How will you ensure the best accuracy of the data collection?

 

Data Collection

Data is a collection of facts, figures, objects, symbols, and events gathered from different sources. Organizations collect data with various data collection methods to make better decisions. Without data, it would be difficult for organizations to make appropriate decisions, so data is collected from different audiences at various points in time.

For instance, an organization must collect data on product demand, customer preferences, and competitors before launching a new product. If data is not collected beforehand, the organization’s newly launched product may fail for many reasons, such as less demand and inability to meet customer needs. 

Although data is a valuable asset for every organization, it does not serve any purpose until analyzed or processed to get the desired results.

Data is the fuel that drives a business organization. Whether it is about resource consumption, investments, outcomes and returns on consumed capital and resources, competitor performance, industry trends and indicators, customer needs, market analysis, operational scrutiny, performance check, or workforce management, their payroll mechanisms, bonuses, over times, time checks and productivity, data plays a crucial role in determining the efficiency of these essential functions and processes.

Data is generated at a dizzying pace. According to Statista, information generation is expected to reach a volume of 181 zettabytes by 2025. This avalanche continues as  project managers  who want  quality data  ask themselves “where should we start?”

In the world of  marketing research , we have too often seen examples of bad surveys, forms and questionnaires. However, what is the point of collecting data when it is incomplete, inaccurate, or riddled with errors?

That is why in this blog we will provide some tips to counteract this problem and ensure the collection of  quality data .

Types of Data Collection Methods

The choice of data collection method depends on the research question being addressed, the type of data needed, and the resources and time available. You can categorize data collection methods into primary methods of data collection and secondary methods of data collection.

Primary Data Collection Methods

Primary data is collected from first-hand experience and is not used in the past. The data gathered by primary data collection methods are specific to the research’s motive and highly accurate.

Primary data collection methods can be divided into two categories: quantitative methods and qualitative methods.

Data collection projects: how to carry them out?

Quality data collection   is the process of gathering and measuring information about variables of interest. Generally, this is done in a systematic way and allows us, among other things:

• Gather information from various sources, in order to obtain a complete and accurate overview of an area of ​​interest.
• Allows individuals and companies to answer relevant questions. This way, they can evaluate the results and better anticipate future probabilities and trends.

To do this, it is important to consider that accuracy in data collection is essential. Well, only in this way can the integrity of a study that leads to correct decision-making be guaranteed.

While methods may vary depending on the company running the study, the emphasis should be on ensuring  quality data collection .

Importance of ensuring quality data collection

Regardless of the field of study or preference, whether quantitative or qualitative, precision in a study is essential to maintain the integrity of a research.

The consequences of having data collected incorrectly include:

• Inability to answer research questions
• Distorted findings resulting in wasted resources
• Loss of time for other researchers causing them to search for fruitless research avenues
• Committed decisions that have consequences on markets, companies and people

What are the challenges to solve to obtain quality data?

Since  quality data  precedes well-maintained processes, its main focus is based on planning. Some of the most common challenges include:

• Uncertainty about the timing, methods and identity of the people responsible for reviewing the data
• Vague description of data collection instruments to be used
• Lack of training of staff members responsible for data collection
• Hiring a certified and widely experienced data provider

Characteristics that quality data must meet

Every  project manager  must keep in mind that  quality data  must meet only one characteristic to achieve this qualification: it must be reliable.

With this in mind, there are several factors that must be considered in the initial planning process. This is how quality can be measured in each of the phases of the study by reviewing the following:

• The design of the questionnaires
• The definition of the sample:  is this survey being sent to the right people? Is there a representative number?
• The panel selection process
• Administration and management of the field
• Processing of the results

But how to guarantee reliable data collection? Let’s see it next!

How can a  project manager ensure  they have quality data?

An important component of ensuring  quality data  is developing a detailed plan from the beginning. However, beyond the organization, quality in these terms obeys international standards.

