Data. Everything is Data: The Last Practical Guide You’ll Ever Need For Your Career and Your Company

26 March 2024

Data. Everything is Data.
What is it good for?

Just as for large enterprises, data is incredibly useful and valuable for small and medium-sized businesses (SMBs) as well. It is now confirmed that they drive innovation, improve decision-making, and overall business performance. Additionally, data tends to impress and inspire confidence. But beyond their impact on organizations, data holds immense untapped potential for individuals at all levels of the workforce. They surround us.

Did you know that approximately 328.77 million terabytes of data are created every day? To put things into perspective, that’s about 228.06 trillion 3-inch floppy disks to store the amount of data generated daily.

Yet, amid this data deluge, many workers overlook the transformative power within their reach. Just as in our daily lives, at work, we are surrounded by data. Whether it’s the number of employees and their status, tasks and where they are performed, or their effectiveness. Data forms the raw ingredient of information and knowledge. They exist in our checklists, forms, surveys, inventories, sensors, quantities, distances, and much more.

Yet, we still often ask ourselves the following questions:

What can we do with data, in practical terms?

What if we could unlock its potential? What if every worker, regardless of their role or industry, could use data as currency to drive their own success? Let’s aim to explore exactly that – to empower everyone to seize the opportunities data offers and catapult their careers with confidence and determination.

Here are clear examples:

  1. Predictive Maintenance: Predicting equipment failures and maintenance needs before they occur, to minimize downtime and reduce maintenance costs.For example, in a Mining Operations Center (MOC) like Agnico Eagle, mechanics and heavy machinery operators use digital forms during pre-start checks, preventive inspections, and compliance checks. These digital forms provide structured data to the MOC, enabling the implementation of predictive maintenance strategies.
  2. Visualizing Figures: Data can often be perceived as intangible. However, through graphs, statistics, tables, and other forms of visual representations, this data comes to life.For example, a graph showing sales trends over a given period can help identify significant trends or fluctuations, thus facilitating strategic decision-making. Similarly, a comparative table of departmental performances can highlight areas for improvement or successes to celebrate.
  3. Proving Your Point: A generated report, statistic, or otherwise unquantified observation now illuminated by your presentation of it, demonstrates your powers of observation, your interest, and your specialty. It inspires confidence in you and is an excellent way to stand out in the office by bringing added value to the company.For example, if you work in customer service and use data to illustrate the positive impact of a new communication strategy on customer satisfaction, it reinforces your credibility and demonstrates your ability to draw concrete insights from available data.
  4. Power BI and Other Technologies: No one can perform AI, prediction, or automation of repetitive tasks, such as generating work orders in another system triggered by an action in another system, without structured and customized data. Tools like Power BI enable the transformation of raw data sets into interactive and informative visualizations, thus providing actionable insights for decision-making.For example, an analysis of data from digital forms by Power BI could reveal gaps in cleaning practices in certain services or recurring issues with certain equipment, enabling managers to take immediate corrective actions to ensure staff safety as well as improve the longevity of work tools by avoiding accidents and unforeseen expenses.

As the journal of digital transformation said: It’s important to start from the right place – digitizing our company’s information, and why not start with digital forms. By leveraging the data at their disposal and using appropriate digital tools, workers can not only improve their efficiency and productivity but also advance their careers by demonstrating their ability to make informed decisions and bring added value to their organization. Ultimately, the judicious use of data can open up new opportunities and lead to significant personal and professional growth.


Unlike you may have read elsewhere – No. A data-driven culture does not have to start at the top.

We live in a competitive world. More often than not, having vast amounts of information at your disposal provides advantages over those who do not. Although historically this has always been the case, in the business world, knowledge allows you to have a better view of your company’s efforts and to anticipate future trends. And to give you the best chance of growing your business, you now need to collect data. While this may seem daunting, it’s a process that requires some basic know-how. Let’s make data collection, its methods, and tools simpler.

What is data collection exactly?

