留學(xué)生dissertation網(wǎng)提供留學(xué)生畢業(yè)dissertation，留學(xué)生系統(tǒng)工程項(xiàng)目管理dissertation定制。本文從相關(guān)決策與價(jià)值闡述工程項(xiàng)目管理失敗的各種因素分析。Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 1 of 9
Decision Making, Value Propositioning, and Project Failures- Reality and Responsibility
Rick Dove
Paradigm Shift International
Abstract
This paper outlines reasons for project failures and ties them to value proposition failures. It defines a valueproposition as including both the proposed project deliverable values as well as the implementation processes that willassure value is delivered. It shows that an effective value proposition is not so much about the technology beingproposed as it is about the problem and value perceptions of the Decision Makers who will sponsor a project; and thatit is the project Champion's responsibility to learn the perceptions of decisions makers, and to carefully guide theireducation of problem issues and solution values...continuously. To this end the bulk of this paper presents two models ofhow Decision Makers form perceptions from value propositions. One model represents the psychological behavior ofindividuals as Decision Makers, and the other of group decision making behavior. Both draw from Nobel Prize winningresearch and show how misperception is the general rule, illuminating the issues that the Champion must address.
Introduction
Project failure can be defined under two basic categories:
1. A project that consumes resources but fails to deliver an acceptable ROI
• the project is terminated before completion
o needs cease to exist - the world changed unpredictably
o necessary resources become insufficient or unavailable
o decision makers have a change of heart or are replaced by one's who don't care
• the project was ill defined so resources were inefficiently applied as it developed definition
• the project was incorrectly defined, resulting in user rejection or insufficient value
2. A project that consumes resources but fails to deliver as proposed
• the project exceeds budget
• the project exceeds time
• the project doesn't meet spec
Some may consider the second category as overly harsh, for in many such cases a completed project doesmaterialize and deliver an acceptable ROI. Unfortunately, budgets and schedules that are exceeded impose costlyconsequences in other areas often unassociated with the project. Budget and time are scarce resources for anyorganization. What one project takes in excess resources postpones or cancels another, as a minimum. As a maximum,there is no limit to the damage that a late, overspent, or underperforming project can cause an organization.#p#分頁(yè)標(biāo)題#e#
Failure is in the eye of the beholder. A defense contractor that works for years on a cost-plus project may notconsider it a failure just because the results are never put into service. Consultants that make studies and thenrecommendations may not consider it a failure just because the advice is ignored. An ERP provider that licensessoftware may not consider it a failure just because expected benefits do not materialize on time and on budget. After all,these activities did generate a successful income stream for the supplier. We will not dwell on these situations, otherthan to recognize that there are those who will redefine failure by ignoring responsibility.
We do recognize that some projects are knowingly speculative, with their outcomes unsure. Here the ROI has astrong component of learning and/or contingency. Whether they delivery results that are putinto service or not, weconsider them valuable.
On the surface, projects fail for a variety of reasons. In reality, all but the first in category one can be traced to baddecision making. In general, most bad decisions can be traced to a failure of value propositioning. Value propositioningis an interaction between Decision Maker and Project Champion. The Champion wields a value proposition incompetition for approval, much like the Knight wields a sword defending a Lady's honor. In the Knight's competition,Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 2 of 9the quality of the sword and the quality of the competitor are two independent factors. So it is with the Champion'scompetition.
The thing a Champion must accomplish is to win approval from those who control organizational priorities andstrategy, those who commit funds and resources. This may mean an engineering project manager winning approval foran internal development project, an account manager seeking selection as an external supplier of products or services, ora business manager seeking budget, capital, or strategy approval. In all cases the process is fundamentally the same.
They are all successful only to the extent that they can be effective Champions of the projects and services they want
Decision Makers to value and select.
Where technology projects are concerned, there is too often no acceptance of responsibility for crafting effectivevalue propositions. In some cases there seems instead a belief that technology stands naked for all to see and evaluate,needing only a guided tour of features and obvious benefits; and that an inappropriate evaluation is a fault of the
evaluator and not of the Champion. In other cases, there seems instead a belief that simply meeting an RFQ'srequirements is sufficient, even though they be inadequate or incomplete.
