What is Data Analytics in Business
Data analysis is the collection of information, numerical values, characters, etc., that is indispensable for a certain purpose (in this case, business), and the collected Data is classified, organized, molded, and selected before interpretation. Recent advances in IT technology have made it possible to process and store vast amounts of Data at high speeds, and Data analysis's usefulness has increased, making it important for many organizations.
"Data" in each department refers to the following items.
Customer attributes such as age, gender, and occupation; sales Data for products and regions; the number of negotiations, process up to closing negotiations; sales number Data, and product purchasing.
Human resources department
Employee Data, attendance Data, career, applicant information in information recruitment activities
Participant Data in various advertising media, seminars, event promotion, cost-effectiveness, competitive product trends, regional characteristics, selection of target group
Customer support department
Number of inquiries for each product/service/hearing content, inquiry type, complaint response type/opinion aggregation
Benefits of leveraging Data analysis
With the progress of IT technology, the importance of Data analysis in corporate activities is increasing year by year. Even organizations that do not currently use Data analysis for their business processes will need to introduce it in the future.
- It is possible to forecast the future
- Can extract problems and possibilities that have been overlooked so fa
- Speedy decision making
By utilizing Data analysis, information that has been uncertain in the past can be extracted with higher accuracy, making it easier to continuously increase sales and market share or consider measures that will lead to them. Although the accuracy of the analysis is not perfect, it is possible to perform highly accurate analysis and prediction by reducing the uncertainty due to the relevance and causal relationship of each Data.
Utilization of Data analysis makes it possible to discover problems, new possibilities, and hints by aggregating information that has been scattered throughout the organization. In the past, analysis of issues faced by companies generally relied on empirical rules and intuition. However, since the results obtained from Data analysis are analyzed and processed from the collected and accumulated Data, it can be capitalized as an organizational resource rather than the information with low accuracy so far.
Rapid decision-making is essential for modern business activities. Introducing Data analysis helps companies make quick decisions and make decisions by quickly providing relevant Data to their challenges.
Three points to note when using Data analysis for business
Introducing Data analysis alone cannot maximize the benefits and benefits. In addition, if you make a mistake in operation or utilization, your work may become complicated or inefficient. Below are the points to note when using Data analysis for corporate activities and business processes.
- Risk of bias caused by subjective analysis
- Don't stick to the method too much.
- Perform analysis with a purpose in mind.
For Data analysis, it is important to correctly identify the causal relationships and regularities found in the Data. Relying solely on subjective hypotheses and Data analysis techniques can lead to subsequent behavior and outcomes bias. Biased hypotheses and Data analysis also include the risk of overlooking issues and issues that cannot be visualized. Therefore, deepen your understanding of the problem you are trying to analyze in advance, select an analysis method that suits your purpose, and remember that if you make a mistake, you will make mistakes in your subsequent actions, and you will need to change direction.
Because many companies are adopting Data analysis, sticking to Data analysis techniques narrows your horizons and tend to overlook tips for developing your business. Data analysis is just one element in formulating management decisions and strategies. It's important to understand in advance that Data analysis is just a factor in determining if the Data is valid, rather than simply applying it to strategy or marketing.
The most common mistake is the purpose of "why do you analyze Data?" It is not clear. If this point is overlooked, the site may be confused, or the work may be complicated. When using Data analysis, it is important to understand that understanding the analysis method and judgment on the analysis results are important.