Expert Choice Solutions combine collaborative team tools and proven mathematical techniques to enables your team obtain the best decision in reaching a goal. The Expert Choice process lets you:. structure complexity,. measure the importance of competing objectives and alternatives, and. synthesize information, expertise, and judgments.
conduct what-if and sensitivity analyses. clearly communicate to share results, and iterate parts of the decision process when necessary. allocate resources (if desired) Upon completion of an Expert Choice evaluation, you and your colleagues will have a thorough, rational, and understandable decision that is intuitively appealing and that can be communicated and justified. A simple AHP Hierarchy This might take the form of (a) choosing an alternative course of action, or (b) allocating resources to a combination (portfolio) of alternatives. The process is iterative and not necessarily one pass through a fixed number of steps.
The process involves combining logic and intuition with data and judgment based on knowledge and experience. Structuring is the first step in both making a choice of the 'best' (or most preferred) alternative as well as in optimally allocating resources to a combination of alternatives. (Animation will show JUST GREEN BOXES, mimicking the visual brainstorming process, then organizing them into goals, objectives & alternatives). Structuring involves identifying alternative courses of action, identifying objectives (sometimes called criteria) into a hierarchy, determining which objectives each of the alternatives contribute to, and identifying participants and their roles (based on governance considerations where appropriate). After structuring a hierarchy of objectives and identifying alternatives, priorities are derived for relative importance of the objectives as well as the relative preference of the alternatives with respect to the objectives. Originally, all measurement with AHP was performed by pairwise relative comparisons of the elements in each cluster of the hierarchy, taken two elements at a time.
For example, if a cluster of objectives consisted of Cost, Performance, Reliability, and Maintenance, judgments would be elicited for the relative importance of each possible pair: Cost vs. Performance, Cost vs. Reliability, Cost vs. Maintenance, Performance vs. Reliability, Performance vs.
Maintenance and Reliability vs. While pairwise relative comparisons are used in AHP and Expert Choice to derive the priorities of the objectives in the objectives hierarchy,AHP and Expert Choice were subsequently modified to incorporate absolute as well as relative measurement for deriving priorities of the alternatives with respect to the objectives. All measures derived with Expert Choice possess the ratio scale levels of measure. If priorities do not possess the ratio level property, as often occurs with other decision methodologies, such as weights and scores in a spreadsheet, the results are likely to be mathematically meaningless. Measurement can be performed by making pairwise relative comparisons, or by using absolute rating scales. Expert Choice allows for subjective as well as objective measurement.
Expert Choice V11 Executions
This capability makes it somewhat unique in that most mathematical models don't allow for human judgment to the extent possible with AHP and Expert Choice. Furthermore, all measures derived with Expert Choice are 'ratio level measures', an important property that avoids computations that lead to mathematically meaningless results. A synthesis (combining) of the measures according to the objectives hierarchy follows the structuring and measurement steps. This is done automatically by Expert Choice. This synthesis is quite unique (as far as models go) since it includes both objective information (based on whatever hard data is available) as well as subjectivity in the form of knowledge, experience, and judgment of the participants. The synthesis results include priorities for the competing objectives as well as overall priorities for the alternatives.
Because of the structuring and measurement methods used by Expert Choice, the results are mathematically sound, unlike many traditional approaches such as using spreadsheets to rate alternatives. But having mathematically sound results is not enough. The results must be intuitively appealing as well. The synthesis workflow step provides tools (such as sensitivity analysis and consensus measures) to allow you and your colleagues to examine the results from numerous perspectives.
Using these tools, you can ask and answer questions such as 'What might be wrong with this conclusion?' Why is Alternative Y not more preferable than Alternative X? If we were to increase the priority of the financial objective, why does Alternative Z become more preferable? Why might others in the organization feel that Alternative W should have a higher priority than alternative X? The answers to one or more of these questions might signal the need for iteration. If for example, you feel that Alternative Y might be more preferable than Alternative X because of its style, and style is not one of the objectives in the model, iteration is necessary.
If style is already in the model, does increasing the importance of style shift the priorities such that Alternative Y becomes more preferable than alternative X? If not, then perhaps the judgments were entered incorrectly, and iteration to re-examine the judgments is called for. If style is already in the model and the judgments are reasonable, how much would the importance of style have to be changed before the decision were reversed? If it is just a little bit, then you might reconvene those whose role it was to prioritize style and ask that they discuss their judgments and feel that they are reasonable.
Comparion Resource Aligner helps you if you are deciding on a combination of actions to take, such as a portfolio of capital investments or projects, then the allocation step is a powerful way to determine an optimal combination of actions or investments subject to constraints such as budget, personnel, space, materials, coverage, balance, and dependencies. Using Expert Choice Comparion Resource Aligner you will be able to enter additional information pertaining to costs, risks, funding pools, dependencies and other constraints that will enable you to determine an optimal combination of alternatives under different scenarios. The following information is an overview of the resource allocation process as it is typically applied in applications such as project portfolio management. We won't discuss details of the Resource Aligner application here but will give an overview instead. The figure above shows the optimum combination of projects given a budget of $11 million.
