of Management Review 17, 2(April): 327.
Hart, Stuart, and Catherine Banbury. 1994.“How Strategy-Making Processes CanMake a Difference.” Strategic Manage-ment Journal 15: 251–269.
Hopewell, Lynn. 1997. “Decision MakingUnder Conditions of Uncertainty: AWakeup Call for the Financial PlanningProfession.” Journal of Financial Planning(October).
Kahler, Richard S. 2005. “Financial Inte-gration: Connecting the Client’s Past,Present, and Future.” Journal of FinancialPlanning (May).
Kautt, Glenn. 2002. “The Financial Plan-ner as Decision Maker.” Journal of Finan-cial Planning (October).
Kautt, Glenn. 2003. “Real Options Analy-sis: The Profession’s Next Cutting-EdgeTool.” Journal of Financial Planning(February).
Kautt, Glenn, and Lynn Hopewell. 2000.“Modeling the Future.” Journal of Finan-cial Planning (October).
Kautt, Glenn, and Fred Wieland. 2001.“Modeling the Future: The Full Monte,the Latin Hypercube, and OtherCuriosities.” Journal of Financial Planning(December).
Kinder, George, and Susan Galvan. 2005.“EVOKE: A Life Planning Methodology
50 Journal of Financial Planning | S E P T E M B E R 2 0 1 0 www.FPAjournal.org
Y E S K E
Contributions
for the Coming Revolution in ClientRelationships.” Journal of Financial Plan-ning (April): 46–55.
Lee, Shelley A. 2001. “What is FinancialPlanning, Anyway?” Journal of FinancialPlanning (December).
Lee, Shelley A. 2001. “Why Do FinancialPlans Fail?” Journal of Financial Planning(June).
Mintzberg, Henry. 1979. The Structuring ofOrganizations: A Synthesis of theResearch. Prentice Hall.
Mintzberg, Henry, and James A. Waters.1985. “Of Strategies, Deliberate andEmergent.” Strategic Management Journal.
Mintzberg, Henry, and Frances Westley.1992. “Cycles of OrganizationalChange.” Strategic Management Journal13: 39–59.
Mintzberg, Henry, Bruce Ahlstrand, andJoseph Lampel. 1998. Strategy Safari: AGuided Tour Through the Wilds of Strate-gic Management. Free Press.
Morgan, R. M., and S. D. Hunt. 1994. “TheCommitment Trust Theory of Relation-ship Marketing.” Journal of Marketing58, 3.
Rudd, Andrew. 2006. FPA of San Franciscopresentation.
Sharma, N., and P. G. Patterson. 1999.“The Impact of Communication Effec-tiveness and Service Quality on Rela-tionship Commitment in Consumer,Professional Services.” Journal of ServicesMarketing 13, 2.
Sharma, N., and P. G. Patterson. 2000.“Switching Costs, Alternative Attrac-tiveness, and Experience as Moderatorsof Relationship Commitment in Profes-sional, Consumer Services.” Interna-tional Journal of Service Industry Manage-ment 11, 5.
Sharpe, Deanna, Carol Anderson, AndreaWhite, Susan Galvan, and MartinSiesta. 2007. “Specific Elements ofCommunication that Affect Trust and
Commitment in the Financial PlanningProcess.” Association for FinancialCounseling and Planning Education.
Stearns, Dennis. 2006. “From Doom andGloom to Shangri-La: Scenario Learn-ing Revisited.” Journal of Financial Plan-ning (May).
Thompson Financial Inc. Accounting Today.Oct. 21, 2002.
Wagner, Richard. 2002. “Integral Finance:A Framework for a 21st Century Profes-sion.” Journal of Financial Planning(July).
Warschauer, Thomas. 2002. “The Role ofUniversities in the Development of thePersonal Financial Planning Profession.”Financial Services Review 11: 201–216.
Yeske, David B., and Elissa Buie. 2006.“Policy-Based Financial Planning Pro-vides Touchstone in a Turbulent World.”Journal of Financial Planning (July).
Y E S K E
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