Shifting Perspective Part III: Putting Qualitative Data To Work
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You’ve put in the work to understand what each chess piece does. Hours of study have given you a full understanding of the strategy and skill involved in the game. All that’s left to do is play.
In the world of business and chess, understanding why things like qualitative data and ideas are important is only the beginning. Now you need to mobilize your team toward actually using them. This includes effectively collecting, analyzing, and using your customers’ and employees’ ideas as data points.
Previously in our Shifting Perspective series, we’ve explained what qualitative data is and why you should be treating ideas the same way you do data. We’ve also looked at how important data maturity is to a healthy, innovative corporate culture.
Today we’re going to get down to the brass tacks of how to use qualitative data in your day-to-day and big-picture operations.
Challenges of Qualitative Data
For a company that has only worked with quantitative data thus far, the process of including qualitative data in the decision-making process can be difficult. This kind of information can have multiple interpretations and often has no clear utilization.
When collecting ideas, businesses will need to develop a clear way to differentiate the useful from the absurd. We’re not suggesting that any data points be thrown out altogether; you never know what they might spark or morph into. However, it's important to hone in on what is feasible and practical.
Other challenges of working with qualitative data can include:
Having a large amount of data points to sort through and make sense of
Drawing meaningful conclusions from seemingly unrelated pieces of information
Making sure that the qualitative data aligns with your business goals and objectives.
Let’s take a look at what you can do to tackle these issues head-on in every stage of the data lifecycle. It will be quite similar to the lifecycle of any other data, with a few key differences in creation and processing.
Stage One: Creation
Since Qualitative data is so unique compared to more traditional forms of information, the process you go through to collect it is vital to its usability.
Tip One: Know What You Want
If you’re going to be using this information to drive innovation within your company, you need to have a clearly defined goal. Decide before a focus group, brainstorming session, or meeting what questions you want to address, what’s been explored in the past, and how this question will contribute to your overall innovation strategy.
Tip Two: Pick the Best Data Collection Method For Your Goal
There are countless ways to collect quantitative data, and which one you choose will depend on what you’re hoping to achieve. If you’re hoping to get your team involved in the innovation process, choosing a data collection method like Stormboard that is interactive, visual, and easy to use will be key.
On the other hand, if you want to get information from customers to jumpstart user-driven innovation, you may consider focus groups or one on one interviews. These, too, can benefit from a collaborative whiteboard to collect any ideas and key information.
Tip Three: Get More Eyes On It
Because this data can be so subjective, it can be helpful to have multiple people involved in any interviews or meetings you plan. This allows you to work together to organize the data collection, as well as have more filters to catch anything that might be useful later on.
Stage Two: Storage
As you shift to seeing ideas as data that can be used the same way as other forms of data, you’ll realize how truly valuable they are. Wherever you store this information, it will need to be secure to prevent any of it from falling into the wrong hands.
Stormboard provides the most up-to-date security on the market, so you can trust that any ideas generated during a storm will stay just between you and your team.
Stage Three: Processing
In the same way that qualitative data can take many forms, the way you analyze it can look like a lot of different things. Let’s break down a few of the most effective ways to process your data.
Narrative Analysis
Stories help us communicate how we see the world and what’s important to us. Using narrative analysis allows you to get personal with your customer base and hear why they think the things they do. This process sees subjects as whole people, as opposed to separating their information into its base components.
Narrative analysis works best with small focus groups and companies that are looking to build strong brand loyalty. It takes time and effort, but depending on what you want, it can be a powerful tool.
Discourse Analysis
Discourse analysis is a type of qualitative research that looks at the way people use language and the context behind those conversations. It’s especially useful for companies looking to get ahead of potential customer service issues, like complaints or misunderstandings.
You can use discourse analysis to identify patterns in conversation and responses, allowing you to anticipate problems before they happen. This process also helps you understand how customers talk about your brand and products — information that can be invaluable when crafting advertising campaigns or new initiatives.
Thematic Analysis
Thematic analysis looks for patterns and commonalities in your data. It’s a great way to get an overarching understanding of the general sentiments expressed by many people on the same subject.
This kind of process is ideal for companies with large customer bases which are looking to gain insights into trends or opinions at scale.
Pro Tip: Stormboard’s unique Idea Grouping feature is an excellent method to identify and connect themes, concepts, and patterns.
Grounded Theory (GT)
GT is an inductive approach to research that works by analyzing your data from the ground up. You start with raw data, then look for patterns and themes within it. Once you’ve determined what those are, you can use them to develop more specific hypotheses that fit into a larger theory of the subject at hand.
When dealing with complex topics or large amounts of qualitative data, GT is ideal since it helps uncover trends and commonalities people might not have noticed before. It also requires less prior knowledge than narrative analysis does – which makes it great for fast-paced companies that need results quickly.
Stage Four: Archiving
Ideas evolve at an even faster rate than other forms of data. That’s why it’s vital that even as your qualitative data is archived, it’s readily available should you need to access it again.
With its cloud integration and Amazon Web Services hosting, you can rest assured that anything created in Stormboard is secure and accessible. All it takes to reference past data and ideas is re-downloading it from the cloud.
Stage Six: Destruction
In the same way that quantitative data runs its course, qualitative data will eventually become outdated. When this happens, it must be properly disposed of so that those valuable ideas don’t end up being used maliciously.
Remember: this data is just as important as personal information or sales forecasting. It should be treated with the same respect and diligence.
The Bottom Line
By now, you can see how powerful qualitative data can be in shaping the future of your company. Using it to its full potential requires companies to shift their thinking around data as a whole.
As they make this shift, businesses must be prepared to treat ideas the same as they would quantitative data points. This includes focusing on security, operationalizing them, storing and managing ideas, and viewing them on an evolving spectrum throughout their lifecycle.
Just like a chess master protects their tricks and strategies, you need to be in full control of where your qualitative data is and how it’s used. By leveraging these ideas, your company can get on the fast track to leading your industry with innovation and data-driven agility.
Get in touch with one of our experts today and get a first-hand look at how your business can shift perspective and find new value in the data you’re already producing every day.
About the author:
A programmer by trade, Nick Saraev is a freelance writer and entrepreneur with a penchant for helping people excel in their careers. He's been featured on Popular Mechanics & Apple News, and has founded several successful companies in e-commerce, marketing, and artificial intelligence. When he's not working on his latest project, you can find him hiking or painting.
