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Action Research

“If I look for better ways to manage projects, then I can increase competitive advantage for our entire organization, but it’s hard for organizations to learn from their activities.”

Whatever way you look at Action Research, you’ll find it the favorite of project managers, and by the way, the most valuable part of being in a community. The purpose of action research is to develop new skills or new approaches and to solve problems with direct application to your project, Integrated PM methods, or within the working PM setting.

Examples:

  • An Integrated PM training program to help train PMs to work more effectively with project team members; to develop an exploratory program leveraging less approval points for efficiency; to solve the problem of apathy in chartering meeting with the project sponsor; to test a fresh approach to interesting more clients in project progress prior to project completion.
  • A community initiative to get more community members contributing their thoughts and solutions in the community forum called Straight Talk.
  • Teaching site visitors how to use the pmNERDS’ website annotation features to further their Integrated PM studies Characteristics:
  • Practical and directly relevant to an actual situation in the working Integrated PM world. The subjects are the project managers, the sponsors, community members, or others with whom you are primarily involved. Provides an orderly framework for problem-solving and new developments that are superior to the impressionistic, fragmentary approach that otherwise typifies develop¬ments in project management. It also is empirical in the sense that it relies on actual observations and behavioral data, and does not fall back on subjective committee "studies" or opinions of people based on their past experience.
  • Flexible and adaptive, allowing changes during the trial period and sacrificing control in favor of responsiveness and on-the-spot experimentation and innovation.
  • While attempting to be systematic, action research lacks scientific rigor because its internal and external validity are weak. Its objective is situational, its sample is restricted and unrepresentative, and it has little control over independent variables. Hence, its findings, while useful within the practical dimensions of the situation, do not directly contribute to the general body of Integrated PM knowledge.

Steps:

  1. Define the problem or set the goal. What is it that needs improvement or that might be developed as a new skill or solution?
  2. Review the literature to learn whether others have met similar problems or achieved related objectives.
  3. Formulate testable hypotheses or strategies of approach, stating them in clear, specific, pragmatic language.
  4. Arrange the research setting and spell out the procedures and conditions. What are the tasks you will perform in an attempt to meet your objectives?
  5. Establish evaluation criteria, measurement techniques, and other means of acquiring useful feedback.
  6. Analyze the data and evaluate the outcomes.
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Quasi Experimental Research

“If we used a true experimental research method, then we would have the best-results, but we can’t control all the relevant state variables.”

Many times, our clients don’t have the time, or variable control required for true experimental research, but still need estimates to provide direction for their performance improvement initiatives. In these cases, they can approximate the conditions of the true experiment in a setting which does not allow the control and/or manipulation of all relevant variables. The researcher must clearly understand what compromises exist in the internal and external validity of the design, and proceed within these limitations.

Examples:

  1. To investigate the effects of spaced versus massed task execution in the to-do lists for project teams without being able to assign team members to the test at random or to supervise closely the execution of their tasks.
  2. To assess the effectiveness of three approaches to teaching basic principles and concepts in Integrated PM when some of the teachers could inadvertently volunteer for one of the approaches because of its impressive-looking materials.
  3. Project value realization research involving a pretest-posttest design in which such variables as maturation, effects of testing, statistical regression, selective attrition, and stimulus novelty or adaptation, are unavoidable or overlooked.
  4. Most studies of business unit problems of late projects, poor quality, cost over runs, or instances of canceled projects, where control and manipulation are not always feasible.

Characteristics:

  1. Quasi-experimental research typically involves applied settings where it is not possible to control all the relevant variables but only some of them. The researcher gets as close to the true experimental rigor as conditions allow, carefully qualifying the important exceptions and limitations. Therefore, this research is characterized by methods of partial control based on a careful identification of factors influencing both internal and external validity.
  2. The distinction between true and quasi-experimental research is tenuous, particularly where human subjects are involved as in projects. A careful study of the relative nature of this distinction as a matter of approximation on a continuum between "one-shot case studies" of an action research nature to experimental-control group designs with randomization and rigorous man¬agement of all foreseeable variables influencing internal and external validity.
  3. While action research can have quasi-experimental status, it is often so unformalized as to deserve separate recognition. Once the research plan systemati¬cally examines the validity question, moving out of the intuitive and exploratory realm, the beginnings of experimental methodology are visible.

Steps in Quasi-Experimental Research: The same as with true experimental research, carefully recognizing each limitation to the internal and external validity of the design.

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True Experimental Research

“If we research practices to identify project constraints, then we can identify ways to improve project performance, but how do we know we can trust our findings before we commit irrevocable resources into the performance improvement effort?”

