Tools for Data Collection
Sensory testing, whether it is Descriptive, Discrimination or Preference/Acceptance, generates data. Depending on the type of test being used, the volume of data can be daunting. Manual data collection and analysis is a very straight-forward process but it has its drawbacks, including increased chance for mistakes, which can lead the researcher down the wrong path.
There are many inherent disadvantages to manually generated data.
- Time. When large numbers of respondents are involved in a study, it takes time to transcribe these numbers into a format in which it can be analyzed.
- Accuracy. Since filling out a paper questionnaire is done by the study participant with no interaction with the test administrator, mistakes and omissions can occur, skewing results.
- Participants handwriting may be difficult to decipher… Is that a 3, or a 5?
- If the data has to be entered into a spread sheet there is always a chance of mistakes being made by the person entering the data.
- All of the above factors lead to the key disadvantages–increased test cost and unreliable data.
The ideal tool for collecting and analyzing data should minimize the handling of the data. An electronic method which guides the study participant in inputting their response to questions, records the responses, analyzes the data and reports the results is the ultimate system.
Sensory software systems which provide these functions also assist the sensory professional in planning and setting up a study by providing:
- questionnaire development with flexible design options
- experimental design capabilities
- automatically-generated codes and labels
- panelist performance tracking
- data analysis and graphing capabilities
Some of the Sensory software systems available include TasteBOSS, Compusense Five, SIMS Sensory, FIZZ Biosystemes and RedJade.
Another option for utilizing this type of software if you do not have a system of your own is to employ an internet cloud sensory testing software service.
Next month, Sensory Bytes will explore measuring responses for Acceptance/Preference testing.