Automated systems of normative and methodical management of enterprises and organizations
The automated system of normative and methodological management support (ASNMOU) by the enterprise (organization) should contain normative-legal, normative-methodical, normative-technical and organizational-administrative documents (NAP, NMD, NTD and RDD) that ensure the implementation of the adopted project and managerial decisions in the process of functioning of the enterprise (organization).
An example of the structure of SNOMA and ASNMOU, corresponding to the main functions that SNOMO should perform, is shown in Fig. 7.1.
As a methodical basis for the creation of ASNMOU, the idea of a stratified representation of the information retrieval procedure is used, with a deepening of the analysis of documents contained in ASNMOU by each stratum, by structuring their texts (Figure 7.2):
- on the top stratum - search for documents by management functions;
- the second from the top - search for sections of documents in accordance with the user's request, the relationship between sections of related documents;
- on the third stratum - output texts to the display or printer (full text or its sections);
- on the fourth stratum (which is not implemented for all documents) - analytical-synthetic processing (ASO) of document texts (which, for example, is required when searching information in the texts of laws and other NAPs).
The types of databases are determined by the specifics of a particular enterprise (organization).
Figure 7. 1. The structures of SNOMA and ASNMOU
Fig. 7.2. Structuring of texts contained in ASNMOU
For example, a database can be distinguished in this way: create a database of NAPs (national, regional), a database on NMD, NTD and RDD of the sectoral management bodies and the enterprise. For the ASNMOU of an enterprise it may be expedient to create separate STP bases, job descriptions, regulations on units, etc. Databases for large enterprises and organizations have a significant volume, so to organize effective procedures for searching and updating information, they need to be structured. Investigation of the features of the ASNMO database and work with them has shown that it is practically impossible to choose the most expedient rigid structure of the database because, on the one hand, the enterprise units participate in the performance of several integrated management functions, and on the other hand, the same function is performed by several divisions .
Databases for large enterprises and organizations have a significant volume. To organize effective procedures for searching and updating information, they need to be structured. Investigation of the peculiarities of the ASNMO database and work with them has shown that it is practically impossible to choose the most expedient rigid DB structure, since, on the one hand, the enterprise subdivisions participate in the performance of several integrated management functions, and on the other, the same function is performed by several divisions .
In addition, it should be borne in mind that the same function can be regulated in documents of different types - in the provisions on units, and in STPs, and in the ORD, etc. However, the same or similar with varying degrees of detail and with slightly modified formulations, the functions in different documents are coded in different ways, according to the grouping and indexing of the functions taken by the authors to develop the document.
In order to combine all the documents of ASNMOU into a single system and realize the idea of stratified deepening of the analysis of their texts, a single information retrieval language (IPN) is needed, with which it is possible to describe the names and contents of documents, which will allow them to be compared and search by requests, also translated into this language.
Such language can be implemented in the form of a classification system and coding of the facet type, the basis of which is the classifier of goals (main directions) and functions of the control system.
A study of the experience of practical implementation of the IPS (including all its elements - IPN, indexing system, choice of CSS), using the traditional approach to the development of the IPY, based on the use of natural language terms as its dictionary, has shown that usually the development of such IPY and IPS in general, requires at least three to five years. Further, a fairly long period of verification of the IPY and IPS is also required from the point of view of relevance and persistence criteria. For such a long period in the management system, significant changes can occur and the process of adjusting the IPY will again take time and significant work of developers. It is practically impossible to borrow the IPY, we can only talk about borrowing the structure of the thesaurus, the principles of the indexing system, the types of KSS. As a result, well-known developments in the field of creating a document-facto IPS for scientific and technical information systems are poorly implemented in the practice of automating the management of enterprises and organizations.
With this in mind, the classification and information coding system (SCCI) of the facet type has been developed as an information retrieval language linking all levels of ASNMOU, the main component of the facet formula is the classifier of goals and functions of the enterprise management system.
The choice of classification of the facet type allows the use of different types of classification for different facets: part - the components of the facet formula (including the named main component) uses a hierarchical classification, part - order, serial (classifiers subdivisions, document types), part - mixed ( adopted during the indexing of the ORD, PPP in a particular organization). The advantage of facet classification is also the possibility of changing the facet formula (composition and order of location of facets), taking into account the specifics of a particular enterprise, organization while maintaining the general principles of developing ASNMOU and SKKI.
The proposed system of classification and coding of information in ASNMOU allows you to structure databases on a request by various criteria: by functions (the classifier of goals and functions of the enterprise's CMS), by types of documents, by departments, etc.
