In order to leverage data, companies must have access to quality information from various sources that provide impactful metrics from which they can build a plan of action.
Gathering information is not difficult, especially with modern technology that allows users to search through millions of sources in a matter of seconds. However, filtering out good data sets that provide actionable insights may be a more comprehensive task.
Therefore, organizations should understand the essential elements of good data and learn how to leverage this information to promote sales and profits.
At first sight, collecting big data may seem simple as users can plug keywords into search engines to populate relevant external content. However, there are key characteristics data sets need to possess to make sure they can be converted into business analytics and data insights.
The 5 elements of a good data set include-
1. Comprehensive Data Consolidation
In order to gain an inclusive view of a business or specific operation, information needs to be collected from a wide variety of data sources. Seeking new and different perspectives gives a data set more context, creating comprehensive, actionable insights.
2. Reduced Repetitive Data
By minimizing duplicates, analysts can efficiently sift through a data collection without having to repeat analyses. Duplicates can lag data integration by adding repetitive information, hampering workflow.
3. Standardization for User Accessibility
Data that originates from disparate sources tend to be formatted and structured differently, making it difficult to digest. Therefore, the information should be organized to ensure it is comprehensive for the user.
4. Quick Response Time
Some actionable insights are time-sensitive and therefore require prompt access to real-time data. Having a quick response time enables fast decision-making based on accurate information, promoting functionality.
5. Easy Integration
Information stuck in its source system is of no use for businesses and cannot be generated into further reports and big data analytics. By integrating existing systems, employees do not have to sift through solutions to manually collect data. Instead, integration software automatically pulls and consolidates information, avoiding human errors, and enhancing workflow.
Leveraging data enables companies to turn raw information into valuable actionable insights. In order to successfully leverage data, organizations must learn how to gather, analyze, and present information effectively.
Businesses can use these five tactics to properly leverage their internal data-
1. Use Data to Establish the Company Brand
Without a collection of metrics over time, businesses remain unaware of the steady and emerging trends in their industries. These patterns help to define a company's strengths and weaknesses, allowing the business to implement new efforts to better establish their brand's identity and evolve with changing trends.
For example, a study by Mint.com in 2009 showed that Redbox was the most popular DVD rental provider on the market, whereas Netflix was the least successful. However, Netflix has since rebranded their company, no longer providing DVD rentals but dominating the virtual streaming service industry.
2. Create Impactful Presentations and Reports
Many companies will simply plug in their metrics and graphs into a default template to create presentations. While this may save time spent on preparation, using the same reporting method quickly becomes uninteresting. Even if the featured information is groundbreaking, a repetitive or dull presentation will damper its impact.
Therefore, effectively developing a thorough, eye-catching report with context, comprehensive metrics, and scenarios ensures the data's significance is clear and impactful.
3. Utilize Visualizations in Marketing Ventures
Visual aids are great tools to draw attention and organize data in digestible formats. Studies show that data visualizations draw 30 times more attention from the audience than standard textual reports and are more likely to go viral due to their shareability.
Line graphs can display a significant amount of quantitative data to show progression over time, while bar graphs can organize metrics by specific functions or items to show their individual performance.
4. Make Data-Driven Decisions
Business intelligence promotes data-based decisions to improve the functionality of departments, such as sales and marketing. By monitoring metrics or key performance indicators (KPIs), companies can analyze various operations' performance to define what functions need improvement. This raw information can then be converted into actionable insights and data analytics to help management teams develop a plan of action.
For example, if a company launches two promotions at the same time, they must monitor the performance of each through sales, customer behavior, and demand fluctuation. Without proper data analysis, marketing teams cannot define which strategy is effective and what elements need to be altered.
5. Open Data to Outside Programmers
Some companies have hosted what is known as a "hackathon" where they publish their raw data, allowing outside analysts and programmers to manipulate and explore the information. While it is still an unusual concept, this allows businesses to look at the content through a new lens at no or limited additional expense.
Yahoo is known for holding the first hackathon event and still practices it regularly. When Facebook was launched, they promoted an all-employee hackathon from which modern features such as the like button, timeline, and chat were developed. These events have allowed creatives to bring new, innovative ideas to companies who seek a fresh perspective.
Companies that collect information from internal and external sources need to learn how to leverage data to their advantage. Good data sets can hold crucial information on an organization's successes and failures that can enhance productivity but may remain ineffective without proper usage. Therefore, businesses should strive to collect, analyze, and convert quality information into actionable insights to promote data-driven decision-making.
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