The perspective of Integrated PM is perfect for true experimental research, and performance improvement. This is how a program center can finally explore the correlations and interconnections between all the facets of the project, and other projects within the program and portfolio. This True Experimental Research is the investigation of possible cause-and-effect relationships by exposing one or more experimental groups to one or more treatment conditions, and comparing the results to one or more control groups not receiving the treatment.

Examples:

  1. To investigate the effects of two methods of new practice implementation as a function of project size (Maintenance & Utility, Enhancement & Improvement, and Transformational) and levels of PM experience (high, average, low), using random assignment of projects and project manager experience levels to method and business unit.
  2. To investigate the effects of a new practice training program on the organization’s project managers using experimental and control groups who are either exposed or not exposed to the program, respectively, and using a pretest-posttest design in which only half of the project managers randomly receive the pretest to determine how much of a performance change can be attributed to pretesting or to the training program.
  3. To investigate the effects of two methods of project value realization evaluation on the performance of project teams within the business unit. N in this study would be the number of project teams, rather than project managers, and the method would be assigned by stratified random techniques such that there would be a balanced distribution of the two methods to projects across the business unit.

Characteristics of Experimental Designs:

  1. True experimental research requires rigorous management of experimental variables and conditions either by direct control manipulation or through randomization.
  2. Typically uses a control group as a baseline against which to compare the group(s) receiving the experimental treatment.
  3. Concentrates on the control of variance:
    • To maximize the variance of the variable(s) associated with the research hypotheses.
    • To minimize the variance of extraneous or "unwanted" variables that might affect the experimental outcomes, but are not themselves the object of study.
    • To minimize the error or random variance, including so-called errors of measurement.

Random selection of subjects, random assignment of subjects to groups, and random assignment of experimental treatments to groups yield the best solution.

Internal validity is the ‘sine qua non’ of research design and the first objective of experimental methodology. It asks the question: Did the experimental manipulation in this study really make a difference?

External validity is the second objective of experimental methodology. It asks the question: How representative are the findings and can the results be generalized to similar circumstances and subjects?

In classic experimental design, all variables of concern are held constant except a single treatment variable which is deliberately manipulated or allowed to vary. Advances in methodology such as factorial designs, analysis of variance and multiple regression now allow the experimenter to permit more than one variable to be manipulated or varied concurrently across more than one experimental group.

This permits the simultaneous determination of

  • the effects of the principal independent variables (treatments),
  • the variation associated with classificatory variables, and
  • the interaction of selected combinations of independent and/or classificatory variables.

While the experimental approach is the most powerful because of the control it allows over relevant variables, it is also the most restrictive and artificial. This is a major weakness in applications involving human subjects in real world situations, since resources often act differently if their behavior is artificially restricted, manipu¬lated, or exposed to systematic observation and evaluation.

Seven Steps in Experimental Research:

  1. Survey the literature relating to the problem.
  2. Identify and define the problem.
  3. Formulate a problem hypothesis, deducing the consequences, and defining basic terms and variables.
  4. Construct an experimental plan:
    • Identify all nonexperimental variables that might contaminate the experiment, and determine how to control them.
    • Select a research design.
    • Select a sample of subjects to represent a given population, assign subjects to groups, and assign experimental treatments to groups.
    • Select or construct and validate instruments to measure the outcome of the experiment.
    • Outline procedures for collecting the data, and possibly conduct a pilot or "trial run" test to perfect the instruments or design.
    • State the statistical or null hypothesis.
  5. Conduct the experiments.
  6. Reduce the raw data in a manner that will produce the best appraisal of the effect which is presumed to exist.
  7. Apply an appropriate test of significance to determine the confidence one can place on the results of the study.
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Correlational Research

“If we compare project managers to the project performance, then we might understand what is causing good project performance, but we don’t understand how to conduct good correlational studies.”

Have you ever wondered just what caused you bad hair day? This is the purpose of ‘Correlational Research’, well not really. It’s not this at all, but we can still benefit from the research. The purpose is to investigate the extent to which variations in one factor of Integrated PM correspond with variations in one or more other project factors based on correlation coefficients.

Examples:

  • A study investigating the relationship between charter existence as the criterion variable and a few of the variables for successful projects.
  • A factor-analytic study of several personality tests of the project manager.
  • A study to predict success in project performance based on intercorrelation patterns for task variables.

