Let s assume that you ve already performed the fundamental steps of creating a survey. You ve determined your purpose for the survey and designed the questions to encourage the right type of data. You ve implemented your survey and have received an ample amount of information from the survey participants. Your next step is the analyze the data. This may not be a straightforward task. Analyzing and interpreting survey data requires as much diligence and strategy as the design process. Below, we ll discuss your priorities in collecting the data as well as the steps of analysis involved in interpreting it.
Priorities Of Data Collection
Your survey will likely be divided into several sections (each with its own singular purpose). Each section of your survey will have a different priority assigned to it. This is natural because some types of data are more important for taking immediate action than other types. The key is to determine your order of priority before structuring your survey. If a particular section of your survey is more critical than other sections, place it first. It s not uncommon for participants to rush through the last couple of sections of a survey simply to finish it. Prioritize your sections and structure your survey accordingly.
Broad Level Review
This is a step that many people neglect. But, it s a valuable way to identify signs that the data collected may not be representative of your participant pool. For example, let s assume that you re surveying your employees about their thoughts regarding training opportunities within your organization. It s possible that employees in different departments will feel differently. Those who are in the finance and accounting department may not feel the need for ongoing training while those in the IT department may feel a great need for it.
A broad level manual review of the information collected from your survey can provide you with a sense of whether the data is accurate. This review can also shed light on shortcomings of your survey process (distribution, presentation, invitations, etc.).
Data Cleaning
Cleaning your survey results is an important step before true analysis can begin. By discarding responses that are incomplete, you can refine the data. For example, let s assume you asked your employees a 2 part question involving their need for additional training opportunities and the challenges they feel in their positions. If some employees only answer 1 of the 2 parts, those results lose significant value. As such, those partial results should be discarded to clean the data pool.
Analyzing In Detail
Your primary goal in conducting detailed analysis should be transforming the survey data into information on which you can take action. Sometimes, this can mean studying trends and baselines using graphs. Other times, you may need to use software to mathematically calculate responses. Tabulations, filters and intense statistical analysis may be necessary given your objectives. Most organizations can extract the information they need to take action on survey results by applying low level analytical procedures.
Taking Action On The Data
The entire process of creating a survey, implementing it, collecting the resulting data and analyzing that data culminates in taking action. If your survey has been designed specifically to provide the data your organization needs, you should be able to easily plan a course of action to leverage that data. This is the end goal of a survey. Each step in analyzing the data leads to taking action. From broad level review to data cleaning and detailed analysis, your ability to put that data to actionable use will determine your survey s value.
Author Resource:-
SurveyGizmo is a leading provider of online survey tools, check them out on the web at http://www.surveygizmo.com
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