Top 5 Reasons Your Analysis Isn’t Working — and It’s Delaying Your Dissertation Submission

You’ve collected your data, run some tests, maybe even drafted your results, yet something still isn’t clicking. Your analysis doesn’t make sense, the findings don’t match your expectations, and deadlines are creeping closer.

If this sounds familiar, you’re not alone. Many postgraduate students reach this stage and find themselves stuck, not because they aren’t capable, but because a few hidden factors are quietly sabotaging their progress.

Let’s unpack the five most common reasons your analysis isn’t working, and how they’re keeping you from submitting your dissertation or thesis on time.

In a quiet library, a postgraduate student surrounded by an array of open books appears overwhelmed, resting their head in their hand.

1. The Research Question and Data Don’t Align

Understanding the overarching question you are addressing in your analysis is crucial for interpreting your data effectively. Your research question guides your entire research life cycle, from how you review literature on your topic of interest, to what you analyse, and how you interpret your findings.

As you engage with more literature, your question should naturally evolve and become more focused. A refined, specific question helps you collect the right data and choose the right analysis approach.

Check out our earlier blog post where we detail how to formulate strong research questions.

It is important to note that exploratory research approaches, such as ethnography or grounded theory, may allow you to refine your question during data collection. However, even in these cases, it is strongly recommended to have an overarching research question to guide your direction.

2. You’re Unsure Which Analysis to Use

Many students apply tests or models they have seen online without considering whether those methods match their data. This delays submission because you get confusing results that are hard to interpret, and when you send your findings to your supervisor, you get sent back to the drawing board.

What to do instead:

• Classify the types of variables you are working with (ordinal, nominal, discrete, continuous ).

• Start with a descriptive statistical analysis to understand your data before applying tests.

• Choose your statistical test based on your research question, not just the software you’re comfortable with.

• Take time to understand the assumptions and conditions behind each test.

• Use a checklist to guide your test selection; this ensures consistency and clarity

3. You’re Cleaning Data Without a Strategy

Often, students rush to the analysis without checking whether their data is clean. Doing a descriptive analysis early on can reveal missing values, outliers, duplicates or inconsistencies that may compromise your results.

How to do this:

• Create a clear data cleaning plan before you begin analysis.

• Keep a record of every cleaning step you take; this will strengthen your methodology chapter.

• Automate repetitive cleaning tasks using R, Python, or Excel macros to save time and minimise errors.

Clean data equals credible results, and fewer headaches later when explaining your findings.

4. You’re Working in Isolation

Do not be afraid to ask for help. Many students struggle to ask for help because they fear appearing inexperienced. You need feedback to know that you are on the right track with your work. Sometimes, simply having a conversation and trying to identify the challenges you are facing can help you find solutions. Interact with others; research can often be a lonely journey at times.

How to tackle this:

• Don’t hesitate to ask for help from peers, mentors, or your supervisor.

• Share your analysis ideas early, even if they are incomplete.

• Find accountability partners or join postgraduate support groups.

• Seek consulting or mentoring (for instance, through Nova Data Analytics sessions)

A simple conversation can often lead to breakthroughs that weeks of solo struggle cannot.

5. You’re Mentally Exhausted

After months or even years of effort, it’s normal to feel drained.

You may find yourself anxious, second-guessing your abilities, or losing motivation. Sleepless nights and constant overthinking become part of your daily routine.

Unfortunately, exhaustion leads to procrastination, not because you are lazy, but because your brain is overwhelmed.

How to fix this:

• Break your tasks into small, achievable goals

• Use structured work methods like the Pomodoro technique to maintain focus.

• Rest intentionally - take real breaks for recharge.

• Remember: finishing is about sustainability, not perfection.

Conclusion

Every postgraduate student encounters obstacles during their research journey.

When your analysis isn’t working, it’s often not about your ability; it’s about clarity, structure, and mental balance.

Take a step back, identify which of these five areas might be holding you up, and address it with a plan.

Progress comes from consistency, not perfection.

At Nova Data Analytics, we support students in transforming analysis challenges into clear, confident results, helping you move from stuck to submitted.

Further Reading

If you’d like to explore some of the concepts discussed in this post in more depth, the following resources offer valuable guidance for postgraduate students:

1. Saunders, M., Lewis, P., & Thornhill, A. (2019). Research Methods for Business Students (8th ed.). Pearson Education.

   A comprehensive guide that explains how to design research questions, choose appropriate methodologies, and conduct valid analyses. Particularly useful for understanding the alignment between research objectives, data collection, and analysis.

2. Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.

   A foundational text for structuring research projects and choosing the right analytical approach. Highly recommended for students refining their research design or exploring mixed methods.

3. Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE Publications.

   Ideal for those using SPSS, this book simplifies complex statistical concepts with humour and clarity, helping students understand when and how to apply different tests.

4. Bryman, A. (2016). Social Research Methods (5th ed.). Oxford University Press.

   Offers deep insights into the principles of research design, data collection, and analysis, especially for students working on social or behavioural research.