Characteristics: Appropriate where variables are very complex and/or do not lend themselves to the experimental method and controlled manipulation. Correlational Research permits the measurement of several variables and their interrelationships simultane¬ously and in a realistic setting. It gets at the degrees of relationship rather than the all-or-nothing question posed by experimental design: "Is an effect present or absent?"

Weakness: Among its limitations are the following:

  • It only identifies what goes with what-it does not necessarily identify cause-and-effect relationships.
  • It is less rigorous than the experimental approach because it exercises less control over the independent variables.
  • It is prone to identify spurious relational patterns or elements which have little or no reliability or validity.
  • The relational patterns are often arbitrary and ambiguous.
  • It encourages a "shot-gun" approach to research, indiscriminately throwing in data from miscellaneous sources and defying any meaningful or useful interpretation.

Steps:

  1. Define the problem.
  2. Review the literature.
  3. Design the approach:
  4. Identify the relevant variables.
  5. Select appropriate subjects.
  6. Select or develop appropriate measuring instruments.
  7. Select the correlational approach that fits the problem.
  8. Collect the data.
  9. Analyze and interpret the results.

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Causal - Comparative Research

“If we want to reduce the amount of changes made at the end of our projects, then we need to find out the causes to so many changes, but that means we should do causal-comparative research.”

Nowadays they tell us that the Boston Massacre wasn’t really what it was claimed to be. What was the cause? There are times that we might feel discovering the cause of project problems might be just as unpopular as digging around in the Boston Massacre. But if you must, then do it right.

One of the most common research methods used in Integrated PM is the Causal-Comparative research method. It’s used to investigate possible cause-and-effect relationships by observing some existing consequence (effect) and searching back through the data for plausible causal factors. This contrasts with the experimental method which collects its data under controlled conditions in the present.

Examples:

  1. To identify factors characterizing persons having either high or low approval rates, using data from past project records.
  2. To determine the attributes of effective project sponsors as defined, for example, by their realized project value. Portfolio and program records over the past five years are then examined, comparing these data to the number of innovative projects or several other factors.
  3. To look for patterns of behavior and achievement associated with project manager experience differences, using descriptive data on project behavior and project value achievement.

Principal Characteristics: Causal-comparative research is "ex post facto" in nature, which means the data are collected after all the events of interest have occurred. The investigator then takes one or more effects (dependent variables) and examines the data by going back through time, seeking out causes, relationships, and their meanings.

Strengths: The causal-comparative method is appropriate in many circumstances where the more powerful experimental method is not possible. It is used when it is not always possible to select, control, and manipulate the facts necessary to study cause-and-effect relations directly. It also can be used when the control of all variations except a single independent variable may be highly unrealistic and artificial, preventing the normal interaction with other influential variables. Of course, with most project conditions, it is used when laboratory controls for many research purposes would be impractical, costly, or ethically questionable.

Note: The experimental method involves both an experimental and a control group. Some treatment "A" is given the experimental group, and the result "B" is observed. The control group is not exposed to "A" and their condition is compared to the experimental group to see what effects "A" might have had in producing "B." In the causal-comparative method, the investigator reverses this process, observing a result "B" which already exists and searches back through several possible causes ("A" type of events) that are related to "B."

  1. It yields useful Integrated PM information concerning the nature of phenomena: what goes with what, under what conditions, in what sequences and patterns, and the like.
  2. Improvements in techniques, statistical methods, and designs with partial control features, in recent years involving Integrated PM, have made these studies more defensible.

Weaknesses: The main weakness of any ex post facto design is the lack of control over independent variables. Within the limits of selection, the investigator must take the facts as they are found with no opportunity to arrange the conditions or manipulate the variables that influenced the facts in the first place. To reach sound conclusions, the investigator must consider all the other possible reasons or plausible rival hypotheses which might account for the results obtained. To the extent that the conclusions can be successfully justified against these other alternatives puts the investigator in a position of relative strength. The difficulty in being certain that the relevant causative factor is included among the many factors under study.

  1. The complication that no single factor is the cause of an outcome but some combination and interaction of factors go together under certain conditions to yield a given outcome. A phenomenon may result not only from multiple causes but also from one cause in one instance and from another cause in another instance.
  2. When a relationship between two variables is discovered, determining which is the cause and which the effect may be difficult.
  3. The fact that two or more factors are related does not necessarily imply a cause-and-¬effect relationship. They all simply may be related to an additional factor not recognized or observed. Classifying subjects into dichotomous groups (e.g., "Achievers" and "Non-achievers") for comparison is fraught with problems, since categories like these are vague, variable, and transitory. Such investigations often do not yield useful findings.
  4. Comparative studies in natural situations do not allow controlled selection of subjects. Locating existing groups of subjects who are similar in all respects except for their exposure to one variable is extremely difficult.

