Soft data
Soft data ( English soft facts ) are data that strongly people - and / or depending on the situation and for different interpretations are accessible.
General
“Soft data”, like its counterpart “hard data”, is a plural tantum . As "hard data" such data are that defined with exactly possible quantified measurement methods as metrics are obtained and therefore by a high degree of inter-subjectivity distinguished. In the case of patients, for example, hard data are age , body weight , laboratory findings , while soft data are data on the patient's medical history, such as coughing or shortness of breath , which are highly dependent on the patient's judgment . A typical example from meteorology is the air temperature as hard data , which is offset by the perceived temperature as soft data .
Many decisions cannot be based exclusively on hard data, but require rounded off soft data. The assessment of the work motivation of a worker cannot be based on their absenteeism alone , because the proportion of low-motivated blue-collar workers in the total absenteeism is not known. This can only be determined through surveys .
species
Soft data are based on surveys , observations , assessments , attitudes , experience values , empirical knowledge , opinions , estimates , assumptions , surveys or evaluations . No decisions can be based on such soft data alone . Soft data are only used to round off hard data and can only be included in decisions together with the latter. For example, credit checks and ratings at banks and rating agencies mainly consist of hard data such as business and economic key figures and other company data; in addition, the qualifications of management (such as their fluctuation and leadership quality in the last five years) as well as identified weaknesses are included in a credit decision a. In the insurance sector , for example, a distinction is made between hard tariff factors in car insurance , which can be checked by the insurer when the contract is concluded , and soft tariff factors such as the annual traffic performance or the number of vehicle drivers .
Soft data in companies can be broken down as follows:
| Employee | Customers |
|---|---|
| Job satisfaction | Customer satisfaction |
| Labor intensity | Customer complaints |
| Sick leave | Complaints |
| Absenteeism | Customer loyalty |
| vacancies | Excess demand |
In order to objectify and quantify this soft data, an attempt must be made to evaluate it in monetary terms. Absenteeism leads to personnel costs that are not offset by work performance and possibly lead to overemployment and overtime for employees who have to take on these tasks.
In addition to the financial sector, the police and intelligence services also work with unsecured data in order to be able to make prognoses for future perpetrator behavior and to obtain suspicious facts about crimes that have already been committed .
Individual evidence
- ↑ Werner Fuchs-Heinritz / Rüdiger Lautmann / Otthein Rammstedt / Hanns Wienold (eds.), Lexikon zur Soziologie , 1994, p. 124 f.
- ↑ Lothar Sachs, Statistical Evaluation Methods , 1972, p. 166
- ↑ Hilmar J. Vollmuth, Key Figures , 2006, p. 40
- ↑ Hilmar J. Vollmuth, Key Figures , 2006, p. 41
- ↑ Wolfgang Gerke (Ed.), Gerke Börsen Lexikon , 2002, p. 489
- ↑ Stefan Pohl, main cancellation of due dates in motor insurance, 2009, pp. 47, 58 f.
- ↑ after Jack J. Phillips / Frank C. Schirmer, Return on Investment in Personnel Development , 2008, p. 107