Mastering Departmental Efficiency With Big Data

Utilizing data for department efficiency is crucial in today’s economy.

May 16, 2023

Efficiency With Big Data

In today’s data-driven economy, harnessing the power of data is crucial for businesses to thrive. Julius Černiauskas, CEO at Oxylabs.io, explores how businesses can leverage data to improve department efficiency and make more informed decisions. Discover actionable insights and strategies to optimize your operations and drive success in the digital age.

By the end of 2022, the globe had created around 94 zettabytes of dataOpens a new window . Data can be a powerful tool if used correctly, and using it to improve department efficiency is becoming increasingly crucial for businesses in today’s data-driven economy. Although difficult, today’s companies must be well-armed with as much data as possible to make more informed decisions and improve efficiency. 

One of the major obstacles facing many businesses is increasing the efficiency of their departments, particularly in areas such as content management and human resources, where data professionals are only sometimes present. A lack of data and analytical capabilities can make it difficult for these teams to understand how to assess the effectiveness of their work. To address this issue and improve performance, companies must make data more easily accessible and understandable to all employees.

Moreover, it can help non-data professionals better understand the value of using data to improve their work. In addition to making data accessible, businesses also need to create a specific culture within their organization. Fostering a mindset that values data-driven decision-making and encourages employees to use data to improve their work should be considered the way forward for most businesses. 

Involving Non-data People

As data becomes increasingly important, those who can effectively analyze and interpret it are in high demand. However, only some people are comfortable working with information, and knowledge can be a barrier to entry for many people who want to use it to improve the organization’s efficiency.

According to another studyOpens a new window , the situation is even more concerning as almost one in five executives experience a shortage of analytics and IT professionals creating a larger barrier to putting data-centric ideas into action. There is a vast need for more data-given talents. However, there are ways most companies can reduce these gaps internally. 

There are a few things that those who are uncomfortable with data can implement to ease themselves into the world of data analysis. Teams such as administration, HR, and talent acquisition can use automatic dashboards to track their performance. The main advantage of all this is greater employee satisfaction, which comes from several places. First, teams can specifically link their achieved results or profit to the company’s performance. For example, an effective LinkedIn campaign can help to hire new team members quickly, and the product created by that team later brings revenue and thus increases the satisfaction of those teams. 

The second important aspect is the speed of reaction. With a data infrastructure and constant monitoring of team’s indicators, it is possible to react much faster to areas that need improvement, change, or, on the contrary, just encouragement. For example, a team of account managers may notice a sharp decrease in the number of companies in a particular segment (for example, sneakers resellers) and pay special attention to it or apply discounts.

Following that is reduced manual work. Along with the data structure comes the opportunity to automate many manual processes. For instance, admin teams can automatically calculate how many and what kind of newbie presents will need to be ordered in the future while monitoring how the number of employees changes. Instead of the previous long manual process, now they can use an automatic Slack message. 

To achieve this data-first culture, I suggest managers assemble a data team and hire people who can analyze data and create data infrastructure (write ETLs, create data warehouses, transform and clean data, understand data structures, and write code). Leadership must be willing to invest time and resources in the data team – the benefits may be unclear initially, and it often takes up to a year to see the first results. Nonetheless, if the leadership includes everyone in the company to make decisions using data, the company’s data-based culture grows naturally.

See More: The Value of Cloud-based Analytics: How Understanding Your Data Helps Keep It Secure

Fostering a Fact-based Culture

Preceding with data refers to making data-driven decisions rather than relying on intuition or mere personal judgments. It can be challenging to let go of the idea that “we just know” what is best for our departments, but when we are armed with data, it allows us to make more informed decisions that improve efficiency. Strengthening a culture of data in all departments involves making it a central part of making decisions and encouraging all employees to use data to inform their work. 

Fostering data-driven culture also involves creating a supportive infrastructure, such as secure and easy-to-use data storage and analysis tools, and establishing clear protocols for handling and sharing information within the organization. 

One way to achieve a data-driven culture is to use a single source of truth (SSOT) – a concept in which a single, definitive data source is used for all aspects of the business. Having a single source of truth can be particularly important in organizations where multiple teams or departments may be working with different data sets or using different systems to store and manage data. In the cases above, it can be easy for data to become siloed or for different teams to have multiple versions of the truth, leading to confusion and potential errors. 

There are several different approaches to using SSOT for fostering a data-based culture. When teams can trust that the data they are working with is accurate and up-to-date, they are more likely to rely on it to inform their decision-making. 

In addition, by establishing a single source of truth, organizations can facilitate better communication and collaboration between teams, as everyone is working with the same data. By sharing information openly, businesses can get everyone on the same page and work towards common goals. 

Overall, having a single source of truth can help create a culture in which data is central to decision-making, and teams are more likely to rely on data to inform their actions. By tracking progress regularly, companies can keep everyone accountable and ensure everyone is pulling their weight. 

See More: The Ultimate Set of Tools You Need To Ace Data Analysis

Big Data for Departmental Efficiency

A more recent survey conducted in 2022 on Global DataOpens a new window Transformation found that employees are still grappling with non-value-added tasks, albeit to a lesser extent. On average, workers now spend approximately 25% of their time on such tasks, primarily attributable to data quality and availability challenges. The survey reinforces that leveraging big data remains an effective strategy for enhancing operational efficiency across departments.

One example is using big data to streamline the hiring process. Human resources teams need to face a variety of reports and a large number of personnel resumes and statistics. Applying big data in major human resource management modules, including recruitment, talent training, and talent assessment, can make the process more efficient and accurate. 

A good example of using big data is to streamline the hiring process. Human resources teams must handle many personnel resumes, statistics, and reports. However, it would be more accurate, efficient, and objective if these teams embraced the big data philosophy and continued exploring its management. Using Big Data in recruitment, talent training, and talent assessment modules of human resource management.

According to researchOpens a new window , the outcomes of talent recruiting are frequently skewed since traditional approaches cannot obtain thorough information about prospects. Fortunately, big data can assist in avoiding erroneous outcomes. It enables businesses to incorporate recruiting with data from the internet and continuously collect resume information. Combining information on the internet with recruiting can help companies learn more about prospects, helping businesses develop better person-job matches.

Another example is using big data to improve customer service. By tracking customer interactions and mining customer feedback, companies can identify areas where they need to improve their service. It can help them save time and resources by addressing problems before they become more significant.

Still, another example is using big data to improve inventory management. By tracking sales data, companies can predict future demand and order inventory accordingly. This can help them avoid stockouts and overages, saving time and money.

The use of big data is revolutionizing the way businesses operate. Companies can improve their departmental efficiency and make better decisions by collecting and analyzing large amounts of data. While there are still some challenges to using big data effectively, the potential benefits make it a technology worth investing in. Overall, using data to improve department efficiency is an important part of succeeding in today’s economy. 

What steps have you taken to optimize your department’s performance with the power of big data? Let us know on FacebookOpens a new window , TwitterOpens a new window , and LinkedInOpens a new window . We’d love to hear from you!

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Julius Černiauskas
Julius Černiauskas is Lithuania’s technology industry leader & the CEO of Oxylabs, a top global provider of premium proxies and web scraping solutions, employing over 400 specialists. Since joining the company in 2015, he successfully transformed the basic business idea of Oxylabs into the tech giant that it is today by employing his profound knowledge of big data and information technology trends. He implemented a brand-new company structure which led to the development of the market's most sophisticated public web data gathering service.
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