Steps:

  1. Define the problem.
  2. Survey the literature. State the hypotheses. List the assumptions upon which the hypotheses and procedures will be based.
  3. Design the approach:
    • Select appropriate subjects and source materials.
    • Select or construct techniques for collecting the data.
    • Establish categories for classifying data that are unambiguous, appropriate for the study, and capable of bringing out significant likenesses or relationships.
  4. Validate the data-gathering techniques.
  5. Describe, analyze, and interpret the findings in clear, precise terms.
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Case & Field Study Research

“If I gain a wholistic understanding of why projects succeed and fail, then I can take measures to encourage success, but I’m not sure of how to conduct this kind of investigation.”

I don’t know. Living out with the wild creatures doesn’t seem like my cup of tea. But I’m glad someone is doing it. My wife and I love watching the films, but don’t need the dirty and danger part. It’s a good thing that while studying Integrated PM you rarely need to live with the Lions. Can you imagine hiding behind a rock or bush building a case study for someone?

The case and field study method is used to intensively study the background, status, and cultural interactions of a given business unit: an individual, project team, program, or enterprise.

Examples:

  • Many of my clients have benefited from a study of past projects to define a set of common project life-cycle stages.
  • An in-depth study of an individual working in a specific job role who either excels above others, or is consistently a low performer to explain the anomalies.
  • An intensive study of a "project team" culture and communication styles in a business unit.
  • A study of projects within a portfolio examining the interconnections of state variables and objective dependencies.

Characteristics: Case studies are in-depth investigations of a given business unit resulting in a complete, well-organized picture of that unit. Depending upon the purpose, the scope of the study may encompass an entire project life cycle or only a selected segment; it may concentrate upon specific factors or take in the totality of elements and events.

Compared to a survey study which tends to examine a small number of variables across a large sample of units, the case study tends to examine a small number of units across a large number of variables and conditions.

Strengths: Case studies are particularly useful as background information for planning major capital projects and programs. Because they are intensive, they bring to light the important variables, processes, and interactions that deserve more extensive attention. They are a part of strategic planning, may pioneer new ground, and often are the source of fruitful hypotheses for further projects. Case study data provide useful anecdotes or examples to illustrate more generalized statistical findings.

Weaknesses: Because of their narrow focus on a few business units, case studies are limited in their representativeness. They do not allow valid generalizations to the enterprise or beyond where they came until the appropriate follow-up research is accomplished, focusing on specific hypotheses and using proper sampling methods.

Case studies are particularly vulnerable to subjective biases. The case itself may be selected because of it's dramatic, rather than typical, attributes; or because it neatly fits the researcher’s preconceptions. To the extent selective judgments rule certain data in or out, or assign a high or low value to their significance, or place them in one context rather than another, subjective interpretation is influencing the outcome.

Steps:

  1. State the objectives. What is the unit of study and what characteristics, relationships, and processes will direct the investigation?
  2. Design the approach. How will the units be selected? What sources of data are available?
  3. What data collection methods will be used?
  4. Collect the data.
  5. Organize the information to form a coherent, well-integrated reconstruction of the unit being studied.
  6. Report the results and discuss their significance. 

The case study is a perfect launching point to provide focus in further studies and for establishing internal common grounds in programs.

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Descriptive Research

“If I use observation, surveys, and market evidence to test developed hypothesizes, then I may discover important concepts, but I’m not sure how to do it, and I may lead myself off track.”

Keith Goffin, author of ‘Identifying Hidden Needs’ indicates “that a survey researcher asks people questions in a written questionnaire … or during an interview, then records answers. The researcher manipulates no situation or condition; people simply answer questions.” The trick is to gather information without influencing it.

The descriptive research method is a common practice for performance and process improvement within the world of projects. The desire is to describe systematically the facts and characteristics of a given team, organization, or set of projects, factually and accurately.

Some examples of this method include:

  • An opinion survey to assess the perceived value of an IT line of service.
  • A team survey to review the effectiveness of a project workflow.
  • A study and definition of all job roles within a business unit.
  • A report of project completion status ‘On Time’ vs. ‘Late.’

Descriptive research is used in the literal sense of describing situations or events. It is the accumulation of a data base that is solely descriptive- it does not necessarily seek or explain relationships, test hypotheses, make predictions, or get at meanings and impli¬cations, although research aimed at these more powerful purposes may incorporate descriptive methods. In this way, historic records of completed projects, and related values of state variables support descriptive research.

