Preventing Scope Creep in Your Research

Preventing Scope Creep in Your Research

When you find a research-worthy problem (Ellis & Levey, 2008), it is important to establish boundaries and discipline your focus to avoid scope creep. Scope creep is a continuous expansion of the problem, which results in seemingly harmless adjustments made to the project’s definitions, topics to be addressed, and final deliverables. The obscure nature of scope creep absorbs relevant topics through the distraction of other important matters, which overcomplicate your research study. Here’s where the Work of Leaders – Vision, Alignment, and Execution (VAE) process model can help discipline your focus (Straw, Scullard, Kukkonen, and Davis, 2013) as introduced in my previous blog post Developing Your Research Topic.

Vision: Start with the End Result in Mind

Craft your research vision by describing the end result of your research project. Your research vision is what you hope your research will accomplish when it is all said and done. For example, my research project in Mobile Technology and the Employee-Customer-Profit (ECP) Chain (Migliore & Chinta, 2016) had two end results:

  1. Build a regression model to predict likelihood of digital technology investments.
  2. Create a survey instrument to measure the variables in the regression model.

I found it helpful to write out statements that specified the end results of my research vision for this particular project. By having the end results in mind, it became easier to think about the specific type of data needed to achieve the research vision. Whether your research is quantitative or qualitative methodology, it’s always a good idea to start thinking early on about the type of data to be analyzed. For example, if quantitative, you need to determine the level of data (e.g. nominal, ordinal, interval, or ratio). If qualitative, you need to determine the type of data semantics (e.g. meaning of text, phrases, spoken words, or symbols, etc.). Then, you need to identify where the data will come from (e.g. personal recollections or experiences via interviews, focus groups, and observations; or from survey/test instruments, databases, and documents).

Research Questions

Well-established research questions guide your inquiry into the problem to be studied and help to prioritize the big picture of your research vision. For example, after I established a research-worthy problem (Ellis & Levey, 2008), which was focused on rapid changes associated with mobile technologies and executive-level decision making, I established the research questions, which included the variables and aligned it all within the scope of the conceptual model. The independent variable, understanding the ECP Chain, was defined as the C-level executive’s ability to comprehend and to judge the following:  “(1) the content and structural form of the organization’s interconnected relationships and processes, which influence positive exchanges between employees and customers for revenue generation, and (2) the value of digital technology for improving financial performance and creating value for competitive advantage” (Migliore & Chinta, 2016, p. 52). From this definition, three research questions guided the inquiry:

  1. To what extent can the likelihood of digital technology investments be predicted from C-level executives’ understanding of ECP Chain?
  2. How is the relationship between likelihood of digital technology investments and C-level executives’ understanding the ECP Chain influenced by the degree of importance that C-level executives accord to the ECP Chain elements?
  3. How is the relationship between likelihood of digital technology investments and C-level executives’ understanding the ECP Chain influenced by the frequency of reflection about the ECP Chain elements by C-level executives? (p. 54)

Research questions should align well to your end-result statements to guide your inquiry throughout the research project. Your ultimate goal is to answer the research questions and achieve the overall purpose of the study.

Test Your Assumptions

It is always a good idea to test your research assumptions before implementing a project. Your assumptions are beliefs and ideas believed to be true such as, your ability to obtain adequate sample size, recruit qualified research participants, access specialized data sources, etc. Therefore, reflect upon assumptions being made and the potential implications if your assumptions are not true.

For example, can you get access to the population, data, etc.?   If you get access, can you obtain the data?   You should always apply a realistic perspective early on in the planning of your research project, especially if you are targeting hard-to-reach audiences like CEOs, senior military personnel, etc.

