ALP Group Process Mining

Main article:

• Business Process Management
• Process Mining

2022

Ability to track and process huge amounts of information in multithreaded mode

The department of corporate information systems ALP Group (LLC ALP-IS is DKIS) reported on February 2, 2022 about "training" of the author's technology of monitoring and fast adjustment business процессовProcess Mining to trace and process in the multithreaded mode huge volumes of information (thousands of elements) - and for one cycle. At the same time, the technology can work with both long-standing and new databases, manage the sequence, quickly connect information sources and manage each of these processes centrally.

Now, key Russian developers and their customers using business management systems will be able to automatically receive the necessary slices of information about the implementation and change of business processes, as well as about their compliance with specified regulations. These processes include, in particular, such mandatory types of corporate activities for any enterprise as, for example, budgeting, procurement, end-to-end management reporting, timely information about tasks not completed in time, etc. In addition, in the future, DKIS ALP plans to combine additional analytical modules into a single environment that will allow customers and project executors to forecast the progress of specific work, the flow of cash flows, production processes, the possibilities for the real development of individual IT modules and IP in general - for the real tasks of each particular enterprise.

The Russian development of DKIS ALP - Process Mining - is designed to become an integral part of the management system of Russian enterprises, including those engaged in such critical sectors for the domestic economy as oil and gas, energy, the financial sector, transport, construction, etc. Now, thanks to the dramatically expanded capabilities of this technology, almost any Russian company gets the opportunity to use all current IT tools, including those built on the 1C platform.

Based on AI accounting and management reporting technology

The Department of Corporate Information Systems ALP Group (ALP-IS LLC - DKIS) will create technology for the formation of accounting (RAS and IFRS) and management reporting based on artificial intelligence. The author's development of Process Mining will check the correctness and compliance of the received data according to already approved rules and procedures. This was announced by the ALP Group on January 27, 2022. More details here.

2021

Start Process Mining Central Management

The Department of Corporate Information Systems ALP Group (ALP-IS LLC - DKIS) on October 28, 2021 announced that it has fully automated the key monitoring and administration processes of customer information systems working in conjunction with Process Mining (PM), the author's ALP DKIS technology for the analysis, management and improvement of business processes.

The updated functionality made it possible to minimize the burden on system administrators and, at the same time, reduced the time for connecting information bases to PM. This was achieved through the introduction of specialized regulations and the centralization of a number of processes. So, now any 1C customer information base in several steps can be registered in the Process Mining system, and immediately begin to interact with it. Thus, through the automation of procedures, the work of connection administrators is limited only to embedding a small component into monitored information databases, which, in addition to the mechanisms necessary to collect and prepare data for analysis in global IP, now contains tools for managing the work of Process Mining itself.

All other actions necessary for the full operation of the PM system, including with additional information bases, can now be performed centrally. One of the key actions is to control the size and priorities of task queues: the monitoring module controls the size of the intermediate queue, warning the administrator in advance if the system begins to fail to handle the entire flow of events. In this case, depending on the load and the number of input events, you can increase the size of the processing "packet" in one cycle, or the number of processing flows. As a result, in one cycle, it is possible to process not a hundred, but thousands of elements in one cycle in multithreaded mode.

In addition, a visual visualization mechanism of the system load level and availability was added to the PM system, implemented in the form of a "traffic light" displaying the statuses of processes occurring inside the system at the current moment.

A number of automated functions have also appeared that allow you to manage the access, depersonalization and filtering of data by given slices - including by objects, events and statuses that are necessary for process analysis in a specific situation.

An important advantage of the solution is the ability to work through a centralized command interface.

For large Russian enterprises interested in the rapid deployment of information systems, the author's DKIS ALP technologies (lean production and change management systems) have long become a kind of standard in the framework of integrated IT projects. Process Mining technology in this range occupies a special place, responsible for constant tracking, adaptation, and in some cases, the formation of new business processes: both in traditional and in new areas of business that are not yet accustomed to fully using ERP systems.