Research authorities, however, are not in agreement on what constitutes "descriptive research" and often broaden the term to include all forms of research except historical and experimental. In this broader context, the term survey studies are often used to cover the examples listed above.

Typical purpose of these ‘Survey Studies’ include:

  • To collect detailed information that describes existing phenomena.
  • To identify problems or justify current conditions and practices.
  • To make comparisons and evaluations.
  • To determine what others are doing with similar problems or situations and benefit from their experience in making plans and decisions.

The steps for conducting Descriptive Research are:

  1. Define the objectives in clear, specific terms. What facts and characteristics are to be uncovered? .
  2. Design the approach. How will the data be collected? How will the subjects be selected to insure they represent the population to be described? What instruments or observa¬tion techniques are available or will need to be developed? Will the data collection methods need to be field-tested and will data gatherers need to be trained? .
  3. Collect the data. .
  4. Report the results.
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Developmental Research

“If I studied past projects, then I could identify areas of improved performance, but I’d like an overview of the process before beginning.”

Ok, I’ve got a real fancy pants set of words for you today, “Developmental Research.” Yes, it is a R&D method, but we already are doing this less formally at some time. In fact, that’s the case with most of the methods in this series.

The purpose for developmental research methods are to investigate patterns and sequences of growth and/or change as a function of time. Of course, this becomes an essential method of most project performance improvements initiatives.

Some examples of Developmental Research would include:

  • A project study that involves repeated observations of the same set state variables (e.g., project or task durations) over long periods of time.
  • Quality studies directly measuring the nature and rate of changes in a sample of the same work products being delivered in different quarters.
  • Cross-sectional growth studies indirectly measuring the nature and rate of the same state variable changes by drawing samples of different projects from representative business units over time.
  • Trend studies designed to establish patterns of change in the past to predict future patterns or conditions.

Some common characteristics of developmental research include focuses on the study of variables and their development over a period of months or years. It asks, ''What are the patterns of growth, their rates, their directions, their sequences, and the interrelated factors affecting these characteristics?"

The sampling problem in this method is complicated by the limited number of subjects it can follow over the years; any selective factor affecting attrition biases the study. If the threat of attrition is avoided by sampling from a stable population, this introduces unknown biases associated with such populations. Furthermore, once underway, the method does not lend itself to improve¬ments in techniques without losing the continuity of the procedures. Finally, this method requires the continuity of staff and financial support over an extended period and typically is confined to a specific business unit or program that can maintain such an effort.

Cross-sectional studies involving developmental research usually include more subjects, but describe fewer growth factors than single unit studies. While the latter is the only direct method of studying project team development, the cross-sectional approach is less expensive and faster since the actual passage of time is eliminated by sampling different project managers across organizations.

Sampling in the cross-sectional method is complicated because the same project managers are not involved with the same projects and may not be comparable. To generalize intrinsic developmental patterns from these sequential samples of projects runs the risk of confusing differences due to development with other differences between the groups that are artifacts of the sampling process.

Trend studies are vulnerable to unpredictable factors that modify or invalidate trends based on the past. In general, long-range prediction is an educated guess while short-range prediction is more reliable and valid.

The steps for conducting developmental research are:

  1. Define the problem or state the objectives.
  2. Review the literature to establish a baseline of existing information and to compare research methodologies including available instruments and data collection techniques.
  3. Design the approach.
  4. Collect the data.
  5. Evaluate the data and report the results.
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Historical Research

If I collect data like Lessons Learned, and risk logs, then I could learn from the past, but I really don’t know how to conduct historical research effectively.”

Give me any three clients, and I'm betting they will have at least five different ways to do ‘Lessons Learned’ at the end of their projects. They’ll tell me, “Oh I didn’t know Lessons Learned was historical research.” Sarah Adams, a Sr. Project Manager, PHP and somewhat of a monster … well let’s just say, Application Development Team Lead under a lot of pressure.

She pushed the team to hold Lesson Learned at the end of every project phase, but no one ever did anything with them. “Then why did they hold the meetings?” you ask. Because that’s how Sarah was trained, that’s how she did it, and when you were on her project team, that’s how you did it.

It really is too bad, what a waste. The good thing is that if you stick around, you could change this. Maybe we won’t have to wait forever. You could show her a better way. Let’s look at Lessons Learned, Project Reviews, and the like, through the lens of historical research.

Historical Research is a viable research and development method that we can all practice. As we strive to improve and better understand Integrated PM, each one of us, using historical research, can advance the cause.

