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Introduction Prior deciding on the project management most suitable approach, a PM must investigate the clarity of the two major variables, goal and solution (Wysocki, 2009: 299). Based on the criteria of clarity, Wysocki (2009: 327) defined 4 management “quadrants” adopting 5 PMLC models: § TPM: Linear and Incremental § APM: Iterative and Adoptive § xPM and MPx: Extreme Each type of the 5 PMLC models is expected to encounter various risks and failure factors.

The PM should asses the risks associated with each model, to decide the most convenient approach. Linear PMLC Model This model is the simplest among the illustrated models, since the 5 process groups are expected to occur once in the entire PMLC within the planned sequence (Wysocki, 2009: 343). A PM would adopt the linear model if the project undertaken is: clear in the aspects of goals and solutions, similar to previously executed projects, short in duration and falling in a single department’s authority.

However, and despite the simplicity associated with implementing this model; Wysocki (2009: 350-353) defined six weakness points for the linear model: limited flexibility to scope changes, high cost, last minute production of deliverables, requires early detailed planning, fixed sequence of work, and lake of focus on client value. In the construction industry, and per my limited experience, this model is widely adopted.

I believe that scope changes are the most challenging risk associated with this model. Hence, other than proper definitions of RBS, COS and POS, a PM should lay a contingency plan (including money and time) for those scope creeps, in addition to a very strict and rights reserving policy for scope changes’ approvals (Franchina, 2010). Incremental PMLC Model The model was designed to partially deliver incomplete deliverables through the PMLC through conducting sequential increments (Wysocki, 2009:358).

In addition, Wysocki (2009: 360-364) defined 7 associated risk areas with this model: seldom team intactness, incremental documentation, fixed set of processes, increment definitions are not based on business value, longer duration, requires clients involvement, and other problems due to dividing the deliverables. However, the first defined risk is the most serious, I believe. Since an alternative key role would affect the project’s performance dramatically. Thus, Franchina (2010) recommended planning the key player’s task in a manner that would keep them utilized through the PMLC.

However, I don’t believe in Franchina’s solution applicability, thus, I would further recommend the development of a methodology or a method statement for the crucial personnel to mitigate the effect of resources alternation. Iterative and Adaptive PMLC Model Despite the differences between the two models, both are having common risks: need for client’s involvement and undefined deliverables (Wysocki, 2009: 396-411). Franchina (2010) recommended two practical solutions: § During the planning process, the client’s involvements should be clearly reflected on the work schedule and accountability matrix should be defined; In addition, during the planning and controlling process, the client must be aware of the developed cost estimates, to decide the feasibility of the project against the expectations. Extreme PMLC Model The name of this model explains the amount of risk associated with the adoption. Since neither the goal nor the solutions are defined, the PM would be facing two major risks: uncertainty of solutions approach and the uncertainty of achieving materialized business values.

Franchina (2010) defined two mitigating actions, firstly, that the client should clearly understand, in the early stages, that his investment in a certain stage might be totally lost due to the undefined solutions, and that he might need to re-finance the project all over again. Secondly, the contractual documents might state clearly the associated risks to diminish the business-value liability of the provider. Conclusion All of the 5 PMLC models are expected to encounter risks and failures.

In the iterative model, scope changes are the most serious risk, by developing contingency plans and scope change’s strict policies risks would be mitigated. In the incremental model, developing a plan that utilizes the key player’s time along the definition of each role method statement/methodology, the risk of project’s team lack of intact would be mitigated. In the iterative and adaptive models, by defining client’s responsibility along the planning process and updating the client with the budgetary progress, risks would be mitigated.

Finally, extreme models are the most risk encountering models, however, through keeping the client aware of the associated risks and developing a right’s reserving contract –that diminish the liability of the provider for business value delivery— risks would be mitigated. Bibliography Franchina, T. (2010) The Five Project Management Life Cycles [Online] Project Management Forum’s Blog. Available from: http://projectmanagementforum. wordpress. com/2010/07/06/the-five-project-management-life-cycles/ (Accessed: 6 August 2011)




Double-Blind Control Experiment


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What is a Double-blind control experiment and where it is most effectively used for?

According to Cherry, (2020), a blind experiment is a study in which both the researchers and the participants are not aware of the individuals being investigated. There are several types of blind experiments which include double, single, and triple blinding tests. Specifically, double-blind controlled experiments involve placing the study’s participants into two groups, one that undergoes an investigational treatment and another one that acts as a control group that acquires a placebo. When it comes to a double-blind controlled experiment, both the researchers and the participants are usually not aware of the specific participants under experimental treatment and the ones receiving a placebo. A placebo is a non-reactive substance that has no effects on people taking it. The control group during these experiments serves as the baseline in determining the significant effects if any, from the exposure to the variable used in the test. Data gathered from the two groups are then compared to determine the impact of the study.

Double-blind control experiments are most effectively used in the medical industry for testing the effectiveness of new or existing medical treatments. According to David, &Khandhar, (2019, double-blind control experiments are essential for clinical studies since the blinding factor helps maximize the validity of the results and thus are ranked as the validation of intervention’s treatment gold standards. With a double-blinded experiment, a researcher cannot treat the groups differently due to bias since both the researcher and the participants get blinded to the treatment that takes place. The factors that support the use of double-blind control experiments include the participants’ lack of knowledge about the group to which they belong, and thus their beliefs are not likely to influence the tests’ outcome. Additionally, the researchers are not likely to give the patients clues on the groups they belong to and thus they equally cannot influence the outcome.

In clinical setups, double-blind controlled experiments are useful in comparing a new drug to an older one whose working is already known. Other examples that apply the experiment include taste testing where individuals are made to compare the test of new substances to the existing ones. The experiments can also be conducted to conduct computer-generated surveys or in forensic applications. However, the double-blinding experiments are not possible in some situations such as when one wants to test for effective psychotherapy. Specifically, it is quite impossible to compare people’s psychologies.


David, S., &Khandhar, P. B. (2019). Double-Blind Study.

Kendra Cherry (2020).Double-Blind Studies in Research. VeryWellMind. Accessed 1st January 2021 from