Treceți la conținutul principal


Systemic errors are considered as” Error that affects all items comprising a group (such as a production batch) in a similar manner and to a similar magnitude. Systemic errors are caused by a flaw in the system (such as in the calibration of a measuring device), occur in the same direction and, therefore, do not cancel each other out. Also called constant error or systematic error.[1]
On the other hand, systemic errors are leading towards systemic risk that is defined as” 1. General: Probability of loss or failure common to all members of a class or group or to an entire system. Erroneously also called systematic risk.
2. Investing and trading: Probability of loss common to all businesses and investment opportunities, and inherent in all dealings in a market. Also called market risk, it cannot be circumvented or eliminated by portfolio diversification but may be reduced by hedging. In stock markets, systemic risk is measured by beta-coefficient.”[2]
There should be made a difference between systemic and systematic.
Wikipedia is defining systematic errors as” ... biases in measurement which lead to the situation where the mean of many separate measurements differs significantly from the actual value of the measured attribute. All measurements are prone to systematic errors, often of several different types. Sources of systematic error may be imperfect calibration of measurement instruments (zero error); changes in the environment which interfere with the measurement process and sometimes imperfect methods of observation can be either zero error or percentage error. ”[3].
The action of systemic errors upon safety into an enterprise or a community or a larger social structure could be significant. Some common examples are regarding the reporting system- when in order to report an unexpected event (that could turn on into a nasty incident or even an accident) the organisational procedures are implying the follow up of a long chain till the problem is solves somehow or there are taken emergency measures. There is nothing wrong with a reporting procedure”per se”. The problem resides when this procedure is not taking into account the context of activity and is supposed to be implemented as it is, regardless of the specific conditions.
Another example of systemic error- on a larger scale- is the provision (adopted for example by the Romanian law) that work accidents should be declared only those with more than three days of hospitalizing or absence from the work. Other countries- like UK- under the RIDDOR reporting criteria [4] are reporting more than 10.000 injuries- Romania is reporting currently just no more than 6500 accidents/year.
As the systemic error is imposed- generally by the functioning management system- it is systematically omitted when auditing a system following the existing management rules.
As an example- we could consider the one from figure 1- where we have a management that is not very familiar with documenting (in writing) its procedures. So, there could be serious incidents and even accidents because the employees have no written safety procedures (other than the ones required by law), the machines and tools have no written maintenance procedures, there are no best practice procedures for doing a specific activity and finally- the products that are going to the client are poorly documented.

Figure 1 Example of systemic error propagation

The example (real) is not necessarily derived from malevolence- in the first moment the management was focused on reducing the paperwork, the employees were overqualified and do not need a lot of instructions and the tools and machines were new and the maintenance was assured by the supplier. As the business was developing and more complex products were added to the fabrication line there was a real problem with the absence of written documentation but at the employee level everyone was used with the empiric work procedures and nobody felled the need to write them down. When there were hired a lot of young and inexperienced workers in order to cover all the customers’ demands the system begun to function with problems and there were some unexpected events- resulting in material loss- because the new workers were pushed to the final assembly line without the documentation regarding the work procedures and also without the one regarding the usage of specific machines. As they were supervised by more experienced workers there was no problem- for a time- regarding their direct safety. From the top management till the last employee everybody was convinced that their approach was the best. Unfortunately an occupational accident occurred- having as the root cause the absence of written documentation regarding a complex work procedure-in which the forearm of a worker was perforated by a drill. The victim was very close of losing his forearm- as the emergency kit also has no written instructions regarding how to stop the bleeding using the components inside.
So- how to identify and prevent systemic errors? In this respect- a way would be to appeal to those that could be affected by these errors- in our example the employees and probably the customers.
Figure 2 is showing such a mechanism.