The purpose of historical research is to reconstruct the past systematically and objectively by collecting, evaluating, verifying, and synthesizing evidence to establish facts and reach defensible conclusions, often in relation to a set of particular hypotheses. With a little care, Lessons Learned and project reviews can provide the PM (Researcher) with the evidence needed.

Sarah was close to being a good example of this, but she didn’t follow through. She wasn’t looking through the lens of research. You bet she systematically collected evidence. However, as far as I know, she never formed a hypothesis to confirm or deny. I need to give Sarah a break for a bit, after all, they never told her at the PMI that she needed to be a researcher.

What does historical research even look like? Let’s take a look at some typical characteristics.

Normally, historical research depends upon data observed by others rather than by the investigator. This means looking at other’s project plans and Lessons Learned documents. Good data results from painstaking detective work which analyzes the authenticity, accuracy, and significance of source material. So now Miss Sarah Adams needs to be a detective, researcher, and in a few sentences, you’ll see the need for a scientist too.

Contrary to popular notions, historical research must be rigorous, systematic, and exhaustive; much "research" claiming to be historical is an undisciplined collection of inappropriate, unreliable, or biased information and conclusions.

Historical research depends upon two kinds of data: primary sources where the researcher was a direct observer of the recorded event, and secondary sources where the researcher is reporting the observations of others and is one or more times removed from the original event. Of the two, primary sources carry the authority of firsthand evidence and have priority in data collection.

Two basic forms of criticism weigh the value of the data: external criticism which asks, "Is the document or relic authentic?" and internal criticism which asks, "If authentic, is the data accurate and relevant?" Internal criticism must examine the motives, biases, and limitations of the researcher, which might cause exaggeration, distortion, or overlooking information. This critical evaluation of the data is what makes true historical research so rigorous-in many ways, more demanding than experimental methods.

While historical research is similar to the "reviews of the literature" which precede other forms of research, the historical approach is more exhaustive, seeking out information from a larger array of sources. It also tracks down information that is much older than required by most reviews and hunts for unpublished material not cited in the standard references.

The Steps for Performing Historical Research:

1. Define the problem. Ask yourself these questions: Is the historical approach best suited for this problem? Is pertinent data available? Will the findings be educationally significant?

2. State the research objectives and, if possible, the hypotheses that will give direction and focus to the research.

3. Collect the data, keeping in mind the distinction between primary and secondary sources. An important skill in historical research is note-taking-small file cards (3 x 5, 4 x 6), each containing one item of information and coded by topic, are easy to rearrange and convenient to file.

4. Evaluate the data, applying both internal and external criticism.

5. Report the findings, including a statement of the problem, a review of source material, a statement of underlying assumptions, basic hypotheses, and methods used to test the hypotheses, the findings obtained, the interpretations and conclusions reached, and a bibliography.

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Call For Papers

“If I write-up a study of our experiences with Integrated PM, then it could be published in the R&D Journal of Integrated PM, and be improved upon for all our benefit, but I don’t have the quantitative data that is expected in a scholarly R&D Journal.”

The difference between qualitative and quantitative studies is more than just levels of abstraction. Turns out acceptance is another difference. We need papers utilizing the power of qualitative assessments. Let me explain.

Integrated PM research is a project value realization activity, and project value realization is a philosophy concerning how to create competitive advantage using projects. As a philosophy, project value realization competes against other philosophies that make different prescriptions for business success. Notable among competitors to the project value realization philosophy are

  • the marketing philosophy (success comes from focusing on markets and customer’s needs to guide business decisions),
  • the innovation philosophy (success comes from technology leadership),
  • the quality philosophy (success comes from building the highest quality products),
  • and the financial philosophy (success comes from making the most efficient use of resources).

At pmNERDS, we believe that Integrated PM is a combination and acceptance of all these philosophies as essential parts of the entire system. Because Integrated PM research reflects an enterprise wide business philosophy, and because this philosophy focuses on learning, organization change may be required when the firm desires to improve its project’s performance with respect to Integrated PM research. Put another way, to be truly effective, Integrated PM research cannot be treated as an isolated function assigned to specialized staff. It must be a cultural orientation that suffuses the organization.

For Integrated PM research studies, the core competence is problem formulation skills. Most business situations do not present themselves as clearly delineated problems but as tangled messes that might be approached in a variety of ways. To succeed in an Integrated PM research study requires that the author clearly articulate the problem to be addressed and the specific kinds of information needed.

If someone was to pick up a project study you might think that factor analysis was a more important component of commercial Integrated PM research than focus groups. In fact, statistical techniques have their place, but are more likely to be seen in academic than commercial research contexts.

