Survey Data Analysis – How To Get More Insight

Philip Cleave
March 23, 2016

Survey data analysis can help give you a better understanding of the decisions your customers make and increase the success of long-term business planning. By delving deeper into the data you collect via questionnaires you can gain better insight, which in turn will lead to better decision making.

Benefits of Survey Data Analysis

Okay, you’ve collected your questionnaires and looked at the replies. Interesting, you have done a great job getting targeted responses and this gets you thinking:

  • Is there more to be found in the data?
  • Is there a different way of looking at it?
  • Is there a deeper insight?

Wouldn’t it be great if you could achieve further survey data analysis and really get the most out of your results! Ask yourself, what if you could…

  1. Restructure the data after the results have been collected.
    • Maybe rationalize a free response question about shopping preferences by using just a few basic categories.
    • Merge under-used response options in a question about income.
  2. Combine questions to produce a single reliable scale.
    • Perhaps create a robust customer satisfaction index from a set of separate questions.
    • Put together a driver compliance scale based on attitude to traffic laws.
  3. Explore how responses to different questions are related.
    • Is salary more important than working conditions for retaining employees?
    • How is consumer spending affected by optimism about the future?
  4. Find out if there is a real and meaningful difference between particular groups.
    • Are different types of commuter more frustrated by their journey to work?
    • Do some hotels provide a better guest experience than others?
  5. Filter particular groups from an analysis.
    • Perhaps exclude people aged over 60 from an analysis of attitudes to house buying.
    • Filter infrequent drivers from an analysis of views about toll road charges.

There are many different ways to get more from survey data analysis. You may simply want to restructure a couple of the questions or explore the results in a slightly different way. Alternatively, you may have specific business issues you want to understand better through the rigor of statistics. Maybe you just want a little guidance on survey design, the analysis or help with managing the data.

Whatever your need, our experienced Chartered Psychologists can provide as much or as little support as you require to help you get the most out of your data. You’ve invested in getting the survey out there so why not get the most out of it?

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Read this case study to see how deeper analysis of data can benefit you:

Case Study: Employee Wellbeing

Wellbeing is clearly important for the individual but it can also impact on performance at work.

Our client was a large public sector organization with an interest in increasing employee wellbeing. Over 2,000 respondents completed wellbeing surveys from staff at different sites across the country. The surveys were comprehensive and each comprised of over 250 different responses, giving more than 500,000 data points from which to work!

The survey covered three broad topics:

  • Health and home life
  • Work life
  • How the organization could support staff and improve wellbeing

We were asked to analyze the data and present a formal report of results.

The first important step of the process was preparation. As part of this, we tidied up the free response questions, dealt with missing data and restructured some of the questions. For example, nine staff grade categories were reduced to just three broad groups:

  1. Officer grades
  2. Middle management
  3. Senior management

We created a sample profile using a range of demographic variables such as age, grade, organizational site and work role. Drawing on this profile we then checked the representativeness of participants.

Guided by the health literature, we produced two psychometrically robust scales. These were a ‘wellbeing’ scale and a shorter ‘stress symptom’ scale. The wellbeing scale turned out to be a particularly useful measure and a key part of the later analyzes.

Some of our analyzes were simply descriptive. For example, we provided statistics, graphs and tables showing the amount of exercise undertaken by employees, attitudes to alcohol & smoking, views on the workplace and awareness of support services. Here are some examples.

  • Temperature, air quality and noise were the physical features of the workplace perceived to have the most impact on wellbeing
  • A quarter of respondents would like guidelines on nutrition and healthy eating
  • Getting the right work life balance was the area where most wanted support
  • On-site training sessions, demonstrations and events were perceived as the best way to get messages across about health and wellbeing

Key results were benchmarked against national standards. For example, after filtering younger respondents ineligible for the NHS health check, we compared employee use of this service with the national figure. In fact, take-up rates by staff were lower than the national average.

We also delved deeper into the data and used a range of more sophisticated statistical analyzes. Here are three of the analyzes that gave statistically significant results.

  1. Scores on the wellbeing scale were correlated with self-reported health and exercise. Clearly, better health and more exercise are linked with higher levels of wellbeing.
  2. Respondents were asked first about their involvement in voluntary/charity work, and secondly, their participation in the community. Based on an analysis of variance, employees involved in both types of activity had the highest mean wellbeing scores whereas those who took part in neither had the lowest.
  3. The three grade groups were cross-tabulated with hours worked and evaluated using a chi-square analysis. Higher grades in contrast to lower grades generally worked significantly more hours than their employment contract required.

Many other analyzes were undertaken as the data was explored, resulting in the following outcome: A solid and defensible foundation for implementing targeted wellbeing initiatives across the organization.

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