How Important is Technology in Innovating the Industry?

Data transfer is a vital step in the data management process. From data collection to processing into a data file or a frequency report, forming handshakes between these processes is where technology can really add value.

 


How Important is Technology in Innovating the Industry?

How Important is Technology in Innovating the Industry?

26th September 2016 in   Market Research Articles by Andy Madeley


Data transfer is a vital step in the data management process. From data collection to processing into a data file or a frequency report, forming handshakes between these processes is where technology can really add value.

We have created our own toolkit and use the Triple-S data interchange format to optimize our scriptwriting activities. Our data processing scripts work with the software application Merlin from Merlinco. Global and local field agencies are likely more familiar with Quantum, QPS, Surveycraft or Dimensions. However, there is no real need for uniform software use. It is not the software used that is the key, but the data management practices the agencies employ.

How agencies use software appropriately and optimally to prevent unnecessary residual data loss is crucial. If a software application is Triple-S compliant, then the time saved due to automatic transfer of data from collection to analysis is immense. Very few local field agencies are aware of this simple and innovative way to transfer data from one application to another, but they should be. It reduces the burden on manual labor and archaic data processing activities, like building recode scripts to get the data from A to B, thus reducing likeliness of error and improving data quality along the way.

Currently, in 8 of 10 instances we ask a local field agency to deliver an SPSS data file. SPSS is recognized throughout the world and most, if not all global and local field agencies have access to this software application. There are some market research specific disadvantages associated with using SPSS, the main one being the way it handles a core market research variable type -- the multi categorical.

If we recommend to agencies that they deliver datasets in SPSS, the positive spinoff is that we obtain data and metadata. We have optimized our toolkit to read both (data and metadata) automatically and create a script that's 80% complete. We then only need to spend a relatively small amount of time adding some further script syntax.

The negative spinoff of using SPSS as the data transfer mode is that someone will have to write a recode script (normally in Quantum or Dimensions) to get the data into SPSS. This adds an unnecessary layer to the process, but most local field agencies are not aware of Triple-S or any other better methods other than tasking someone in the data processing department to write such a recode script. Where 15+ years ago the majority of SwissPeaks’ time was also spent manually setting up scripts, we now spend less time needing to do this and can deliver expedited data and frequency reports much easier.


 

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