Projects in yellow are in the optimal portfolio. This is typically only the first 'iteration' for an optimum portfolio. Subsequent iterations will evolve as decision makers discuss dependencies, balance and coverage, musts and must nots, and other resource constraints such as specific type of personnel, building space, etc.
The Benefits column shows the relative benefits of each of the alternatives (often projects in a project portfolio application) that were derived in Expert Choice Comparion. Costs are typically dollar costs, but can be any constraint (such as Full Time Equivalents - FTE's) that places a limitation on selecting all of the alternatives. You can specify many different constraints from the Resource Aligner tab in addition to the 'Cost' constraint on the data grid tab. The 'Cost' constraint, however, has a special function in that it can be used to generate a 'Pareto' curve that shows different optimum portfolios (combinations of alternatives) at different maximum cost values.
Project risks (one of the ) can be entered directly into the risk column. The risks should be estimates of the relative risk of the alternatives or projects.
If you need to derive such estimates, you can create and evaluate an 'associated' risk model using the Risks pull down menu: You can set up 'Strategic Buckets' by designating categories for the alternatives/projects. Typical categories might include type of project, business area addressed, time-frame, level of risk, geographical region, etc. The figure below shows the result of adding a 'Time frame' attribute with Short, Medium, and Long term category items: Benefits vs. Costs 2D Plots The figure below shows a 2d plot of benefits vs.
Costs for a set of projects, color coded by the Time frame category. Some organizations that don't have access to a resource aligner optimizer might use such a plot to hand select a 'balance' of projects that tend to be in the upper left of the plot (high benefit and low cost). They might also try to get some 'balance and coverage' for different strategic buckets such as Time frame. We can create a plot as above, but show only the funded projects or other plot view options: We could do this for different strategic bucket categories and look for cases where there may be an imbalance or lack of coverage. If we observe any, we could then add constraints to the resource aligner to constrain the projects in a category to some maximum or minimum number. There are many other capabilities available so that the decision makers can easily mold the optimum portfolio to their needs and wants.
The decisions and resource allocations that Expert Choice are applied to are almost always complex, important (even crucial) and thus require iteration. One pass through a series of steps is hardly ever enough. There are many reasons for this including but not limited to:. Someone in the group feels that Alternative Y is really more preferred than Alternative X because of it's style, and you realize that style was not included as an objective.
The most preferred alternative is likely to cause political problems with another part of the organization, resulting in delays in getting approval. Adding an objective of time to get approval should be added to the model. The combination of the two most preferred alternatives suggests another alternative that was not considered, and should now be added to the model.
A sensitivity analysis graph shows that the most costly alternative increases in priority as the importance of cost increases, indicating that judgments were entered incorrectly, e.g. In making a pairwise comparison, which alternative is more costly, rather than which is more preferred with respect to cost. A performance analysis graphs shows that one alternative is best on every objective and every sub-objective! This is a sign of either a trivial decision, or more likely a sign that something was overlooked because if an alternative is best on every objective except cost, for example, it is most likely going to cost more. If this occurs, look at the pros and cons of the alternatives, especially the cons of the alternative that is best on every objective.
The cons of this alternative should 'point to' objectives for which this alternative is NOT best! If you then add one or two objectives or sub-objectives based on the cons of the best alternative, you can send a link to participants to re-evaluate the project and click on 'next unassessed' to enter the few additional judgments necessary. Perhaps the most important reason is that your intuition does not agree with the results. AHP and Expert Choice models are unlike any other economic or management models in that they can and should incorporate any and all considerations - qualitative as well as quantitative, subjective as well as objective. With adequate iteration, the results obtained with Expert Choice will always make sense. In some cases, the iteration will change the priorities of the alternatives to match ones intuition while in other cases ones intuition will change due to insights gained from the model. There is no fixed sequence for iteration.
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In some cases, it might be obvious that additional alternatives should be identified or designed. In other cases, additional objectives added to the objectives hierarchy. Participant roles and judgments might need to be reexamined and discussed. For either of the above cases you can return to the Structuring step at the top level workflow, or click on the link to structuring in the structuring tabby under this Iteration step which will take you there as well.
In some cases you might want to review the judgments made in the Measurement step. You can return to the Measurement step at the top level workflow, or click on the link to Measurement in the Measurement tabby under this Iteration step which will take you there as well. Hint: Before iterating, you might want to make a copy of the project using the Save as option found in the Home Projects page: Regardless of what steps might be involved in iteration, the time required for iteration should be included in planning the decision process, and never as an afterthought. If iteration is required but not performed, two important benefits of the decision process are jeopardized: The ability to justify the decision to others who might object or delay, and the ability to track the success of the decision process over time. The Analytic Hierarchy Process (AHP) is a powerful and flexible decision making process to help people set priorities and make the best decision when both qualitative and quantitative aspects of a decision need to be considered. By reducing complex decisions to a series of one-on-one comparisons, then synthesizing the results, AHP not only helps decision makers arrive at the best decision, but also provides a clear rationale that it is the best. Designed to reflect the way people actually think.