There are good historical and sociological reasons for the relative neglect of qualitative Integrated PM research techniques. First of all, the path to promotion and prestige in academic social science rests on the ability to master arcane statistical analysis. Ph.D. programs in projects and in supporting disciplines such as psychology and economics heavily emphasize training in statistics and associated mathematical subjects such as probability theory.

The best journals feature the most elaborate and advanced statistical treatments. Publication in such journals is sine qua non for promotion and tenure. As a result, most instructors teaching projects, particularly those teaching in the better graduate programs, owe much of their career success to their facility with and mastery of statistical analysis. It should come as no surprise if their course syllabi and the textbooks they choose also emphasize the analysis of quantitative project research data.

In IT, as in academia, there is also a bias towards quantitative data. In most technology firms, especially those that sell business to business, management staff consists of engineers and scientists. These are people whose career success may initially have rested on the mastery of the intricacies of the physics that underlie electrical engineering. This background leads quite naturally to a demand that Integrated PM researchers deliver precise numerical estimates.

Unfortunately, training in the physical sciences is not always a good preparation for training in the social sciences. Human data are different from physical data. Most notably, measurements on humans are subject to much greater uncertainty than the measurements taken on things, and are much more mutable- what is true today may not be true tomorrow, and what is true for this client may not be true for another client. Qualitative techniques are ideally suited to grappling with uncertainty and novelty.

In summary, the discipline needs Integrated PM research papers that corrects for the unequal and subordinate emphasis typically placed on qualitative techniques. Members of this community are in particular need of the potential benefits delivered by qualitative research. That is, technology managers, PMO Directors, Marketing Directors, are less familiar with non-quantified but disciplined social science research.

Perhaps more important, quantitative Integrated PM research techniques are often unsuitable for project markets, inasmuch as they may presume a sample drawn from a large homogeneous population (projects are most often fragmented and small), easy -to-explain product functionality (project products are complex), and a stable competitive and pricing environment (projects change rapidly). All these factors play to the strength of qualitative techniques.

Please then, don’t hesitate in submitting your research, there are additional blog posts that can help point you to research methods, and section editors who have volunteered to help bring your ideas to the rest of the community.

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Open Access Journals

“If I publish my research papers in the R&D Journal of Integrated PM, then other members of the community can base future research on my finding, but people outside our community won’t see it, and the benefit of publishing my studies is directly proportional to the number of other researchers reading it.”

You bet, there have been many different models for publishing journals containing research and development material. With electronic publication, we are no longer limited to a single publishing model, and it appears that for the foreseeable future a variety of different publishing models will operate in parallel. While still accounting for only a fraction of the overall scholarly publishing system, there are currently in excess of 2,700 Open Access Journals in the Directory of Open Access Journals. OA Journals operated by groups of colleagues, will never be the dominate form of scholarly publishing; but at the same time their numbers continue to grow, as does the quality of material they contain and their acceptance among scholars.

One of our reasons for going this direction is to provide information access to those who otherwise would not have the resources to acquire such resources. One of the most striking differences between paper and electronic publication is the cost of distribution. For paper journals, the cost of distributing each copy is significant and the only practical means of funding these journals is through subscription fees. With electronic distribution, the cost of dissemination disappears, making it possible to distribute journals freely to anyone who wants to access them and find other means of funding the operation of the journal. Calls for distributing at no cost and finding other means of funding began almost as soon as journals appeared in electronic formats.

The R&D Journal of Integrated PM is built on an open access journal framework which provides access to the OAJ community and is part of a global network of indexed journals, and can be accessed at most universities worldwide. There are five main purposes for pmNERDS to sponsor this R&D Journal on Integrated PM.

1) Most would agree that OAJ provides the most comprehensive, up-to-date and authoritative archive of information in a given scholarly field. Obviously, the accuracy and quality of the material contained in this archive is of central importance. Peer review services are one of the most important mechanisms for validating the information contained in these journals.

2) Communication among professionals working in the same field is another important objective. Within the Center of Excellence, Communication is King. The R&D Journal provides the foundation for that initial discussion which leads the practices of both innovation and learning.

3) The Journal also plays an important role in maintaining community standards on how research and practice development are conducted.

4) Recognition and reward might seem unimportant to some, put the submission of papers would justifiably stop if there wasn’t a benefit for doing so. The distribution and acknowledgement of achievement is an important role of the R&D Journal

5) Not all the information in the Journal strictly focuses on scholarly research. The Journal also acts a means of tying our Center Of Excellence together. The Open Access Journal provides many benefits to the community and the research contributor. We are constantly adding new capabilities to the journal in terms of submission process automation, reviewing, publishing, and distributing content. Feel free to reach out and volunteer to review submitted articles, and proofread submissions.