I will show that an effective value proposition is not so much about the technology being proposed, as it is aboutthe problem and value perceptions of the decision makers who will choose a solution; and that it is the Champion'sresponsibility to learn the perceptions of decisions makers, and to carefully guide their education of problem issues and#p#分頁(yè)標(biāo)題#e#
solution values...continuously.
Classic theory models decision making in optimal terms, maximizing utility with perfect information, objectiveevaluation, and computational omnipotence. In reality decisions are made by mere mortals, who are computationallychallenged, confused by technology and ROI, and strongly influenced by personal interests, biased perceptions, andlimited attention. We will review how decision makers in http://www.400190.com/dissertation_writing/Engineering/organizations actually make decisions, as opposed to howthey ought to, or how we wish they would.
To this end the bulk of this paper presents two models of how Decision Makers form perceptions from valuepropositions. One model represents the psychological behavior of individuals as Decision Makers, and the other ofgroup decision making behavior. Both show how misperception is the general rule, and illuminate the issues that thewould-be effective Champion must address.
A word about the graphic models that are presented later is in order. Decision making behavior models aresummarized with a graphic called a concept map. This is a particularly useful and clear representation of knowledge thatJoseph Novak (see references section) developed and trademarked. Concept maps visually summarizes the central ideas
and their relationships in each section. They have a surprising ability to clarify the densest information-packed text, and
to show in one illustration what takes many pages to explain in words. They don't usually convey full meaning,
however, until after the text is first read, as they are somewhat like an outline. Concept maps follow simple rules: theyare hierarchical, in that concepts lower in the diagram are refinements of concepts higher in the diagram; relationshipsare directed downward along connecting lines, as befits a hierarchy, unless an arrowhead is present to show differently;and one should be able to clearly read a meaningful thought when traversing connected concepts.
Value Propositioning
Value propositioning happens in all conversations that attempt to obtain a favorable decision among alternatives.Sometimes it is done by the Decision Champion who seeks the decision. Sometimes it is done by the Decision Makerwho seeks an understanding. Regardless of whether one or both do it, three factors get in the way: human, decisionmaking,behavior. Decisions are always made in favor of the choice with the best value...as perceived by the DecisionMaker. Perception is everything; but perceptions are formed independent of truth, accuracy, and the best intentions ofall parties.
The process of value propositioning by a project Champion cannot begin until a problem is perceived by a DecisionMaker, and does not result in approval until that Decision Maker perceives a sufficiently superior value to direct achoice. Thus, we see that the value propositioning process is enabled by the Decision Maker.
The Champion has only one channel for influence, and that is the value proposition. The Champion constructs thevalue proposition using skills applied to knowledge. This knowledge is the Champion's personal interpretation ofinformation about the problem, the Decision Maker's context, the competition, and the solution being championed; and,most importantly, personal imagination of how information and competitive value propositioning is affecting theevolution of Decision Maker perceptions.#p#分頁(yè)標(biāo)題#e#
The Decision Maker's initial perceptions are personal interpretations of the problem and the decision makingcontext. The process of value propositioning then adds perceptions of values, risk, and trust associated with perceptionsof solution candidates, and augments the initial perception of the problem. All of this occurs as the Decision Makerinterprets the value propositions offered by each of the competitors.Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 3 of 9
From this it is clear that a Champion's value proposition does not speak for itself, anymore than the Champion'ssolution speaks for itself. The Champion's solution, as perceived by the Decision Maker, is an interpretation of aninterpretation, both constrained and filtered sequentially by the knowledge and ability of the interpreter. A valueproposition does not speak for itself either, because the perceptions it hopes to cause evolve continuously as competitivevalue propositions cause new interpretations.
Value propositioning is not a discrete event, but rather a dynamic process that is anticipated and managed by the
effective Champion, and must continue even after a favorable decision is obtained.
