Error culture in companies: Automatic data analysis



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Text comes from: Die Macht der versteckten Signale: Wortwahl - Körpersprache - Emotionen. Nonverbale Widerstände erkennen und überwinden (2014) from Dr. Gabriele Cerwinka, Gabriele Schranz, published by Linde Verlag, Reprints by friendly permission of the publisher.
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Of course, in addition to the error message systems "operated" by humans, all automatic error reporting systems are also part of the error culture of a company.

Error culture in companies: Automatic data analysis Fehlererkultur010

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Here writes for you: Dr. Gabriele Cerwinka is a shareholder of Schranz and Cerwinka OEG. Profile
Here writes for you: Gabriele Schranz is a shareholder of Schranz and Cerwinka OEG; Vienna - Zurich. Profile

Anonymous error message system

Overview

The most efficient is a system in which errors can be entered anonymously and unassignable. For example, the error message for airlines is anonymous (see chapter 6), only the route is announced, but not the date and the flight number.

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In this way even the smallest incidents are reported, without fear of consequences and without the danger of harming a colleague.

The more anonymous, the better

Overview

Anonymity is not possible everywhere. In some processes, reported errors can easily be assigned to persons.

Trotzdem sollte auf größtmögliche Anonymität geachtet werden. Zumindest sollte es auch die Möglichkeit einer zusätzlichen anonymen Fehlermeldung im Unternehmen geben.

Systematic detection of all errors

Overview

The basic question a company must ask is how to detect errors. To clarify:

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  • Which instruments, such as forms and computer systems, are used?
  • How extensively should the errors be described?
  • How are the errors categorized?

A standardized messaging system

Overview

The introduction of a standardized error message system is the most important basis and thus the most important instrument of a positive error culture.

The difficulty lies in the time-saving handling of often time-consuming reporting instruments, which are perceived by the parties as too complex and therefore impractical.

Simple standards

Overview

Clear standards such as an input mask, on which date, time, exact description of the error, possible causes and measures taken so far, as well as possible suggestions for improvement are recorded.

Above all, proposals for an improvement of the situation are to be recorded immediately in connection with the error message, since the directly affected employee is currently dealing with the topic and is thus required to deal constructively with the recognition of the error.

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Examples of automatic capture

Overview

Examples of this are the Toyota Production System (TPS): Andon, an optical production information system that reports the occurrence of a machine error by means of light signs on a display panel, or Jidoka, a self-controlling fault detection system that detects errors and controls or stops machines via sensors.

Good examples of central reporting systems are CIRS (CIRS Medical in Austria or CIRSNET in Switzerland or ASRS in aviation), in which the entered errors of all participating institutions are recorded, processed and made accessible.

Evaluation of detected errors

Overview

If all errors and near-errors are reported, an enormous amount of data is generated. These are now systematically prepared and evaluated.

This evaluation should be carried out as centrally as possible in order to be able to filter all available data into meaningful findings.

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Subsequent anonymisation

Overview

Important is the subsequent anonymisation, where this is still necessary. Categorization of errors: When evaluating, it is helpful to distinguish the reported errors and events and to assign them to similar categories.

So können Häufigkeiten ermittelt und Gefahrenquellen bewertet werden. Daraus erfolgen oft auch Fehlerlisten, die als Grundlage zur Fehlererhebung dienen können. Der Mitarbeiter muss lediglich den schon in der Liste befindlichen Fehler ankreuzen. Dies macht vor allem bei Produktionsprozessen Sense.

Classification into personal or subject-related errors

Overview

A decisive categorization is the assignment of whether an error has arisen directly as a result of a human error or whether there are factual reasons and causes.

This distinction is fundamental for an accurate determination of the cause.

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Classification into external and internal errors

Overview

Are factors that are outside of the company, involved in the development of the error, the division into external and internal errors also provides a valuable and notwenige help in uncovering the causes and resolve the source of error.

With the help of the new networking opportunities with the corporate outside world, new instruments of a culture of error are being developed that are based on even more transparency and openness.

Open Source Model

Overview

As an example we would like to introduce you to the open-source model: the users of a system, ie the customers, contribute to the improvement of a product. They provide data and suggestions that feed into product development.

This leads to an open exchange about undesirable developments. All - companies and customers - are interested in an ongoing improvement.

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The customer is involved

Overview

They trust each other, the provider makes the customer feel like they are sitting in the same boat and are involved in the product development.

So the customer is not just a consumer, but also a participant. This model is mainly found in software development.


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