Figure 2 Systemic errors vs. sentiment analysis

Man is an animal of habit. Comfort- including comfort at work- is a continuous desire. Opinions regarding his state at work, his comfort and others are central to almost all human activities and are key influencers of our behaviours. Our beliefs and perceptions of reality, and the choices we make, are, to a considerable degree, conditioned upon how others see and evaluate the world. For this
Opinions and its related concepts such as sentiments, evaluations, attitudes, and emotions are the subjects of study of sentiment analysis and opinion mining. ” Sentiment analysis, also called opinion mining, is the field of study that analyses people’s opinions, sentiments, evaluations, appraisals, attitudes, and emotions towards entities such as products, services, organizations, individuals, issues, events, topics, and their attributes. It represents a large problem space. There are also many names and slightly different tasks, e.g., sentiment analysis, opinion mining, opinion extraction, sentiment mining, subjectivity analysis, affect analysis, emotion analysis, review mining, etc. However, they are now all under the umbrella of sentiment analysis or opinion mining.”[5]
Why would such an instrument be interesting for the assurance of safety and health?
1. Because it allows the processing of natural language. As told before the most occupational accidents have a primary cause the human factor. We could not quantify (at this moment) the human factor- but we could describe- in natural language- certain facts that are describing typical behaviours and we could identify- through this description- specific patterns that could turn into dangerous or even malevolent behaviour.
2. We could define in this analysis certain domains of interest and formulate specific queries that could search for peculiar aspects of behaviour that could look normal (like the work without printed work and safety procedures) for a specific workplace but could be decelated as peculiar in a certain mass of employees.
3. We could refine our analysis using referential for safety- defined also in natural language.
4. We could make our search- and analysis- for large numbers of employees. Maybe sentiment analysis would not be suitable (at actual costs) for 3 persons- but for an enterprise with 200 or more employees it could be interesting.
5. The opinions are anonimized- and the employees that are giving these opinions are protected expressing their opinion against unwanted consequences.
6. Employees are listened. The whole managerial process could be improved by taking into consideration the employee opinion- expressed in a certain time. A regular report- for example a semestrial one- could be asked so that the employee is expressing its opinions without consuming the management time- but they are actually heard and their opinions are valued.  

[5] Bing Liu 2012, Sentiment analysis and opinion mining


Postări populare de pe acest blog


Analiza cauzelor rădăcină este o metodă extrem de folosită de către managementul de performanță  din firmele dezvoltate. Metoda este considerată ca o metodă primară- care trebuie utilizată în primele faze ale analizei specifice procesului managerial. Ne propunem să prezentăm o metodă de analiză a cauzelor rădăcină care să poată fi aplicată atât pentru managementul calității cât și pentru managementul securității – ținând seama de faptul că în cea mai mare parte, cauzele rădăcină ale problemelor de calitate și problemelor de securitate și sănătate sunt comune. Figura 1 prezintă modul  global de analiză pentru cauzele rădăcină Din figură se poate observa că avem 2 procese distincte: ·         -un proces de identificare- care va fi realizat pe baza metodei cunoscute și ca 5 W ( 5 Why); ·         -un proces de analiză; procesul de analiză urmărește: o   stabilirea cauzelor specifice managementului calității și managementului de SSM; o   ierarhizarea cauzelor identificate;

Figura 1  Structurare…


KPI definitionA key performance indicator(KPI) is a measure of performance, commonly used to help an organization defineand evaluate how successful it is, typically in terms of making progress towards its long-term organizational goals.
–KPIs provide business-level context to security-generated data –KPIs answer the “so what?” question –Each additional KPI indicates a step forward in program maturity –None of these KPIs draw strictly from security data
COBITControl Objectives for Information and Related Technology (COBIT) is a framework created by ISACA for information technology (IT) management and IT governance. It is a supporting toolset that allows managers to bridge the gap between control requirements, technical issues and business risks. COBIT was first released in 1996; the current version, COBIT 5, was published in 2012. Its mission is “to research, develop, publish and promote an authoritative, up-to-date, international set of generally accepted information technology control obj…


Așa după cum s-a văzut dintr-o postare trecută, graful de risc poate fi un instrument util- și nu numai în cazul bolilor profesionale. Vom adapta în continuare  teoria existentă la teoria și practica din România și vom detalia câteva aspecte considerate de interes.
Este interesant de adaptat  graful de risc pornind de la clasicul sistem Om-Mașină folosit în practica de specialitate din domeniul SSM din România. În acest sens, folosind experiența existentă și datele statistice putem dezvolta în mod corespunzător- așa cum se prezintă în continuare în acest material.
Tabelul 1- Atribute folosite în graf Atribut Descriere I (Inițiatori) Operator(O): a. operator pregătit necorespunzător[1] b.operator malevolent [2] c.operator surprins de un eveniment neprevăzut datorat sarcinii[3] d. operator surprins de un eveniment neprevăzut datorat mașinii;[4] e. operator surprins de un eveniment neprevăzut datorat mediului/factorilor naturali. [5] Sarcină(S): a. sarcină incorect formulată- care dete…