Individual Behavior in Decision Making
Gaining a favorable decision requires an interaction with Decision Makers that results in them having a favorableset of perceptions. This is a direct result of the Decision Maker's interpretation of the value proposition. The valueproposition is a communication. As a communication, it is subject to miscommunication, possibly due to poorcommunication on the Champion's part, and definitely due to inherent human nature that filters and biases theperceptions obtained from the communication.
Later we will explore the behavior of groups as Decisions Makers. Now we look at the behavior of individuals as
Decision Makers. These are not independent perspectives, however, as individuals in groups bring their decision
making behavior with them.
How individuals make choices when offered alternatives has been shown to differ considerably from objective,optimal reasoning. Theories attempting to model what really happens abound, but one stands above all others inacceptance, principally for its coherence and its ability to predict actual behavior. Prospect Theory, as it is known, wasdeveloped by Daniel Kahneman, who shared the 2002 Nobel prize in economics for his effort.
This discussion of individual decision making is my adaptation of Kahneman's work, principally based on theresearch he and Amos Tversky report on in their impressive collection of papers published as Choices, Values, and
Frames [1].
Value propositions generally attempt to show multiple benefits, each stemming from some feature inherent in thesolution, and each promising to deliver some desirable value. Decision Makers, especially experienced ones, perceivevalue propositions as legitimate attempts on the part of a Champion to persuade, and so they hear each promised benefitwith a bit of healthy skepticism. Subjectively they associate with each claimed benefit some uncertainty, or probability,of the likelihood that it will deliver as promised. Not because they disbelieve the Champion, but rather because they#p#分頁(yè)標(biāo)題#e#
know from experience that honest claims assume ideal conditions of implementation, transfer, and acceptance. Suchconditions are rarely itemized, and are unlikely to exist in any event. This historical record results in a Decision Makerassessing each claim with some subjective probability of likelihood.
The discussion will now explore ten behavioral results that stem from five psychological mechanisms whichinfluence how Decision Makers arrive at valuation. Four of these behavioral results are associated with the weighting ofprobabilities, where the Decision Maker deviates plus or minus from some neutral assumption of the probability that aclaim will be realized.
Valuation is knowledge dependant. A Decision Maker knowledgeable in the area of a benefit claim is likely tooverweight the probability that it can deliver as promised, assuming that the knowledge is in agreement with the claim.
Conversely, when little or no knowledge is present, the claim is likely to be underweighted.
Valuation is simplified. Various kinds of simplification are actively employed to reduce the complexity ofevaluation and decision making. One standard procedure is to eliminate any claims deemed insignificant from further
consideration. A claim may be deemed insignificant because its ability to deliver is considered highly unlikely; perhapsbecause it appears culturally or politically incompatible. A claim may also be considered insignificant because it simplyis not appreciated as something to be desired; often for good reason, but sometimes due to an insufficient understanding.
Another typical simplification is the chunking of probabilities. A subjective assumption of the probability that a claimwill deliver is unlikely to be fine grained. It is more likely that round numbers like 90% or 75% or 50% would be theassumption than 87.2%, for instance.
留學(xué)生dissertation網(wǎng)提供留學(xué)生畢業(yè)dissertationValuation is relative. The status quo typically establishes the neutral point for measuring value. Thus, a costreductionbenefit is generally valued for the amount saved, independent of the total amount of cost, unless the amount isdismissed as insignificant. Likewise, new capability, increased productivity, faster response, better quality, and othersuch benefits are measured relative to a reference point.
The reference point is not, however, always the status quo, nor always a fixed point throughout a decision makingprocess. Sometimes the reference point is based on expectations, hopes, or what is believed possible. A Decision Makerseeking a specific performance objective will not value something that gets halfway there, even though it is twice asgood as the status quo provides. Decision Makers seeking a reduction in some undesired quality, such as security risk,Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 4 of 9#p#分頁(yè)標(biāo)題#e#
will recognize relative value for any solution that accomplishes that, until they learn it is possible to eliminate the riskcompletely.
Typically a candidate solution is measured against multiple objectives, and the valuation for each is rolled up into arepresentative total Value. Frequently a solution cannot offer positive gains on all objectives. One solution may offergains in ease of use and speed of response, but with a loss of a familiar but marginally necessary capability present inthe status quo. Another may offer twice the performance of the reference point but cost twice as much as well. Thesevaluation measurements are all viewed as gains and losses relative to the reference point.