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Research & Development

“If I conducted an Integrated PM experiment, then I’d learn more about how Integrated PM improves project performance, but I haven’t had training in designing and conducting experiments, where do I start?"

Research projects come from Workshops, and our members interests. Once a project is proposed, members are needed to repeat and validate findings. Others apply the results to new practices of Integrated PM.

Let’s say you’ve developed a well-constructed problem statement. This is the kind you have before starting any project, and this includes a research project. Our next step is to construct the research design. Design decisions depend on the purposes of the study, the nature of the problem, and the alternatives appropriate for its investigation.

Once the principle purpose has been specified, define explicit scope and direction, attention needs to be focused on a delimited target area. The nature of the problem then plays the major role in determining what approaches are suitable. Design alternatives can be organized into nine functional categories based on these differing problem characteristics:

  1. Historical
  2. Descriptive
  3. Developmental
  4. Case or Field
  5. Correlational
  6. Causal-comparative
  7. True experimental
  8. Quasi-experimental
  9. Action

I’ll be committing a separate blog post explaining each of these categories of experiments in more detail later, for now consider this overview.

HISTORICAL- To reconstruct the past objectively and accurately, often in relation to the tenability of a hypothesis. “A study reconstructing practices in the teaching of Program Management in the United States during the past fifty years; testing the hypothesis that the PMI is the real author of current project management practices.”

DESCRIPTIVE- To describe systematically a situation or area of interest factually and accurately. “Population census studies, public opinion surveys, fact-finding surveys, status studies, task analysis studies, questionnaire and interview studies, observation studies, job descriptions, surveys of literature, documentary analysis, anecdotal records, critical incident reports, test score analysis, and normative data.”

DEVELOPMENTAL- To investigate patterns and sequences of growth and/or change as a function of time. “A longitudinal growth study following an initial sample of 200 PMs with from six months experience to 10 years experience in PM; a cross-sectional growth study investigating changing patterns of PMOs by sampling groups of PMO Directors with various levels experience; a trend study projecting the future growth of Integrated PM from the past trends and recent building estimates.”

CASE AND FIELD- To study intensively the background, current status, and environmental interactions of a given social unit: an individual group, institution, or community. “The case of the capacity planner with great credentials, but poor leadership skills; an intensive study of a group of teenage youngsters with PM training; an intensive study of a typical company in the Midwest in terms of its Integrated PM characteristics.”

COORRELATION- To investigate the extent to which variation in one factor correspond with variations in one or more other factors based on correlation coefficients. “To investigate relationships between task duration and one or more other state variables of interest; a factor-analytic study of several Integrated PM roles and capabilities; a study to predict success as a product manager based on intercorrelation patterns between project managers and selected marketing variables.”

CAUSAL-COMPARITIVE- To investigate possible cause-and-effect relationships by observing some existing consequence and searching back through the data for plausible causal factors. “To identify factors related to the project performance problem in particular organizations using data from project plans over the past ten years; to investigate similarities and differences between such groups as portfolio managers, program managers, capacity planners, and project managers, using data on file.”

TRUE EXPERIMENTAL- To investigate possible cause-and-effect relationships by exposing one or more experimental groups to one or more treatment conditions and comparing the results to one or more control groups not receiving the treatment (random assignment being essential). “To investigate the method effectiveness of teaching Integrated PM to elementary school students using random assignment of teaching methods and students; to investigate the effects of a lunch break on the performance on projects based on random assignment of projects and lunch breaks.”

QUASI-EXPERIMANTAL- To approximate the conditions of the true experiment in a setting which does not allow the control and/or manipulation of all relevant variables. The researcher must clearly understand what compromises exist in the internal and external validity of her design and proceed within these limitations. “Most so-called field experiments, operational research, and even the more sophisticated forms of action research with the attempt to get causal factors in real life settings where only partial control is possible.”

ACTION- To develop new skills or new approaches and to solve problems with direct application to the classroom or other applied setting. “An Integrated PM training program to help PMs develop new skills in facilitating project discussions; to experiment with new on-line approaches of teaching Integrated PM to PMs; to develop more effective consulting techniques in Integrated PM.”

Research and Development of Integrated PM methods is a powerful way of growing the practice, each of us standing on the shoulders of those before us, while preparing to carry those not yet here.

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