Data collection is a vital process aimed at gathering information to effectively address various questions. Essentially, it’s a structured approach to capturing and evaluating information from various sources, providing a comprehensive understanding of a particular domain.

Businesses frequently use this process for various purposes, facilitating informed decision-making and enhancing overall performance. However, before starting data collection, address the following key points:

  • What is the objective, and what is the relevance of the data to be collected?
  • How to identify specific information needed to achieve desired outcomes.

Additionally, it is imperative to select the most appropriate data collection method tailored to the goals and requirements of the business. And if you want to be even more advanced – assigning a dedicated research team to identify and access relevant data sources is essential.


What are the 2 main data collection methods?

Keep in mind that our mission at nspek is clear: to equip you, the savvy professional, with the tools and insights necessary to navigate the vast landscape of information gathering. Whether you’re an administrator, a seasoned business operator, a meticulous mechanical inspector curious about predictive maintenance and rigorous compliance expectations, our goal remains firm: to empower you in your quest for knowledge.

When it comes to data collection, there are two main methods: quantitative and qualitative. The choice of method heavily depends on what you are studying.

Understanding Qualitative Data Collection

So, what is qualitative data collection? Qualitative data is made up of the romance and complexity of human experiences, emotions, perceptions, and behaviors. Unlike quantitative data, it doesn’t focus on numerical measurements or quantities. It doesn’t rely solely on statistical analysis or mathematical formulas to draw conclusions.

It involves a comprehensive analysis of various factors to provide deep insights into raw data. This method encompasses not only data collection but also its analysis and management. As mentioned earlier, it often aims to assess the emotions or thoughts of participants. There are three distinct techniques for qualitative data collection:

  • Ethnographic Exploration: Derived from the rich tapestry of anthropology, this approach immerses itself in understanding the fabric of human existence. It’s about capturing the essence of how people weave their lives.
  • Theoretical Insight: Rooted in sociological inquiry, this method seeks to ground qualitative research in tangible realities rather than abstract hypotheses. It utilizes advanced participant observation, intensive interviews, and curation of documents and artifacts.
  • Phenomenological Perspective: At the heart of phenomenological exploration lies the narrative of human encounters with the unexpected. It’s a deep dive into understanding how individuals cope with unique events or chance encounters. Imagine witnessing the aftermath of a natural disaster; it’s in these moments that the phenomenological focus reveals its significance.

But it doesn’t prevent us from collecting quantitative data on qualitative data such as: The duration of an inspection, the date or location of it, the progress of a filled form, the identification of the person behind it, the number of items or questions, the types of media or formats used, etc.

All are researches that are possible to observe with a good analysis tool.

In essence, our effort doesn’t just stop at data; it’s about illuminating the human experience, enriching your understanding, and strengthening your decision-making process.

Quantitative data collection primarily serves research in various fields, including marketing, scientific investigation, and academia. It involves analyzing numerical results to draw meaningful conclusions. In this methodology, several quantitative data collection methods are commonly employed.

A predominant technique involves conducting surveys containing closed-ended questions, facilitating the acquisition of structured responses. These surveys shed light on preferences, trends, behaviors, opinions, and other quantifiable parameters. Additionally, methods such as tests, experiments, and polls contribute to the quantitative data collection process. These approaches, while relatively straightforward to implement, enable researchers to ask questions aimed at accumulating factual data.

Deepening Quantitative Approaches

There are also different approaches to quantitative research:

  • Descriptive Research: This method paints a detailed picture of the subject or group studied, helping us understand its complexities.
  • Experimental Investigative Research: This approach carefully sets up controlled experiments to discover how things cause other things, revealing the inner workings.
  • Quasi-Experimental Research: Similar to experimental research, this method navigates the realm of variables with partial control, providing valuable insights into phenomena where total control is inaccessible.
  • Correlational Research: Diving into the interaction between variables, this approach unveils complex patterns and connections without implying causality, enriching our understanding of intricate relationships.