Decision Makers are not, strictly by nature, either risk averse or risk seeking, as is often believed, but changebehavior depending upon the options that face them. For example: A company that has decided to choose an integrated
ERP system to replace a collection of poorly integrated independent applications is likely to find that it must give upsome previously valued functionality. Quite possibly all candidate solutions will be unable to meet some specific
capability satisfactorily. Under these circumstances Decision Makers are more likely to consider otherwise marginalsolutions that will provide the desired capability, even though there may be some higher risk associated with such achoice. This is the case where a high probability of loss creates a tendency for risk seeking behavior. Risk seekingbehavior also surfaces when the situation shows low probability of gains, as when all solution candidates for an ERPsystem agree to develop custom code for a missing desired feature, but all have a track record for failing to delivercustom code on time. Risky solutions are also more acceptable when a problem has terminal implications, such asoperating costs that will guarantee bankruptcy or product costs that spell market loss.
Conversely, risk averse behavior is exhibited when a low probability loss is perceived, such as when an engineeringproject cannot guarantee that it will meet some specific performance mark, but the likelihood of missing it is fairly low.
Under these conditions Decision Makers are not going to take a risk on some otherwise wild alternative just because itlooks solid on that one desire. Risk averse behavior is also seen with high probability gains, as in why take a risk if itlooks pretty safe that desires will be met by going down the safer path?
Valuation is formulation dependant. Describing the same claim in different words and concepts can change theperception of loss or gain. Decision research shows that couching loss-mitigating expenses as insurance can turn a loss
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Probability is the subjective likelihood, assumed by a Decision Maker, that a proposed benefit will deliver as promised.
Relationship flow is downwardunless arrowhead present.
Core concepts of individual decision making behavior.
Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 5 of 9perception into a gain perception. That there are differing perceptions of loss and gain is evident when a valueproposition features the elimination of jobs, which may be viewed by some Decision Makers as a gain and by others asa loss. Formulation effects are also evident in the order of presentation. Decision research shows the when conceptswhich establish a certain perspective are presented in series, one or a few that follow a strong one can ride theestablished psychological context.
Valuation is non-linear. Initial increments of gain are valued higher than subsequent increments. People value the
addition of $100 to a wallet with $100 already in it more so than the addition of $100 to a wallet already containing
$1000. We value a 100% gain more than we value a 10% gain, even though the increment is identical, and generally we
will pay more for the one than the other. Losses reflect the same diminishing return shape. Loosing $100 from a $$1000
wallet is not felt nearly as badly as loosing $100 from a $200 wallet. This diminishing of value results in undervaluing
incremental increases of gain. Reducing an uncertainty or risk from 10% to zero is a lot more valuable than reducing it#p#分頁(yè)標(biāo)題#e#
from 25% to 15%. People value the elimination of uncertainty over simply reducing it, even when the amounts are
equal. This is called the certainty effect, which appears to have an even stronger push from underlying psychology than
just from the diminishing returns of the loss-value function.
Diminishing losses are not symmetric with diminishing gains. "Losses loom larger than gains", the decision
researchers affirm for us. One implication of this important distinction is that a gain and loss of equal value are not
perceived as offsetting. Unless under mandate to reduce headcount, losing 12 people because technology can save their
salaries is not typically considered an even deal by many real Decision Makers, in my observation. Another implication:
Things we own appear to have higher value than we are willing to pay to re-acquire them. This is called the endowment
effect, and its classic example is the person unwilling to part with a special bottle of fine wine when offered $200 for it,
but equally unwilling to buy the same bottle for $100. This faster decline of loss value, as compared to increase of gain
value, accounts for the generally observed loss averse behavior people exhibit.
Group Behavior in Decision Making
Herb Simon was awarded a Nobel prize in Economic Sciences in 1978 for his work that founded the field of
behavioral economics. His concepts of "bounded rationality" broke from the classical notion that business decisions are
made under optimal conditions and strive for optimal results. These concepts are described in his book Administrative
Behavior [2], which the Nobel committee called epoch-making, and form the basis for both Kahneman and Tversky's'
work on individual decision-making behavior just discussed, and for the "important work", according to Simon, of
Richard Cyert and James March, published as A Behavioral Theory of the Firm [3].