The international standard ISO 20252 is responsible for governing and monitoring social, opinion and market research. Including insights and data analysis.

It establishes guidelines and requirements related to the way in which market research studies are planned, carried out, supervised and reported. In this way, the companies in charge of this type of projects adhere to strict guidelines to ensure a maximum degree of reliability and integrity.

What can be obtained from having a monitoring body? Thanks to your participation, we achieve consistency and transparency in the way surveys are conducted. Likewise, confidence is obtained in the results and in the providers who provide this service.

For example, if a problem arises with the contracted service, the standard specifies a series of actions with which a  project manager  can appeal:

At the project level

• Request to replace interviews.
• Additional validation request.
• Review of the data obtained.

At the field work level

• Additional training for interviewers can be requested.
• In the case of fictitious interviews. Review and validation of recent or simultaneous work performed by that person must be requested.

 

 

Why is it essential to maintain the accuracy of data?

It is only through an effective data analysis that the management can keep a track of their performance. It is through this that the organization develops an insight about where it stands in the market. Data analysis is the basic and most crucial component of business and organizational research and therefore, it becomes all the more essential to maintain the neutrality, credibility, quality and authenticity of the collected data.

Data analysis will only provide a realistic insight and will suggest real-time and practical measures if the data is genuine and free from any machine or manual errors, discrepancies or loopholes. Therefore, it is essential for data analysts and organizational management to ensure the accuracy of data and information collected on a regular basis from various organizational operations and procedures.

And measures to ensure the accuracy of data

The efficacy and accuracy of the data collection process can be improved by incorporating the following measures in the data collection techniques.

Use reliable data resources

Data resources play the most crucial role in effective data collection and further analysis. You need to ensure the reliability and credibility of the systems and personnel responsible for data and information generation.

Align your key factors and parameters

Analyze and sift through the factors that contribute to data accumulation, and figure out the most relevant factors you need for the analysis or to develop a feasibility or performance report of a particular task or operation. Devise a set of basic and essential parameters to formulate a game plan for your data collection.

Align your key factors and parameters

Analyze and sift through the factors that contribute to data accumulation, and figure out the most relevant factors you need for the analysis or to develop a feasibility or performance report of a particular task or operation. Devise a set of basic and essential parameters to formulate a game plan for your data collection.

Maintain the neutrality

Rumors, claims and exaggerations pertaining to a specific issues or tasks may invoke the wildfire effect that only tends to compromise or alter the neutral perspectives of data collection. The wildfire effect is the consequence that occurs as a result of a negative bias.

Use automated and computerized programs

There is a huge room for mistakes and human error in the manual mechanism of data entry and information recording. There is also a high risk of compromised and inaccurate data entries due to personal biases and buddy favors that might totally change the inferences and results and hence, lose the efficacy and portability of the data analysis and results. Data collection through smart and automated systems, such as Time and Attendance Software, makes it convenient for managers to focus on other factors and parameters while the system records real time and accurate data in perfect tandem.

Data is the fuel that drives a business organization. Whether it is about resource consumption, investments, outcomes and returns on consumed capital and resources, competitor performance, industry trends and indicators, customer needs, market analysis, operational scrutiny, performance check, or workforce management, their payroll mechanisms, bonuses, over times, time checks and productivity, data plays a crucial role in determining the efficiency of these essential functions and processes.

Why is it essential to maintain the accuracy of data?

It is only through an effective data analysis that the management can keep a track of their performance. It is through this that the organization develops an insight about where it stands in the market. Data analysis is the basic and most crucial component of business and organizational research and therefore, it becomes all the more essential to maintain the neutrality, credibility, quality and authenticity of the collected data.

Data analysis will only provide a realistic insight and will suggest real-time and practical measures if the data is genuine and free from any machine or manual errors, discrepancies or loopholes. Therefore, it is essential for data analysts and organizational management to ensure the accuracy of data and information collected on a regular basis from various organizational operations and procedures.