Thus, quantitative data collection stands as the bedrock of research, equipping researchers and decision-makers with crucial empirical evidence for informed decision-making and scientific inquiry.

Unveiled Data Collection Tools

Here’s a variety of tools ready to streamline the process effectively.

1. Traditional Paper Forms:
While their significance diminishes with technological advancement, paper forms persist in some contexts. Despite their declining use, some businesses still rely on them for data collection. However, response rates tend to be lower compared to those obtained with more sophisticated electronic form applications, especially those capable of requiring responses to specific fields.

2. Dynamic Interviews:
Interviews emerge as powerful instruments for extracting information from target demographic groups. Armed with a well-designed questionnaire, interviews provide a personalized approach to data collection. To optimize cost efficiency, consider conducting interviews via web or phone chat interfaces. Additionally, the flexibility of open-ended questions enhances the depth and authenticity of responses.

3. Streamlined Online Surveys:
Online surveys provide a cost-effective and expedient way to amass large amounts of data with minimal effort. However, respondents require access to computers and internet connectivity to participate. This tool offers real-time result generation and fosters seamless interaction with the target audience.

4. Mobile Applications: Pioneers of Data Collection 2.0
In the digital age, mobile applications emerge as indispensable tools for rapid and accurate data acquisition. Beyond mere data collection, these innovative platforms facilitate robust data management. Notable advantages include error mitigation and the potential for enriched databases comprising multimedia elements such as videos, photos, and GPS coordinates.

5. Document and Record Analysis:
Documents and records emerge as invaluable resources for data acquisition, obviating the need for direct questioning. By leveraging existing data sources, this method taps into documents such as meeting minutes, attendance registers, and financial reports to gain comprehensive insights.

6. Web Scraping Exploitation:
Venturing into the digital space, web scraping unveils a treasure trove of data freely accessible on the internet. This technique allows the extraction of relevant information from online sources, enriching datasets with external insights.

Why Care About Data Collection?

Today, no one denies that data collection is a crucial process for businesses. It’s not just about improving decision-making; it is about creating a treasure trove of information about various workflows.

Empowerment for Informed Decision-Making:

Data collection equips human-centered, career-oriented individuals with the tools needed to make critical decisions that resonate with the needs of customers and employees. It facilitates efforts to:

  • – Expand the customer base
  • – Improve customer retention rates
  • – Adjust marketing strategies
  • – Raise customer service standards

Additionally, it promotes evidence-based decision-making, paving the way for increased sales, productivity, and improved financial outcomes.

Acquiring a Comprehensive View of Performance:

Data collection offers a panoramic view of business performance, enabling managers to assess the effectiveness of their investments and efforts. By selecting relevant key performance indicators, they can effectively monitor progress and navigate towards success.

Cultivation of Strong Brand Image and Employer:

Leveraging data from employees or customers, companies forge stronger connections with individuals, fostering a sense of trust and loyalty. Just as an employee who feels heard, a satisfied customer becomes a brand ambassador, amplifying the company’s reputation through word-of-mouth recommendations.

Anticipation and Resolution of Complex Challenges:

Data collection serves as a beacon, illuminating inefficiencies and potential obstacles that could hinder growth. Whether through quantitative or qualitative means, it not only identifies problems but also propels the company towards innovative solutions and continuous improvement.

Adoption of Technological Advances:

As technology evolves, data collection methods also evolve. It facilitates and accelerates the identification of inefficiencies and the prediction of potential issues that could impede operations, health, safety, quality, standardization, and growth. It helps the company reduce and detect errors.

Advanced data collection – whether quantitative or qualitative – offers a range of sophisticated tools for analysis and management. From trend-based predictive maintenance to workflow automation and advanced monitoring operations centers, heavy industries harness cutting-edge technologies to improve efficiency and effectiveness, to find appropriate solutions, and to improve for the future.

Evolving at the pace of technology, data collection is not just an elegant expression for gathering information; it makes numbers speak and transforms a noise of information that might otherwise seem random into a symphony.