Why do 83% business leaders use data analytics to improve decision-making?
Gone are the days when businesses sidelined data to make informed decisions. The current business landscape demands companies to leverage data to rise above the rest. From improving sales and gaining new customers to enhancing productivity, data insights can help companies across different areas.
Data analytics has evolved and will continue to do so thanks to artificial intelligence (AI). AI-powered business analytics plays a critical role in enhancing decision-making. Around 83% of business leaders have turned to big data to improve decision-making and glide past their rivals.
As more and more businesses move online, they can gather data from many sources. That being said, collecting business data insights is futile if you do not understand how to use them to your advantage. Therefore, data analytics is increasingly being used by businesses worldwide. That said, there are plenty of businesses that are reluctant to switch from conventional data integration techniques to new and improved practices.
If you are not convinced yet, we hope this article changes your mind. We will take you through the benefits of using data analytics in business. In addition, we will also look at why it is important to use business data insights for better decision-making.
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Understanding data integration
As mentioned earlier, businesses can draw insights from many sources online. Data integration merges business insights drawn from these sources, allowing you to work efficiently. Without data integration, businesses need to toggle between different systems to interpret all the data they collected. This process is counterproductive as it is time-consuming and also paves the way for disoriented data interpretation.
For example, an email marketing executive has access to data collected by the email marketing software. In this scenario, the sales, and marketing team have little idea about the insights gathered from the email marketing tool. Typically, the sales and marketing department uses a customer relationship management (CRM) tool to collect valuable customer information.
What is the issue here? You guessed it. The email marketing team cannot access the data gathered by the sales team and vice versa. Data between both teams is shared manually through emails, phone calls, and spreadsheets. Sounds like a nightmare right?
Data integration bridges this gap and addresses this challenge. Users can share information without hassles. Different departments have access to data collected from all sources, eliminating mistakes, confusion, and all forms of discrepancies.
Challenges with data integration
Data transformation, or transforming one type of data into another for it to be read by an application, is one of the biggest hurdles in any project which involves data integration. There are multiple stages involved in this complex, and resource-intensive procedure.
Selecting which components should be changed, collecting component information, creating a mapping document to convert data, importing or extracting component details, and conducting tests to assure accuracy are all highly time-consuming steps in data integration.
Incompatible APIs (application programming interfaces) between different applications and scalability issues that surface as businesses expand are other challenges tied with data integration.
Using business data insights; why is it important?
No doubt using business data insights offer significant benefits. Did you know that around 63% of businesses claimed that data analytics was pivotal to gaining a competitive edge over their competitors?. Besides, these firms could work better, harder, and be more competitive with data analytics at their disposal.
Benefits of using data analytics in business
After understanding what exactly data integration is and the importance of business data insights, let’s look at the benefits of data analytics.
While there are many benefits of analytics in the business world, we are going to focus on just a few in this article.
1. Better and precise marketing
Data analytics enables businesses to get a much better understanding of their target audience. It efficiently clears the grey zone around what their customers are looking for. Therefore, it allows them to create and deliver different marketing campaigns for different segments of their audience. Data analytics in business lays the foundations for better and more precise marketing.
2. Increased productivity and efficiency
Data analytics allows businesses to organize their core processes. This results in higher productivity levels and also boosts the overall efficiency of the business. How?
With analytics, businesses can manage their resources, understand their finances better, and identify the key areas for improvement.
3. Better decision making
One of the major reasons for using data analytics in business is to improve decision-making. Businesses should have clarity regarding why certain decisions are taken.
Say, a company intends to launch a new line of footwear in December. Is it a good time to launch a new product at that time of the year? What sales are they expecting? What form of online advertising will attract maximum eyeballs? Data analytics answers all these questions, enabling better and improved decision-making.
4. Customer service
Despite creating the best products and offering the best services, companies may still lose customers. But why? This is because other brands provide seamless customer service and go above and beyond to ensure their customers have the best experience.
Since data analytics offers deep insights into customer preferences, brands can create a personalized experience for each audience member. Besides, since the customer service teams have access to in-depth customer insights, they can offer better help to every customer.
How can businesses use data analytics?
After exploring some of the major benefits of using data analytics in business, it is a good idea to examine how organizations can apply it. Because of the sheer volume of data, businesses may struggle to take the first few steps toward the successful integration of data analytics.
Therefore, it is a good idea to take a look at how businesses can use data analytics. What are the other factors they must consider throughout the data analytics life-cycle? Let’s find out.
Before moving forward with data analytics, businesses ensure that they have a long-term strategy in place and specific goals in mind. They must evaluate the following questions concerning their data requirements: Specifically, why (to learn more about customer engagement, for example) and what they intend to accomplish with the data they collect.
Businesses need to decide which data sources they’ll use, which data points they’ll focus on, and how to gain that data after they are clear in their minds about the reason for employing data analytics. While some businesses use transaction and social media data, others employ high-tech sources such as GPS and RFID chips.
Accuracy of data collected
We previously mentioned that at first glance, raw data tells us very little. Businesses must make sure the quantitative data they gather is relevant and that they can interpret it. Simply collecting huge amounts of information isn’t helpful and may even be counterproductive.
Using data correctly
Businesses that aspire to use data analytics must carefully evaluate how they will accomplish so and allocate adequate resources for the task. What indicators do you wish to use? Some businesses have in-house data analysts, that offer them an edge over rivals. However, smaller businesses may not build in-house teams due to budget constraints.
Data visualization allows companies to clear the clutter and represent data concisely. When businesses deal with large volumes of data, they should ensure they present the same in such a way that all relevant stakeholders can comprehend it easily.
There are plenty of business analytics tools to choose from. Tableau, Qlik Sense, Microsoft Power BI, and Datawrapper offer interesting features that enable you to present data as charts, tables, and more.
Again, gathering data becomes counterproductive if you do not know what to do with it. Hence, companies should create a plan of action and make good use of all the data they collect.
Data analytics technologies in business
Businesses can pick from a bunch of data analytical tools to use data analytics. Here are some of the most extensively used data analytics technologies worldwide.
- Predictive analytics
- Data management
- Data warehousing
- Machine learning
While we will not elaborate on each technology in this article, you can check out our blog which offers amazing insights into machine learning.
Data analytics is increasingly being used across different business sectors worldwide. Companies that have identified the importance of leveraging precious business data insights to their advantage have established a solid position in their industry.
Despite the notable advantages of using data analytics in business, many firms are skeptical about integrating it into their routine. While that trend is gradually changing, it could a few years.
Data analytics in business is important to stay clear from the competition, understand customers, identify problem areas, and eventually expand the business. As companies continue to focus on digital transformation, the adoption of data analytics tools is likely to grow in the upcoming years.
What are your thoughts on data analytics? Does your company use analytics? We would love to hear from you.
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 (2018) “83 percent of enterprise executives say they’ve pursued big data projects to gain a competitive advantage” Forbes [online] Available from: https://www.dataideology.com/data/83-percent-of-enterprise-executives-say-theyve-pursued-big-data-projects-to-gain-a-competitive-advantage/ [accessed August 2022]
 (2020) “Why Data Analytics?” Visioneerit [online] Available from: https://www.visioneerit.com/services/data-analytics [accessed August 2022]