MMK approves data management framework
A key element of MMK's Development Strategy until 2025 is the digitalisation of the Company's business processes with the ultimate goal of increasing labour productivity and improving product quality.
Digitalisation and the development of automated systems leads to an accumulation of data on a large scale which grows rapidly and constantly. The complexity of processing such large data sets – known as 'Big Data' – makes it necessary to find new approaches to data management, which includes not only creating, storing and maintaining data, but also increasing the efficiency of the data search process that is required for further analysis.
The Data Management Development Project was launched at the end of last year and approved for implementation by MMK CEO Pavel Shilyaev. Testing of the new framework was carried out on the basis of data from two production structural units: the Oxygen-Converter Shop and the thick-plate mill 5000.
"An archive of digitised data without a data management system looks like a library without a filing system," notes Dmitry Ganaev, manager of the cross-system integration and monitoring group at MMK Informservice. "Searching for information in such a system is like searching for books by taking one after another off the shelf at random. Data management means creating a structured catalogue and a full inventory of existing data, as well as developing a methodology for further automation of these processes. In other words, it means generating data on existing data."
The ultimate goal of the project is to enable MMK's analytics specialists not only to find necessary data quickly, but also to conduct better analyses. It is sometimes said that the difference between "information" and "data" is that only information has a value. It is the results of the analysis that turn "data" into "information". High-quality data management will make information more accurate and complete, and therefore more valuable.
To make this happen, MMK will create a unified corporate dictionary that describes terms in a way that allows the data to reflect the same nuances of meaning. The system and users alike will "speak the same language". The next stage is to catalogue the data for all information systems that record production data and other data belonging to MMK.
"In terms of data management, MMK is at the forefront not only among its competitors, but also on the market as a whole," says Anton Konstantinov, Manager of Deloitte CIS Consulting Department. "A developed data management function is a prerequisite for the successful implementation of MMK's digitalisation strategy. In addition, it provides cross-functional support to other areas of the Company's development. For example, MMK has the strongest unit in the field of analysis and processing of digital data by mathematical methods (Data Science), which will be able to use the services provided by the data management unit for even deeper analysis and building accurate prediction systems.”
The main tasks now facing MMK in terms of data management are to ensure availability and quality, and to develop a convenient service for internal use. As shown by a 2019 Deloitte study, which included a survey of top management from more than 1,000 companies around the world, the problem surrounding high-quality data services is now very acute. Around 67% of those surveyed at the level of senior manager or higher stated that they have difficulty gaining access to and using data. MMK is already working to prevent this problem.
“Currently, technologists and analysts often must collect information in parts from different information systems when searching for data. Creating a unified system and handling data on a level that meets modern demands will enable us to increase the speed and quality of our analytics and, ultimately, to increase efficiency and the quality of management decisions,” Mr Shilyaev emphasised.
MMK faces the same task that businesses all over the world are facing: how to transform the function of data management from being strictly supportive to creating a direct or indirect economic effect. This can be achieved by shortening the amount of time between the beginning of an idea’s development to its eventual realisation – i.e. the time spent on data search, business analysis and decision-making. This makes it possible to launch new products and reform existing ones faster than competitors. In addition, in the medium-term, departments should cooperate with data management team to find proactive approaches to improving various business indicators, as well as possible ways to monetise collected data.