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PULSE
SURVEYS

dk•analytics is an online application which allows to deploy surveys in a “pulse” fashion. It can be used to assess key aspects of the organisational culture and the levels of employee engagement. 

 

Our tool can be used for any kind of pulse survey. Currently, our Clients have the following surveys

at their disposal:

 

  • engagement survey

  • innovation survey 

  • client centricity survey

  • digitalisation syrvey

  • survey on working in times of the Covid-19 pandemic

Unlike traditional surveys, dk•analytics allows

a constant two-way communication with the polled employees. This allows management to react quickly to problems which might arise.

dk•analytics features an analytics panel - the principal tool of a survey’s sponsor or administrator (this can be top management or/and HR). Survey results are presented in real time - with all aspects of the poll readily accessible. They can be analysed using filters - by aspect, group of respondents (which can include function, location, work level, etc.) and chosen question. 

The tool assures that respondents have complete anonymity - all survey questions are answered anonymously and the input data are anonymised

at database level. In order to view filtered results,

a minimal number of answers is required.

 

Key features of our application include:

 

  • Custom questionnaires

  • Cyclical and constant surveys

  • Custom frequency for sending questions

  • Each question sent separately according to a chosen frequency

  • Constant access to incoming results, plus analytics and filters

  • Ad-hoc questions can be sent to chosen respondent groups during the survey

 

The results are available in the panel and include:

  • Aggregate result 

  • Results for key aspects

  • Change of the results from previous to current cycle

 

The panel provides filtering by:

 

  • time frame

  • function, location, job and/or other criteria defined by the sponsor/admin

  • key aspects

  • any question of the questionnaire

 Filters can be combined, which results in a far going granulation of data.

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