Designed to reflect the way people actually think, AHP was developed in the 1970’s by Dr. Thomas Saaty, while he was a professor at the Wharton School of Business, and continues to be the most highly regarded and widely used decision-making theory. Saaty joined Dr. Ernest Forman, a professor of management science at George Washington University, to co-found Expert Choice. Structured Decision Making The AHP and Expert Choice software engage decision makers in structuring a decision into smaller parts, proceeding from the goal to objectives to sub-objectives down to the alternative courses of action. Decision makers then make simple pairwise comparison judgments throughout the hierarchy to arrive at overall priorities for the alternatives. The decision problem may involve social, political, technical, and economic factors.
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Analysis of Objective and Subjective Data The AHP helps people cope with the intuitive, the rational and the irrational, and with risk and uncertainty in complex settings. It can be used to:. predict likely outcomes.
plan projected and desired futures. facilitate group decision making. exercise control over changes in the decision making system.
allocate resources. select alternatives. select alternatives. do cost/benefit comparisons Expert Choice is intuitive, graphically based and structured in a user-friendly fashion so as to be valuable for conceptual and analytical thinkers, novices and category experts.
Because the criteria are presented in a hierarchical structure, decision makers are able to drill down to their level of expertise, and apply judgments to the objectives deemed important to achieving their goals. At the end of the process, decision makers are fully cognizant of how and why the decision was made, with results that are meaningful, easy to communicate, and actionable.
HUNTSVILLE, Texas - A former Dallas accountant condemned for fatally shooting his two young daughters while their mother listened helplessly on speakerphone is looking to the U.S. Supreme Court to spare his life. John David Battaglia is set for execution Thursday evening for the May 2001 killings of his 9-year-old daughter, Faith, and her 6-year-old sister, Liberty. Battaglia and his wife had separated and the girls were killed at his Dallas apartment during a scheduled visit. Battaglia's attorneys have asked the Supreme Court to stop the punishment and review his case, contending Battaglia, 62, was delusional and mentally incompetent for execution.
Circuit Court of Appeals, hours before Battaglia's scheduled punishment, rejected an appeal that argued a lower court improperly refused his lawyers money to hire an expert to further examine legal claims he's mentally incompetent for execution. The Supreme Court has ruled that prisoners can be executed if they're aware the death penalty is to be carried out and have a rational understanding of why they're facing that punishment.
Attorneys for Battaglia contend that he doesn't have that understanding and that the state's highest court, the Texas Court of Criminal Appeals, misapplied the Supreme Court's guidance when it ruled that Battaglia is competent. They also argue that a federal judge improperly denied their requests for additional money to hire an expert to collect information about his competency, which has been the focus of prolonged appeals in his case. State attorneys argued that the Texas courts ensured proper legal standards were followed and that Battaglia had been provided expert help and a court hearing in accordance with Supreme Court precedents. A state judge and the state appeals court described Battaglia as highly intelligent, competent, not mentally ill and faking mental illness to avoid execution. Testimony at a hearing showed Battaglia used the prison library to research capital case rulings on mental competence and discussed with his father during a phone call from jail the 'chess game' of avoiding execution. State Judge Robert Burns, who found him competent, said Battaglia's intelligence and education - he has a master's degree - shows he's not a 'typical inmate' and has the 'motive and intellectual capability to maintain a deliberate ploy or ruse to avoid his execution.'
According to prosecutors, Battaglia became enraged that his estranged wife, Mary Jane Pearle, notified police about his harassment and he used the visit with their daughters to act on his anger. Pearle, who had gone to dinner, returned a call from one of her daughters and heard Faith pleading with her father, who put the call on speakerphone. 'No, daddy, please don't, don't do it!' Faith begged.
Pearle yelled into the phone for the children to run, then heard gunshots. Christmas,' Battaglia told Pearle, the words of the holiday greeting derisively divided by an obscenity. There were more gunshots. Pearle called 911. At the time of the shootings, Battaglia was on probation for a Christmas 1999 attack on Pearle. His profanity-laced Christmas greeting to Pearle was an apparent reference to that. Faith was shot three times, Liberty five.
Hours later, Battaglia was arrested outside at a tattoo shop where he had two large red roses inked on his left arm to commemorate his daughters. It took four officers to subdue him. A fully loaded revolver was found in his truck and more than a dozen firearms were recovered from his apartment. Battaglia told The Dallas Morning News in 2014 his daughters were his 'best little friends' and that he had photos of them displayed in his prison cell. 'I don't feel like I killed them,' he said. 'I am a little bit in the blank about what happened.'
Battaglia would be the nation's third prisoner executed this year, all in Texas.