Cyert and March offer that "...the firm is, in fact, a coalition of participants with disparate demands, changing foci
of attention, and limited ability to attend to all organizational problems simultaneously." They note that coalitions have
inherent conflicts which remain unresolved, power politics and positions that often exert disproportionate influence,
goals that might be ambiguously stated purposely to restrict knowledge of true intent, and other group-induced behavior
that force departure from optimized, objective decision making. A coalition is of course a group of individuals, each of
which brings to the party the misperception mechanisms and biased individual behaviors already discussed.
Three processes are of interest: objective setting, perception creation, and choice. In all three the nature of the
problem perception plays an important foundation role. Before looking at these three processes, we will review six
embedded concepts that deserve separate note: candidate solution search, organizational slack, acceptable level rules,#p#分頁(yè)標(biāo)題#e#
unresolved conflict, attention focus, and "satisficing". The behavioral model presented here is my adaptation of Simon's,
and Cyert and March's work to the subject of value propositioning.
Satisficing, in Simon's words, is the essence of what he calls bounded rationality: "Administrative theory is
peculiarly the theory of intended and bounded rationality - the behavior of human beings who satisfice because they
have not the wits to maximize." Under ideal conditions in an ideal world Decision Makers are supposed to find and
examine all possible solutions, maximizing the value obtained by selecting the best from among all those available. In
reality, where time and attention are scarce resources, and complexity rules, the Decision Maker "...looks for a course of
action that is satisfactory, or 'good enough'....Because administrators satisfice rather than maximize, they can choose
without first examining all possible alternatives and without ascertaining that these are in fact all the alternatives.
Because they treat the world as rather empty and ignore the interrelatedness of all things (so stupefying to thought and
action), they can make their decisions with relatively simple rules of thumb that do not make impossible demands upon
their capacity for thought. Simplification may lead to error, but there is no realistic alternative in the face of the limits
on human knowledge and reasoning."
Attention focus is limited for Decision Makers. Generally all have other ongoing duties with daily deadlines and
surprises which compete for attention. On top of this is the shear complexity and impossibility of trying to anticipate all
of the unintended consequences that will ensue from any decision. When limited available attention is directed at the
Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 6 of 9
decision making process, it is focused where personal urgency is felt. This gives priority to a manageable subset of
issues.
Unresolved conflict is a natural artifact of modern organizations. The separation of responsibilities and objectives in
a hierarchical structure pits different sub-groups in competition for resources and strategic focus. Conflict is mitigated in
coalitions through a variety of means, some natural and some imposed. Natural means are principally the result of
limited attention focus. Some participants have immediate interests so sharp that longer term conflicts are ignored or
unseen. Imposed means have two forms of interest to us. First, objectives that may conflict across functions are
prioritized in sequence. For instance, a production objective may require satisfaction before a marketing objective is
given priority, or even considered in the evaluation process. Second, the organization requires that decisions made by
the coalition observe acceptable level rules, discussed next.#p#分頁(yè)標(biāo)題#e#
Acceptable level rules, Cyert and March tell us, circumvent conflicts that would otherwise deadlock a coalition or
disenfranchise some participants. Basically they "...require that local decisions satisfying local demands made by a
series of independent decision centers result in a joint solution that satisfies all demands." They observe that one impact
of this rule is the lowest common denominator effect. Satisfying all demands is possible, as they note that if no solution
alternative can accomplish this, then either the coalition will find some more candidates to consider, or they will relax or
eliminate demands to find a common acceptable level for all participants.
Organizational slack refers to the operating efficiency, or leanness, of an organization at a specific point in time.
When times are bad and downsizing has run its course, for instance, slack is at a minimum or non-existent. Under these
conditions decision mistakes that waste time or squander resources can be very costly, perhaps unrecoverable. Decision
Makers are very wary and highly risk averse, and more inclined to search harder for strong solutions. In good times
when cash is not a scarce resource, when general market growth is strong, or when competitive advantage enjoys strong
market acceptance, organizational slack increases. Under these conditions risks with interesting reward potential can be
viewed favorably, and satisficing is quicker to settle for acceptable solutions.
