In all organizations, thousands of data are generated per minute, which result, for example, from actions we carry out in information systems, manual records, machines, equipment, sensors and many other data sources. Despite the existence of this universe of data, teams have great difficulty in tracking and aggregating data, to obtain dashboards, updated in real time, that allow evaluating the performance of the organization, processes, teams, customer or consumer preferences, among others.
This theme is so critical that in the study “More Jobs of the Future – A Guide to Getting and Staying Employed – Through 2029”, published by technological company Cognizant, the role of “Useless Data Engineer” is identified as one of the 21 new careers that will emerge by 2029.
It is therefore crucial to outline digitalization strategies that will result in the creation of a reliable and properly consolidated and catalogued data architecture.
At SINMETRO, depending on each reality, it may prove necessary to implement a network of IoT sensors, to continuously measure tens, hundreds or thousands of critical variables of your production process, and digitize the factory floor, laboratories, quality controls or checklists, to centralize, track and analyze critical data.
Based on this collection of information, we create quick and intelligent tools for statistical analysis and data modeling, incorporating AI/ML algorithms, in centralized and simple platforms, which allow you to monitor, in real time, your entire value chain and create effective value in the company, from Big Data.
Thus, we provide your company with visualization, control, statistical analysis and variable modelling systems, allowing you to reduce numerous non-value added tasks, associated with manual operations of reading process variables and time-consuming data analysis.
At SINMETRO, depending on each reality, it may prove necessary to implement a network of IoT sensors, to continuously measure tens, hundreds or thousands of critical variables of your production process, and digitize the factory floor, laboratories, quality controls or checklists, to centralize, track and analyze critical data.
Based on this collection of information, we create quick and intelligent tools for statistical analysis and data modeling, incorporating AI/ML algorithms, in centralized and simple platforms, which allow you to monitor, in real time, your entire value chain and create effective value in the company, from Big Data.
Thus, we provide your company with visualization, control, statistical analysis and variable modelling systems, allowing you to reduce numerous non-value added tasks, associated with manual operations of reading process variables and time-consuming data analysis.
The methodology adopted to develop these strategies typically includes the following steps:
- Identify the variables that characterize a business and its value chain.
- Understand how these variables are measured and how they are tracked.
- Define the performance indicators (KPIs) to be calculated and measured in real time.
- Map, characterize and validate data collection sources. At this stage, it is important to analyse the information systems that support the processes, their databases and levels of integration. It is common to have data scattered in excels, with insufficient categorization, which makes its analysis very difficult.
- Implement a secure data network, through the adoption of cybersecurity systems.
- Connect machines and equipment to information systems to the data network.
- Define a continuous flow of data that is able to automatically link variables in the value chain.
- Integrate information systems to avoid duplication of tasks and ensure this continuous flow.
- Identify, in the information systems, “states” or actions that imply a change of phase, to measure, for example, the execution times between tasks.
- Define the most appropriate statistical analysis for each type of variable (note: performing the statistical control of numerical variables is different from analyzing attributes).
- Design the dashboards to be developed for each type of variable or set of KPIs (Key Performance Indicators).
- Develop a Business Intelligence system integrated with the various data sources, which allows exploring this Big Data through an analytical view of the data and performance indicators (KPIs), which can integrate predictive models for current and specific situations, associated to alarm rules to support the operation.
- Promote the programming of implicit business logic, which is just “in people’s heads”, in algorithms that make this knowledge explicit.
- Empower people to measure, monitor and control variables, KPIs, with a view to optimizing processes.
Data is today, from the point of view of our CEO Cristina Barros, the “new gold of organizations”. It is, in this context, imperative to value them, bringing mathematics to the floor of operations, motivating and enabling teams to “see” beyond the obvious and identify trends and deviations that can and should be corrected in good time, in favor of process efficiency and organizational sustainability.