With the advancement in technology and the desire of many businesses to stay at the forefront, there has been an increasing need for organizations to utilize data analytics for decision-making. Meanwhile, this can be especially difficult in a society where intuition is romanticized and many individuals rely on their guts to make a decision. According to a study, about half of Americans rely on their instincts to tell them what’s true, even when there is evidence presented to them. While studies show that intuition can be helpful, basing organizational decisions on just the gut can be a very big mistake.
In this article, we discuss what data analysis is, the types and its benefits for decision-making.
What is Data Analysis?
Data should be at the heart of decision-making in every organization. By leveraging digital insights on your data, you embrace business intelligence and as such, you can make strategic decisions that will lead to increased growth and transformation. Data Analysis involves analyzing and interpreting data to draw insights and patterns that can tell you something meaningful about what you should be doing in a particular aspect of your business. Data-Driven Decision Making involves making decisions backed by relevant data rather than just on guts or observation. This entrepreneurial strategy is applied in different organizations and fields including healthcare, transportation, and telecommunications.
Data analysis is also becoming popular amongst many big and small companies, as data adoption increased from 17% in 2015 to 59% in 2018. These companies, according to reports, saw an increase in profit, productivity and cost reduction. Using Data to Make Smarter Decisions
There are so many talks about data analytics, but how exactly can one use it to drive growth and decision-making? Many people who have heard of big data understand the importance of data analysis, but when it comes to obtaining relevant insights to drive growth, they reach a wall.
To better understand how to use data to make decisions, it’s important to know the different types of analysis and what they do. There are 4 types of data analysis used across different industries and these include:
● Descriptive Analytics ● Diagnostic Analytics ● Predictive Analytics ● Prescriptive Analytics
All these 4 types of analytics can help improve decision-making and below, we explain the key things you need to know about how they are utilized in decision-making
Descriptive Analytics
Descriptive Analytics often answers the question ‘what happened?’ It is recognized as the simplest and the foundation of all types of data insights because it gives details about what happened in the past or what is currently going on. The insights from descriptive analysis will tell an organization if something is going wrong (or right). Descriptive is also often used to track the Key Performance Indicators (KPI) which describes how a company is performing against a benchmark. A real-time example of descriptive analytics is Google Analytics which provides an overview of what’s going on with a website including the engagement, the number of people who visited, the time, location, and other information. However, findings from this type of analysis don’t explain why something is wrong and as such, it isn’t a good idea for data-driven companies to base decisions on descriptive analytics alone.
Diagnostic Analytics
At this point, we are asking, ‘why did it happen?’ After getting findings of what happened, you can dive deeper to know the causes of what happened with the diagnostic analysis. Many data-driven organizations often combine this with descriptive analytics to have detailed information about what happened and why. For example, if descriptive analytics showed that the people who visited your website in September dropped by 10%, conducting diagnostic analytics will show why this happened. A diagnostic inspection could show that the link on your social media page is broken, or maybe your audience finds it difficult to load your page.
Predictive Analytics
Now that we know what happened, and the causes behind the outcome, we can now use the data available to predict likely outcomes. In a world that is uncertain, being able to forecast what will happen can improve decision-making significantly. Predictive Analysis focuses a lot on statistical models and machine learning tools, which makes it more tedious than descriptive and diagnostic analysis. The question this form of analysis answers is, “what is likely to happen?” And it is the point many organizations have difficulty. Prescriptive Analytics
This is the type of analysis many organizations aim for as it answers the questions ‘what do I need to do’? Meanwhile, only a few are equipped to perform it effectively. Prescriptive Analysis is a combination of all the insight gotten from previous analysis to understand the step to take during a current situation. It recommends the next course of action, and it requires effort, resources, and a huge commitment from the organization. At the moment, some of the big data-driven companies that utilize prescriptive analytics effectively to improve decision-making include Apple, Netflix, and Facebook. These companies utilize Artificial Intelligence to collect data, analyze them and then use them to make informed decisions.
How Data-Driven Decision Making Can Help Your Business
Lufthansa, the second-largest airline company in Europe at one point, had no uniformity across their over 500 subsidiaries. To solve this, they decided to use an analytics platform across all subsidiaries, and their efficiency increased by 30%. By using analytics, the company was able to make informed decisions that empowered the organization,
From growing sales to making better decisions, the benefits of data-driven decisions in big organizations are so vast. Some of the benefits of data analysis for decision-making include;
1. Make Better Decisions
Collection and data analysis can help make more confident decisions in any current problem or challenge. Whether its workforce planning or product launch, the availability and analysis of data allow you to understand the impact of any decision you make. Also, with data, a business can respond to market changes faster, detect new opportunities and make decisions that put them at an advantage in the market.
2. Cost Savings
Data-driven decision-making can reduce costs as managers and leaders can make cost-saving decisions through data insights. A recent survey of 1,000 executives showed that one of the reasons some businesses invest in big data initiatives is to reduce expenses. Since using data already improves productivity and efficiency, there is good chance organizations can also save on costs.
3. Greater Transparency and Accountability
Data-driven decision-making ensures that every data and information is prioritized and outcomes are measured accordingly. This improves transparency and accountability in organizations, thereby boosting teamwork and competency of staff.
4. Serves Customers Better
Data analytics can help businesses predict and understand consumer behavior. For example, some organizations use data to find out more about their customers and then, they use this information to address their needs effectively and improve their experience.
5. Grow Sales
Every business wants to be successful and maximize its revenue. Data gives the insight to identify revenue opportunities, things to do better and how to improve performance and sales. For example, if a product isn’t doing well, a leader can use data to identify what's wrong and develop strategies to improve its desirability to consumers.
Conclusion
Analysis of the proper data with the proper application for interpreting it is an essential part of running a business. It helps a company understand the past/present performance and helps to make better future decisions. Therefore, businesses, no matter the industry they fall in, need to stay focused on data analytics to increase productivity and stay at the forefront.
Now that you are familiar with data analytics and its types, what type of analytics do you think your business needs?
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