Search is the activity that identifies and selects candidate solutions for consideration. Satisficing behavior tends to
limit search activity initially to a small number of candidates. Search is influenced by three factors: the current amount
of organizational slack, who is in charge of the search, and, importantly, a tendency to look for candidates that are
similar in nature to the existing unsatisfactory solution or to the perception of the problem. Thus, when an existing
product becomes inadequate for the market, a company will tend to look purposely for projects that promise a superior
featured version rather than something completely different that would obsolete the product concept. There is an
inclination to stay inside the box unless adequate solutions cannot be found. Unless, of course, the person in charge of
the search process is an out-of-box thinker by nature, or for some other reason feels a more radical approach has
compelling value. In any event, the person or sub-group in charge of the search has a dominant influence on which
candidates will be considered. The final influence is organizational slack. When high, there are excess resources
available to spend more time looking for more candidates. Satisficing will often counter this effect. Since high slack
reduces the pressure to find an optimal fit, search may end when the first candidate is found that appears to meet all of
the objectives.#p#分頁(yè)標(biāo)題#e#
The objective setting process typically begins in advance of solution search activity. It is not an isolated event in
sequence, however, and evolves as perception creation evolves, and as membership in the coalition changes. Objective
setting, in the sense of what must be addressed by a solution, has two parts: identifying the nature of individual
objectives and establishing the performance level for each.
The list of objectives is principally influenced by two factors: the Decision Makers in the coalition, and their
individual objectives. Individual coalition members exert personal preference in setting objectives. If coalition
membership changes before a final choice is made, it is quite possible that objectives can change as well.
The performance targets set for each goal are influenced principally by three things: past objectives, performance
attained on those past objectives, and performance attained by other organizations on similar objectives. The roots of
performance targets are sunk in the organizational learning that occurs from prior shared experience and observation,
and is often unspoken context that the skilled Champion will seek.
Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 7 of 9
The perception creation process, as seen previously, is an interpretation of value propositions. These value
propositions are related to a specific pool of solution candidates generated from the search activity discussed above, and
are influenced by five sources of bias worth noting: prior training-and-experience, unresolved conflict, attention focus,
decision psychology, and simple patterns. We've discussed the nature and effects of attention focus and unresolved
conflict above. Decision psychology was the subject of individual decision making behavior discussed previously. That
leaves simple patterns and training-and-experience remaining for discussion.
Simple patterns for developing valuation are the general rule, for two reasons. Firstly, accurate ROI comparisons
are difficult to compute and subject to disagreement, so simply being affordable and clearly addressing the problem
with improvement appear to be stronger influences. Secondly, though some argue that all things can be translated into
costs, accomplishing this for all criteria is awkward and subject to disagreement, so settling on a small number (six plus
or minus) of mainly independent objectives is frequently observed.
Training and experience, of course, form the initial knowledge base that any Decision Maker starts with.
Perceptions build upon this foundation only when new information is closely related to what is already known,
facilitating incremental knowledge growth. Someone from finance participating in a decision for a CRM (Customer
Relationship Management) system, for instance, is likely to understand a sales-cost analysis much more readily than the#p#分頁(yè)標(biāo)題#e#
features that improve personal interactions between customer and salesperson.
The choice process is the group's mechanism for selecting the final choice among alternatives. Typically this
follows rules standardized by the organization. These standard rules determine how candidates are scored against
objectives addressing the problem perception. They are based on the organization's past experience in scoring decision
alternatives, and consequently often reflect the organizational slack in the past when the rules were established. If they
were established when slack was high, they are likely to be less risk sensitive than otherwise. If not, uncertainty may
play a dominant role. In any event, organizational choice prefers to avoid uncertainty rather then carry it into the scoring
process, when possible.
