Top 5 reasons to use NVivo


Lyn LaveryI’m often asked if software such as NVivo should be used for qualitative data analysis. For me this is an easy choice, as I’ve used what I’ll refer to as ‘pen and paper’ methods previously, and wouldn’t want to return to them. However, there are some who would disagree with me.

Arguments against the use of software include the idea that CAQDAS distances you from the data or that it is simply a code and retrieve tool. I definitely disagree with this, and if anything, I believe it gets you closer to your data because it automates the clerical/administrative side of things for you, leaving you more time to come up with insights. There’s also the argument that it’s only suitable for certain methodologies. Depending on the software you use, this is usually not the case. Software such as NVivo can be used for any qualitative methodology you may choose to follow.

So, what do I say when people ask about using qualitative data analysis software? Here are my top five reasons for using NVivo:

  1. NVivo provides an organised and structured approach to analysis: Regardless of the methodology adopted, I believe a systematic approach is important to ensure that qualitative data analysis is undertaken in a rigorous manner. NVivo provides a good structure for this – I can keep track of (and review) transcripts as I import them into my project, see how far I have progressed with my coding, and make notes of emerging ideas (via memos) as I code.
  2. Everything is stored in one place: I’m the type of person who writes notes on random bits of paper (which aren’t always filed away neatly). I love the fact that when I set up an NVivo project, everything is imported or created in one database, allowing easy access to all my information when needed. It also means that the file can be easily backed up and is portable.
  3. NVivo enables you to work effectively with different types of qualitative data: When I’m undertaking mixed methods research – or even just a basic qualitative study with a literature review component, I find it extremely helpful that I can analyse across different data formats utilising the same thematic (node) structure. For example, I can import journal articles and other PDFs, and compare what my participants reported with the existing literature on the topic. Alternatively, I may have undertaken a survey with a couple of open-ended questions – being able to import an Excel file containing this data means that I can code it alongside transcripts from my semi-structured interviews.
  4. NVivo makes sub-group analysis easier: While marking up themes with highlighter pens on paper copies of transcripts can still be useful, imagine trying to look at this information across a large number of participants, while also exploring responses by different sub-groups within your sample (e.g., comparing what males and females said). NVivo has some fantastic features such as matrix coding queries that allow you to easily do this.
  5. NVivo helps you be a more efficient researcher: This is really an outcome of the four points listed above – when used effectively, NVivo can save you time during both the analysis and write-up phase. You can extract information across selected criteria with the push of a few buttons, and when you are drafting your thesis or report, there’s the capacity to easily insert verbatim text directly from your NVivo project.

It’s worth pointing out that there are other software possibilities, such as Dedoose, ATLAS.ti, MAXQDA and QDAMiner. NVivo is our preference, but don’t take our word for it – visit the CAQDAS Networking Project for further information about what’s available. If you decide to learn more about NVivo, we have a free webinar Is NVivo for You? A Brief Tour where you can see it in action, and we also run introductory NVivo training if you’d like some hands-on experience with the software.