As part of the "hybrid ERP" model

The ALP Group Corporate Information Systems Department announced on October 20, 2021 that it will use the "hybrid ERP" model, which will dramatically reduce the time to implement automated enterprise management systems, quickly receive and process initial results. The updated model will ensure maximum flexibility and adaptability of solutions during operation, as it does not limit the customer when implementing business processes, but "adjusts" to them and supports business continuity.

The solution is based on two key developments of ALP DKIS - Process Mining and Change Management System (MIS) with the use, if necessary, of the Low Code methodology in the market.

The flagship development of the ALP Process Mining (PM) DKIS is a system-forming element of the "hybrid" ERP deployment model and provides continuous monitoring of the customer's business processes, allows them to be managed at the level of specific procedures and events, and through the functions of dynamic analytics - almost instantly transfer this information to the relevant IP modules and inform employees about the identified changes and deviations. To implement these functions, ALP has created a set of ready-made business process benchmarks. Thus, due to this module, at the stage of planning business changes, you can analyze key laws, and when implementing the project - unify them, creating a kind of designer that is flexibly customizable for each innovation.

The second component of the presented model is the ALP DKIS author's technology for change management (MIS), which at the IT system level provides notification of new tasks (with control over the availability of all necessary supporting documentation), tracking and recording customer requests, automatic and timely distribution of production tasks, monitoring their execution, as well as project information support.

Finally, by using Low Code technology in some cases, the customer is able to significantly reduce the implementation time of functionality that supports decision making and the quick implementation of new and transformation of existing business processes.

All these technologies, linked into a single set, translate IT from a traditional automation tool into a real business assistant, aimed at introducing genuine innovations, and in a short time and with an understandable return mechanism. With this approach, many functions that are critical to enterprises can be implemented in just a few days, and without reference to the refinement and serious redesign of the system.

Expanding the composition of global analysts. Dynamic Dimension Functions

ALP Group Corporate Information Systems Department (ALP-IS LLC - DKIS) - a Russian developer of IT solutions for managing large commercial and state organizations based on 1C software products - June 3, 2021 announced the completion of work on a large-scale modernization and expansion of the functionality of the Process Mining system, designed to conduct continuous automated monitoring of business processes going on inside corporate IP.

The most important change in the Process Mining software in the second phase of the project development was the expansion of the composition of global analysts, the introduction of the concept of "object status," the addition of the function of dynamic analysts, as well as the mechanisms of quantitative indicators and sets of ready-made business process benchmarks.

So, now the system allows you to perform process analysis in the customer IE, built on different configurations, but having identical business processes associated with different objects. In particular, in the updated version of Process Mining, the attribute "Optional Business Process Step" appeared, which makes it possible to use a single standard of a particular process for different departments and IP. At the same time, in the template you can specify a business process step as optional for a particular information base. Accordingly, the system does not treat as a process violation the absence of the specified business process step in the information base linked to the configuration. For example, in the business process of purchasing, the step "Request from subdivision" may not apply in some IS, while all other steps (approval, transfer of funds to the supplier, etc.) are the same. In this case, the "Requisition" step is marked as optional for systems where it is not used (and vice versa); thus the system will not issue an error.

Another innovation was the mechanism of dynamic analysts. You can now configure your own set of analytical sections for each configuration, and Process Mining will automatically "take" the relevant data from the customer's system during the initial download, and later, when performing a process analysis, will display this information for different sections.

We have also completed the development of a quantitative mechanism that allows you to enrich analytics with large sets of aggregated data (totals/sums of directory elements, document details, etc.). It is important that, like dynamic analytics, quantities are configured independently for different information databases linked to different configurations. Thus, now, working with data, the analyst is able to use quantitative analysis when monitoring processes.

Work continues on the development of the reference process library, which contains the necessary templates for typical ERP on the 1C: Enterprise platform, which allows even faster implementation of the Process Mining system. With this approach, the need to configure templates disappears, and to start the system, it is enough only to implement the embedded part of Process Mining in the customer's IS, deploy SQL Server and configure integration using the command interface. In this case, data in automatic mode immediately begins to arrive and be checked by the system for compliance with standards. Dynamic analytics and quantities can also be added as required by the customer.

Process Mining technology created by ALP DKIS can be used in organizations of any scale and scope.