The structures of records in the ADIFS database created for the PDP, NMD, PDD of various types may be different, but in each of them, fields (and corresponding facets in the classifier) must necessarily be provided for the indexes of the functions of the enterprise's classifier of goals and functions.
Experimental studies have shown that it is most convenient to use the three-level structure of the FT, i.e. for these indices, it is expedient to allocate three fields. Then the corresponding facet must also contain three fields and for indexes of the function classifier within the document (taking into account the format and peculiarities of indexing documents of a specific type), which provides the interrelations between all documents, i.e. unifying them into a single system.
In accordance with the idea of stratification, it is necessary to create conjugate databases for different strata. Using the terminology of STI theory, it is convenient not to talk about creating databases for different strata, but about creating two-, three- or more contour ADIFS.
In particular, when creating a DB of normative legal documents, two variants of ADIFS were investigated: a two-contour one - with the search for documents in the first circuit and extraction of sections from them (which contain information about legal norms or production standards representing ) in the second; three-contour with the search in the contours sequentially in the first - documents, in the second - sections and in the third - the articles (containing even more concrete factual information about the legal norms or specifications).
In the same way, databases of normative and methodological documents can be organized.
For example, when creating ADIFS provisions for business units or databases, the following contours can be formed: 1) the selection of provisions or other NMD, NTD, ORD, corresponding to the request, i.e. structuring for a request (for example, by enlarged functions, by groups of units); 2) search in the database of the selected documents on the user's request for information about the functions, terms and methods of their implementation, and similar factual information (searches may be carried out according to the characteristics provided for the development of ADIFS); 3) output of fragments of documents selected in accordance with requests in the second loop, to a display or printer in a user-friendly form (for example, sections of positions containing necessary information about functions, terms of their execution, performers, in the form of a table, etc.). ).
An example of a three-loop ADIFS normative-methodical documents of ASNMOU (regulations on organizational structure of the enterprise) is shown in Fig. 7.3.
The database structures in this example have the following form (the facet classification is adopted in this example).
The structure of the first outline of the OBD provisions on divisions:
where N1 - the number of the department in the existing SNOMO; N2 - the name of the department; F1, F2, F3 are the indices of the aggregated function in the structure of the company's objectives and functions, the implementation of which is regulated in the position.
Fig. 7.3. Structure of the three-contour ADIFS normative-methodical documents of ASNMOU
The database structure of the Interconnection provisions on the subdivisions of the enterprise (the second circuit AD FIPS), the components of which are the functions of position:
пто = & lt; FI, F2, F3, NI, DI, FJ, DK, NP>,
where Fi, F2, F3 are the indices of the aggregated function in the structure of the company's goals and functions, the implementation of which governs the document being prepared; N1 - the number of the producer of the document in the existing SNOMO; DI - the name of the type of the source document (or a particular document) for which the function is being prepared; FJ is the index of the function inside the position; DK - the index of the document received as a result of the function; NP is the number of the department to which the document is sent for further processing (agreement). Search of the factographic information in this circuit can be carried out by any parameter.
The third path is the output of the corresponding selected texts.
In the above example, ADIFS also provides a block for the formation and analysis of organizational and technological procedures (OTP) for the preparation and implementation of management decisions, based on the formation and analysis of which it is possible to clarify the structure of ADFIs.
Accordingly, for the database - regulatory documents.
The structure of the NAP DB of the first circuit can be represented as follows:
npd = T , D, M , F1 , F2, F3, IF>,
where N - the document number in the NAP DB; T - type of document (law, resolution, etc.); D - the name of the document; M - the place of publication or storage of the document; Fi, F2, F3 - index of the aggregated function, regulated by the document; IF - is the name of the file in which the document text (or text fragments) is stored.
The structure of the NDB DB of the second circuit will look like:
npd = , F2, F3, F4, F5, F6, IFR>,
where N - the document number in the NAP DB; D - the name of the document (law, resolution, etc.); R - the name of the section of the document; Fi, F2, F3, F4, F5, F6 - the index of the function, governed by the section; IFR is the name of the file that contains the section of the document text.
If necessary, a contour can be formed for NAP articles or an analytic-synthetic information processing circuit.
To accelerate the development of ASNMOU for specific enterprises and organizations, systems for its generation by ADFIs are being developed, with examples of which can be found in 11, 191.
The above examples of DIPS refer to the IPS class, in which factographic search is understood as a process of finding ready-made data and facts that are extracted from texts during the preparation and indexing of input data and are entered into IPS arrays. In this case, the theory and methodology of developing such IPSs practically does not differ from purely documentary IPS, and often DIPS developed and transformed into DFIPS.
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