Uncertainty is avoided either by negotiating predictability with the winner, or by recasting the objectives for a
shorter term solution that has sufficient predictability. If the decision choice involves an outside party, such as a product
vendor, predictability is typically obtained with contract terms that guarantee results or extract a compensating penalty.
based on
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Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 8 of 9
If the decision involves inside projects, other funded projects may be required to compensate, if necessary. Where#p#分頁(yè)標(biāo)題#e#
uncertainty is caused by an inability to see far enough into the future, objectives will likely be scaled back to fit within a
shorter period of time.
Choice requires that the unresolved conflict inherent to decision-making groups be mitigated. As we saw earlier,
this can also modify objectives, where compromise is made until all Decision Makers find acceptable common ground.
Of course in any such group there are politics at work, and there are some Decision Makers with more say than others,
and some who dominantly influence others.
Through it all, satisficing reigns. The group will search for an acceptable solution and be happy to make a decision
once one is found. Faced with multiple acceptable solutions, the best among them will be desired, but not necessarily
discovered. Instead, simplification will be employed to make the decision process manageable. In a strong satisficing
situation, the order that candidates are considered will have a major effect on outcome, for the first one that meets
acceptable criteria is quite likely to trigger a decision and end the process.
Conclusion
On the surface this paper speaks directly to Decision Champions, as opposed to Decision Makers. A Decision
Champion is that person seeking a favorable decision, and therefore responsible for making an effective value
proposition. I cast the Champion as the active party and the Decision Maker as the passive party. Not because this
always is, or should be, the case; but rather that the Champion is typically in competition to show better value than all
other acceptable alternatives. I am tempted to say that the Champion therefore has more to lose if value is not perceived
in its best light. But of course this is not true - all parties have a lot to lose.
Nevertheless, the effective Champion must address and influence the perceptions of all Decision Makers, from the
time of proposal through to final project completion. Decision Makers forget why they made a decision, new Decision
Makers enter the process and old ones leave, new developments and priorities dominate thought and cloud old
decisions, and sometimes a dominant Decision Maker receives initial acquiescence from others who simply wait for his
departure.
A complete value proposition addresses delivered value, not potential or wishful value. As such, it addresses both
the project deliverables as well as the processes and commitments that assure delivery, and continues as an ongoing
activity until the project is completed.
Projects fail because value propositions are incomplete, incorrect, miscommunicated, misperceived, misdirected, or
become obsolete. With the exception of the later, the former are all the responsibility of the Champion, and rely
principally on skills of learning and educating, exercised with diligence and persistence.
Learning skills are required to understand completeness and correctness as entry level knowledge necessary to play#p#分頁(yè)標(biāo)題#e#
the role of effective Champion. Continuous learning in real-time, throughout the entire process of value propositioning,
is necessary to sense a Decision Maker's perception evolution, and to sense the entry of new Decision Makers during the
process.
Education skills are required to avoid miscommunication, correct misperception, and effectively develop correct
perception. Learning theory has much to say about effective means for incrementally developing perception at both ends
of the educating-learning vector, but a complete discussion is beyond the scope of this paper. The interested reader is
directed to the work of Daniel Ausubel [4,5] and Joseph Novak [6,7], and to my book [8] that places all of this in the
context of value propositioning.
Rote learning is something most of us are familiar with from early schooling, when we memorized multiplication
tables, dates of historical events, or poetry of no personal interest. Unless one is gifted with a photographic memory, this
type of learning generally relies on dull repetition. In contrast, what Ausubel calls meaningful learning, relies on
associating some new piece of knowledge with something already known. The closer the association too what is already
known, the more effective the learning. It is this association that provides meaningful linkage between new knowledge
and prior knowledge.
Ausubel notes: "If I had to reduce all of educational psychology to just one principle, I would say this: The most
important single factor influencing learning is what the learner already knows. Ascertain this and teach him
accordingly." In addition to closely related prior knowledge, he also believes two other factors are necessary for
meaningful learning: the learner must believe that learning the material will provide some value, and the learner must
want to learn the material. These three conditions are not automatically present when a Champion addresses a Decision
Maker. From my experience, one or all of these necessary conditions is missing far more often than not. If that means
the Champion must rely on rote learning to have the many points of the value proposition remembered at valuation
time, repetition repetition repetition would seem in order. Unfortunately this is not an option, as rote learning in this
case is not a substitute for meaningful learning. Though the Decision Maker may well remember the irritating insistence
Proceedings of International Council On Systems Engineering (INCOSE) 2004 Region II Conference, Sep 2004 Page 9 of 9
of certain claims, if these claims are not tied into related prior personal knowledge they float unsupported with no basis
for belief.