Expanding AI Applications

The ALP Group Corporate Information Systems Department (ALP-IS LLC), a Russian developer of IT solutions for managing large commercial and state organizations based on 1C software products, announced on February 16, 2021 the expansion of the areas of application of Artificial Intelligence technologies for managing various types of projects for the implementation of CIS (Corporate Information Systems) and internal process management.

Now, along with the traditional use of AI in optimizing business processes with the help of POProcess Mining, DKIS ALP will use the capabilities of these technologies to test hypotheses in the corporate Laboratory, assess project risks, as well as when selecting personnel.

In addition, now on an ongoing basis with the help of Artificial Intelligence, the company is testing software components that will be used in real projects in the future. For example, one of the key practices for the ALP DKIS is to conduct an in-depth analysis of the quality of program code. At the same time, according to the company's experts, AI technologies should be used in conjunction with other traditional development and analysis tools, since only in this combination can the system integrator guarantee its customers high quality of functionality and reliability of the implemented projects while maintaining the proper level of information security. It is important that this approach applies both to open source solutions, which ALP DKIS develops and supports on its own, and to proprietary products that receive supplier support, the company noted.

In 2021, DKIS ALP plans to expand the use of AI in a number of other key areas of its work. First of all, the company noted a global package of quality control solutions, covering directly program code, performance, documentation, etc. In turn, in the field of personnel management, AI will be widely used in predicting the load of specialists. This will allow for a more accurate balancing of staff in order to scale rapidly and accumulate resources for specific projects. In the future, on the basis of AI, the company plans to implement the technology of accurate management of mutual settlements and relationships with customers for each project.

2020: Integration with 1C: Enterprise

On October 28, 2020, ALP Group (ALP-IS LLC) announced that it had made POProcess Mining one of the key tools in integrated ERP projects. This solution is fully integrated with the 1C: Enterprise system and can be used in organizations of any scale and scope.

The Process Mining application is aimed at the most effective use of ERP systems created on the 1C: Enterprise platform, and is the first domestic development of this class on this platform. This solution is created within the ALP Group and thus does not depend on foreign software. Currently, pilot projects of this system are underway with some ALP customers.

Process Mining allows you to automatically monitor business processes within enterprise information systems continuously and, in case of discrepancies, record and notify authorized employees in real time.

We emphasize that as the business, the number of employees and the territorial distribution of the enterprise grow, it is especially important to be sure that the business processes taking place within the corporate information system fully meet the standard defined in the regulatory documents. To achieve this, continuous monitoring of these processes is required. At the same time, it is especially important to monitor the progress of processes when amending existing regulations: any changes should be mandatory reflected in the IS and, therefore, be carried out in accordance with updates. It is impossible to solve such problems of complex monitoring manually, by analysts in practice.

The initial configuration of the Process Mining application - building a process model and evaluating compliance with regulations - provides for loading data from the logs (logs) of events of enterprise information systems. Then, as a result of their processing and analysis, a complete picture of the processes actually taking place in the system, their sequence, participants and their actions is created, time intervals between events are calculated, etc. Note that the customer can adapt his IE himself, and can attract an external consultant for this, since the creation of a library of reference processes is a rather time-consuming task.

In the next stage, during the operation of the system, continuous monitoring and comparison of data from the customer's IS with reference business processes is provided. The application collects data on the fly, in constant mode - for this, ALP specialists developed a specialized module that is embedded in the customer's 1C system. This module collects, depersonalizes, and sends user information to the Process Mining application. Note that the special technical solutions that were used to create this module provide complete transparency of data collection operations, and the module itself does not affect the performance of the system (it works constantly, but users do not notice this). It is also important to emphasize that this ensures compliance with the requirements of the IB and the protection of confidential information: only aggregated data in an impersonal form that does not contain either commercial or personal information are included in the Process Mining database. Thus, information is used only for process analysis.

The application helps identify the causes of discrepancies that may include, for example, changes to regulatory documents that are not reflected in the system. More complex situations include malicious intent or negligence, when someone receives wider access rights than prescribed by the regulations, and commits unlawful actions. Since such events can have critical consequences, automatic detection of such deviations is particularly important as quickly as possible.

