In 2022, the world talked a lot about the National Institute of Statistics, because it was the year of the population census, attempts to find out what was happening in the country. It is also a great opportunity to discuss how information can be used to make better decisions.

Data analytics is only as effective as the information it processes, but before going through the process, it needs to be collected. Larger or smaller organizations have their own mechanisms for this, but so does the country. Each state has an organization that collects data on the state of affairs, from the number of citizens to the most accurate information. Romania has a National Institute of Statistics (INS) and it has been active since 1859.

In the context of the census, which showed us why such information is important, and also because it is a period in which the field of data analysis has developed tremendously, providing answers to challenges that would otherwise be difficult, if not impossible, to solve , we turned to people, who specialize in the field for an explanation of the utility, what data can be collected, and what problems arise.

How he contextualized the situation Kosmin Thanas, Manager of BI and Data Engineering (Data Intelligence and Analytics), Cheil | Centtrade, a well-structured plan for using external data can provide a competitive advantage. “Organizations that keep pace with the expanding external data ecosystem and successfully integrate a wide range of external data into their operations can outperform other companies by improving growth, productivity and risk management.”

The pandemic that began in the spring of 2020 is the first global event to exemplify how relevant external data can be. In a remarkably short period of time, existing models of consumer research, forecasting and forecasting have been rendered obsolete by rapid changes in people’s purchasing habits, activities and digital behaviour. “At the same time that organizations were trying to understand these changing patterns, they were not finding value in their internal data. At the same time, large amounts of external data can – and still can – help organizations plan and respond at a granular level.”

The first step is to have the data. Then use them to your advantage

At the Romanian level, the largest data provider is the INS. Even if in 2022 the Institute was most often talked about through the prism of the census, it is only the largest operation that is carried out once in a decade. Annual activity, however, is much more interesting in terms of the information it can provide. As he explained Volodymyr Alexandrescu, INS spokesman, the metrics the Institute can provide are important in public and private decision making. Any organization that makes decisions in a country, from business development to public policy, needs to know what to expect, what the prospect of achievement is, whether the labor force is there, whether the population is declining or how the population in a certain area or what the local challenges are.

The data that INS can provide is initially included in the research program developed in the fall of the following year. “This program includes new studies every year that appear at the request of those who use the data. The main user, of course, is the state, which needs information to coordinate its development plans at all necessary levels of society. Then there are smaller or larger companies, and basically any organization that exists in Romania can be among the users, because it can benefit from the information provided by the statistics,” Volodymyr Alexandrescu added.

Once the data is collected, it’s time to use it. And in this sense, as Kosmin noted, data analytics can help an organization in everything: from personalizing marketing for an individual client to identifying and mitigating risks for its business. And here comes a critical balance: using data analytics to make business decisions and minimize financial losses. “Predictive analytics can suggest what might happen in response to changes in the business, and prescriptive analytics can indicate how the business should respond to those changes,” she added.

Applying to apparel retail, for example, an online and brick-and-mortar company can analyze sales data along with data from social platforms and then create targeted social media campaigns to drive e-commerce sales for product categories that customers already engage in . interested in In addition, there is the nuance of improving the customer experience, which can be achieved with the help of behavioral analytics models. That way, a company can run a predictive model on e-commerce transaction data to determine which products to recommend at checkout to increase sales. Last but not least, such analysis can also inform the success of campaigns to change prices or place product offers.

At the state level, Volodymyr Alexandrescu noted that the actions behind the data have a double perspective. On the one hand, we are talking about the actual population that will be the subject of the decision – production, sale, hiring, etc. – and on the other hand, we are talking about the prospect of commercial relations with players from other countries, both at the private and public levels. Since the data are collected by the INS based on methodologies valid at European Union level, carried out by statisticians from all Member States, they can be useful for understanding the context outside the country.

As technology has developed rapidly, data analysis has also experienced significant growth. Data can now be retrieved and processed much faster and with much less error. In this context, as explained by Kosmin Tanase, the information resource has become more important in the formation of a market strategy or even a new direction of development, which can be fruitful. But this is where the human resource problem begins, because the informational value of data can only be accessed with the right people who can explore the data and draw the right conclusions from it. “These people have a technical background that involves understanding both mathematical models and analysis methods, as well as the programs needed to run them. Also, simply knowing the technical side is not enough to be able to successfully extract information from datasets. Thus, any analyst needs a quantitative mindset to observe and understand possible patterns specific to the type of data being analyzed.”

Tasks that will speed up data analysis

If INS does not lack data and can provide it as needed, the greatest need is for efficiency in collection and access. At the national level, Volodymyr Alexandrescu said that Romania badly needed an administrative data system that would allow any institution in the country that needed certain information to have access to it without having to do their own research. Such a system would also increase the speed of data collection by reducing field trips, but would also reduce costs. “And in the development of such a project, all institutions that will be the beneficiaries of the relevant information should participate, so that they have elements that allow every subject in the country to use it,” he added.

At the organizational level, Cosmin Tanase explained that organizations can face a number of challenges in collecting consistent and quality data, and it is necessary to first identify the obstacles to consistent data collection. She also highlighted three challenges.

Inconsistent data collection standards. – “The principle of data standardization emphasizes the importance of collecting general data and demographic information. Typically, defined standards include data definitions, structured questions with agreed-upon response options that can guide consistent collection practices. These criteria are not always universally applied and may themselves be inconsistent, which may affect the consistency of data collection.’

Lack of quality assurance processes for collected data. – “The likelihood of verifying the information with the person who contacted the service may be limited, which means that the data initially collected cannot be verified. In addition, the complexity of record keeping systems can vary, as the quality of the data depends on who is entering the information correctly. Time may not allow staff to verify data integrity or recover missing data.”

Economic and IT constraints. – “Some companies do not have the resources or infrastructure to prioritize system updates and data collection processes. This may be due to limited manpower to enter and maintain information or lack of budget to update records management systems. Such upgrades can be expensive and time-consuming.”

Humans are naturally inclined to analyze data and make decisions based on it, even if we don’t realize it most of the time. What we are seeing now is the development of this skill at much larger organizational, national and even international levels. In this unusual field, with the answers it can provide on many levels, at a professional level, data analysis imposes an important condition on the specialist in this field: constant learning and improvement. This is due to the fact that the most accurate results can be obtained in the shortest possible time only when using the latest methods and technologies.

Article based on Cheil | In the middle