To explain the mechanisms of learning Ausubel relies on a cognitive model of how knowledge is structured
internally in our minds. It is suggested that our ability to know things arises from an ability to represent concepts in#p#分頁(yè)標(biāo)題#e#
neural structures, and to relate these concepts to each other in some meaningful association. For instance, at an early age
we develop a concept of living things and another for non-living things. At some point we develop a concept for pets,
like the family dog and cat, which is different than the concept we have for people. But we associate both people and
pets to the concept of living things rather than to the concept of non-living things. The first association we develop
between living things and people may be simply that they interact with us, whereas the non-living play toy in the crib
does not. This association and the two concepts it connects is meaningful because it can be acted upon. Either concept
may exist without any association to another, but they are meaningless in isolation. As life progresses we develop large
structures of concepts and associations that model the world as we know it. Assimilating new knowledge occurs when a
new concept is associated with some concept we already possess, such as the concept of a crying noise associated with
people as attention-getting. New knowledge also develops when new associations are made between existing concepts,
such as additional variations on attention-getting, like hunger is alleviated by people when a crying noise is made.
Hunger is likely one of the many initial hard wired concepts that form the seed foundation for all subsequent
associations to new concepts.
Novak has made this concept-association model of knowledge explicit, with an external visual representation he
calls concept maps, a term he has trade marked. His purpose was to provide a tool that can help people skillfully
improve the learning process, either in others when they engage in teaching, or in themselves when they engage in
learning. Both are pivotal skills for the effective Champion.
Two concept maps have been used in this paper to visually summarize the central ideas. Partly this is done because
it is known that many people are better as visual learners then as verbal or textual learners; partly because otherwise
dense textual information becomes transparent in graphic form; partly because it is a succinct way to summarize the key
points; and partly, hopefully, because their usefulness as tools for both learning and educating has been self-discovered
and appreciated.
References
1 Daniel Kahneman and Amos Tversky (Editors), Choices, Values, and Frames, Cambridge University Press, 2000.
2 Herbert Simon, Administrative Behavior, Free Press; 4th edition, 1997.
3 Richard Cyert and James March, A Behavioral Theory of the Firm, Blackwell Publishers, 1992.
4 David Ausubel, The Psychology of Meaningful Verbal Learning, Grune & Stratton, 1963.
5 David Ausubel, Educational Psychology, A Cognitive View, International Thomson Publishing,1968
6 Joseph Novak and D. Bob Gowan, Learning How To Learn, Cambridge University Press, 1984.#p#分頁(yè)標(biāo)題#e#
7 Joseph Novak, Learning, Creating, and Using Knowledge: Concept Maps As Facilitative Tools in Schools and Corporations,
Lawrence Erlbaum Associates, 1998.
8 Rick Dove, Value Propositioning - Perception and Misperception in Decision Making, Iceni Books, 2005, see
www/parshift.com/ValueProp for overview.
留學(xué)生dissertation網(wǎng)提供留學(xué)生畢業(yè)dissertationAuthor Bio
Rick Dove is a recognized thought leader and change agent for agile enterprise and agile systems of all kinds. He coled
the seminal effort that defined agility in the early nineties as the survival need of the new millennium. He
subsequently organized and led the Agility Forum's industry-collaborative work that identified and defined concepts
and principles for achieving agility in all aspects of enterprise. He's developed and managed deployment of agile
enterprise business processes and IT infrastructure. He is a prolific writer and frequent speaker on the subject, and the
author of Response Ability: The Language, Structure, and Culture of The Agile Enterprise (Wiley 2001) and Value
Propositioning - Perception and Misperception in Decision Making (Iceni Books 2005).