Take for example, assumptions I made about accessing and obtaining data from a specialized target audience of C-level executives in the U.S. retail industry (NAICS codes 44 – 454390) and if they would really take 15-20 minutes out of their busy schedules to complete the survey (Migliore & Chinta, 2016). To test this assumption, I first had to vet several reputable research companies specializing in online panels of hard-to-reach audiences to determine if I could obtain an adequate sample size representative of the population under study. Then, I tested my assumptions in terms of cost, timing, legal and institutional review board (IRB) requirements, process efficiencies in data collection, and overall quality outcomes. In addition, I conducted a pilot test (after receiving IRB approval) to ensure a quality test sample of CEOs, CIOs, and CTOs, etc., and that the survey design formatted correctly both for desktop and mobile devices, since many of the research participants would be responding to the survey via a mobile phone.

Purpose and Alignment

Purpose and alignment are critical success factors for disciplining your research focus to improve clarity. Your study’s purpose statement should clarify pertinent details to align the main elements of the problem statement and research question(s). Main elements include things like the type of relationship or comparison you are interested in examining, variables, etc. Alignment of these main elements within the purpose statement helps improve focus and helps to define the scope of the study. For example:

  • The purpose of this quantitative causal comparative study will examine the cause of differences between U.S. Pharmaceutical Sales Representatives and Pharmaceutical Customer Service Representatives on gender, performance evaluation, and compensation
  • The purpose of this qualitative case study is to examine how the experience of heroin withdrawal symptoms  influences the process of resilience in 20 participants residing within the State of Michigan who are between the ages of 18 -30 and who self-identify as a heroin substance abuser

Execution: Research Action Plan

The discipline to execute the research action plan is equally as important as the previous steps in the process for turning research vision into scholarship. Here is where momentum is needed to execute action and achieve success.

For example, after receiving IRB approval, do what you said you were going to do – that is, execute according to the plan. If it’s your dissertation proposal, execute your research plan according to what is written in Chapter 3. If it’s a research fellow project, execute according to the research plan you established in your proposal for your selected methodology and design.

As you execute the research action plan, pay attention to the details, because details matter. For example, when analyzing data in the SPSS application, it is important to double check results (e.g. hypothesis post hoc tests). In addition, when setting variables in the SPSS application you need to identify the data types of the variables correctly, otherwise garbage in equals garbage out. You also want to make sure you are selecting and running the right statistical test(s) to get meaningful data results. Here too is where you need to check the details made about your data assumptions in terms of the level of measurement (e.g. nominal, ordinal, interval, ratio), the sampling frame, sample size, etc., to set the correct statistical test. Keep in mind that statistical tests such as ANOVA, ANCOVA, or MANOVA vary in data assumptions (e.g. one-way, two-way, three-way, etc.) as do Pearson or Spearman correlation, just to name a few. In addition, always go back to confirm accuracy of set up and analysis in SPSS and then reflect upon the interpretation of results to see if the results make sense. Execution is about following detailed actions specified in the research plan, analyzing data in-depth, and interpreting results accurately to answer the research questions.

In summary, disciplining your research focus involves details and it includes development of a research-worthy problem (Ellis & Levey, 2008). The process of vision, alignment, and execution (VAE) (Straw et al., 2013) can be useful to avoid scope creep and turn your research ideas into scholarship. If you have questions or want to share an idea for research, please contact me at lamigliore@email.phoenix.edu

References

Ellis, T.J. and Levy, Y. (2008). Framework of Problem-based research:  A guide for novice researchers on the development of a research-worthy problem.

Migliore, L.A. and Chinta, R. (2016). Mobile technology and the employee-customer-profit chain. SAM Advanced Management Journal 81(1), 52-69.

Straw, J., Scullard, M., Kukkonen, S., and Davis, B. (2013). The work of leaders:  How vision, alignment, and execution will change the way you lead. John Wiley & Sons, Inc.:  San Francisco, CA 

Comments

Erik Bean's picture Erik Bean | June 30, 2017 7:38 pm MST

Thank you for sharing this valuable short and extacting treatise on VAE. A paradigm such as VAE can potentially have seemingly many uses and application both inside academia and in the field. 

Christopher Hicks's picture Christopher Hicks | July 24, 2017 2:19 pm MST

Thank you for sharing your insights regarding VAE Dr. Migliore!

I found the advice about crafting vision statements very useful. I also appreciate how you used the operational definition of the independent variable to inform the research questions.