When implemented, Process Mining is deployed within the customer's corporate network, and the embedded data collection module is added to all ERP configurations that need to be monitored. The platform works with its own separate database, where you can also load the "history" of data from the event log 1C, which is useful in the initial formation of the process model and making adjustments to the IE.

Note that Process Mining continues to develop and improve. So, a number of functions are being developed, primarily related to the business process analyzer. These works are carried out taking into account the experience of real projects and the needs of various categories of users (business, IS services, etc.). The ability to monitor, build intelligent business process graphs is also expanding. Particular attention is paid to system performance: during the year, the information system can generate more than 300 thousand events related to one regulatory process, so serious optimization of calculations is required to support real-time work.

2019: Process Mining Platform Launch

On June 18, 2019, the ALP Group Corporate Information Systems Department announced the release of an import-independent technology platform for continuous process optimization (process mining). This platform (alone or in conjunction with the RPA-DKIS platform) simplifies the creation of i-ERP class solutions based on 1C products for large organizations.

According to the developer, this platform is comparable in its functionality to leading foreign analogues focused on Western ERP systems. In contrast, the development of ALP DKIS is fully integrated with 1C products, which is its key feature. It is of interest to any organizations using or switching to process management, striving to constantly improve the efficiency of their processes, reduce costs, identify violations of regulations, and optimize them. The use of the Process Mining DKIS platform reduces the sanctions risks of Russian enterprises and allows them to increase customer orientation and adaptability, as well as more accurately assess the quality of work of specific employees.

The Process Mining DKIS platform provides two application scenarios: with or without a business process reference description.

When working without a standard, the customer receives a powerful tool for analyzing the established practice of solving similar problems. And it can gradually develop the optimal rules of the process by identifying coincidental and different sequences of actions, prohibiting certain actions, as well as assessing the spread of the duration of individual operations and the entire process. At the same time, moving from private to general, the organization minimizes the risk of unnecessarily simplifying regulations and losing its undocumented "know-how" that create competitive advantages, the developer emphasized.

In a benchmark version, it is of greatest interest to the analyst or auditor to be able to automatically detect deviations in actual sequences of actions from those required by the regulations, while obtaining an accurate assessment of the impact of specific employees on the performance and timing of the process and its critical branches. This analysis allows you to find ways to improve even well-tuned processes. And also to identify the individual inefficiency of specific employees, while separating low qualifications and lack of motivation from cases where productivity decline had objective reasons (for example, complex customers are sent to a certain sales employee). Such reasons are recorded in the system, which allows them to be taken into account when re-analyzing.

Thus, according to the developer, the Process Mining DKIS platform not only supports the full life cycle of the business process, but also copes with a situation typical of Russian organizations when well-developed processes (for which benchmarks have been developed) are adjacent to processes that are in the early stages of formalization and are characterized by high variability, as well as with established practices that have yet to be formalized and regulated.

The ALP Group noted in the DKIS that in a no-ethal scenario, the organization may not have an initial idea of ​ ​ how the process should be organized. The analyst only sets his original and final documents (for example, for sales - a customer card in the CRM system and an invoice in accounting), and also imposes restrictions using filters that allow you to simultaneously take into account many different factors (for example, a time segment, a slice of the customer base, region, transaction amount range, etc.). For each instance of the process being studied, the system extracts from the 1C applications the entire collection of documents created when moving from the start point to the end point, identifies the performers of each action, and clearly displays matching and different sequences. Repeating the analysis with different parameters, the analyst or auditor quickly comes to understand what to include in the process rules, what to cut off, and what to leave to employees.

In an alternative scenario (with a reference), process instances are sampled in the same way, but they are not compared with each other, but with process rules that are considered correct, that is, reflecting the organization's current view of the norm. By changing the reference rules, you can conduct managerial experiments according to the "what if" scheme. The Process Mining DKIS platform is fully integrated with the 1C technology platform and its non-enterprise ON management application. The introduction of this software product, according to the developer, will allow a wide range of Russian customers to switch to import-independent ERP class and i-ERP solutions, improve the quality of management, as well as the efficiency of processes, departments and enterprises as a whole.