6 Ways to Make Your Change Survey Measure Up
More than half of change efforts fail. So how do you make sure yours is on the winning side of that statistic?
By Jenna Neyman and Simon Warshal
People often rely on surveys to gather insights on how their change is going. Carly Fiorina, the former CEO of Hewlitt Packard once said, “The goal is to transform data into information, and information into insight.” If that’s the case, then it’s reasonable to assume the quality of our insights will be impacted by our ability to convert our data into information that tells a meaningful change story.
For those of us without an extensive background in data analytics, our ability to use our survey data is often constrained — or at least made significantly more cumbersome — by the format of that data. Here are six tips for survey design that will make it easier to derive better data and insights, inform decision-making, and tell your change story.
Tips for change survey design
Survey design is a robust field and the focus of entire collegiate and post-graduate curricula. The goal of this article is not to teach you the complete ins and outs of survey design. Rather, we hope to equip you with tips to optimize your survey output for easier conversion into a meaningful change story using data visualization tools.
1. Define your survey goals upfront
Think about the specific and targeted goals for your program and survey. Don’t ask everything just because you can — focus on critical asks. Consider:
- What is the story I want to tell with the output of this survey?
- What questions do I need answered?
- How am I planning to use or take action on the output?
Determine what you need to ask in order to answer those questions, tell that story, or inform decision-making. For example, don’t ask if people prefer in-person versus virtual training if you already know training will be virtual to accommodate multiple locations.
2. Think long-term
During a change effort or when managing a cyclical program, we can survey at multiple points in time to compare and monitor progress. Frame questions so they can be replicated and compared, 1:1, for longitudinal impact. For the best results and easiest data preparation, keep your questions and their response options 100% identical.
3. Code your questions upfront
It is important to label charts and graphs. It is equally important to make sure the whole label is visible. Long questions and response options may get cut off with a “…”, leaving your viewers unsure of what the visual is trying to tell them. Coding your questions makes data cleansing easier, enabling you map the code to a short, visual-friendly variable label.
For example, by putting a short label like “TTF_” in front of your question about knowing which tools are right for which tasks, you can more easily convert “TTF_” to “Knowing Tool-Task Fit.” Then, your visualization labels won’t get truncated by the dreaded ellipsis.
4. Use numeric response options instead of text response options
It is easier to measure numbers than words. Assigning a numeric value makes plotting graphically fast and easy. When response options are on a scale, like a Likert scale, swap your text options for numbers. Designing your survey to have numeric outputs will significantly reduce the amount of data cleansing and coding you’ll need to do to prepare your data set for easy use within a data visualization tool.
Be sure to also think about how you’ll account for “not applicable” responses and reverse coded items, if you have them.
5. Plan how you’ll slice your data
Aggregated data only tells one perspective of a story. A more accurate change story often comes to life when we look at different demographics of our respondents, filtering by level, team, tenure, role, region, etc.
By planning how you intend to slice your data, you can capture any necessary data points. Consider whether you can map respondents to organizational profile data behind the scenes or if respondents will need to disclose certain demographic information.
6. Decide where your data will live
The easier your data is to access, the easier you’ll be able to build and maintain your change story through data visualization tools. Consider building your survey so the data is automatically populated within an easily accessible output file that can serve as the source data for a data visualization tool. If you have multiple data sources, consider consolidating them into a single data file for ease of use and reference.
Next steps
At Slalom, we drive meaningful and fiercely human change with “change analytics” — the use of data to mobilize the value of change management toward achieving core business goals. Change analytics encourages you to explore a wide array of data sources and data points so you can measure and maximize your specific change goals.
Change isn’t easy. But by simplifying your data output with smart survey design, telling your change story can be. Learn how Slalom can support your change transformation and help you tell your data story.
Slalom is a global consulting firm that helps people and organizations dream bigger, move faster, and build better tomorrows for all. Learn more and reach out today.
