How does data science help business? If this is also the question in your mind, then you will want to read this post to the end!
In an increasingly global marketplace, it is more important than ever for businesses to use any edge available to them. From refining best practices to adopting new marketing strategies as markets change, there are many decisions that can make or break business growth.
The good news is that there are ways to make these decisions less mysterious. Data science can help you understand why something needs to change as well as how changing it impacts your business. We will consider all that in this post. Just keep reading!
First, What Is Data Science?
Data science refers to the practice of collecting, interpreting, and analyzing data. That might sound fairly straightforward, right? As you might expect, there are varying degrees of complexity. Collecting information can include intricate machine-learning algorithms, for example, and the data to sift through might encompass multiple terabytes. Data scientists, the data science experts, have multiple functions in businesses in almost every field.
Data scientists are important for businesses, specifically, in a number of ways. They are responsible for interpreting a large volume of data, for example, as well as ensuring that the data collected is accurate.
They do this to help leaders make data-driven decisions for the good of their organization. Data scientists use data to test and develop hypotheses, assess financial risks, analyze market and customer trends, recognize cybersecurity threads and adopt proactive practices, and even keep track of equipment maintenance needs.
Data science is perhaps primarily used to identify customer characteristics, needs, and wants. Data scientists analyze data to reveal insights into their target audiences. This includes information used to identify new opportunities for increased revenue, predict customer behavior, and detect fraudulent transactions.
You will also find data scientists doing the same for academic institutions, healthcare providers, sports teams, and government agencies, among others. The field is important in many industries, in fact, and is growing at a rate of 36% according to the US Bureau of Labor Statistics.
Simply understanding data isn’t enough to create a truly effective data scientist, however. They must have certain qualities to prove invaluable to businesses.
What Characteristics Should Effective Data Scientists Have?
We’ve already discussed the professional responsibilities some data scientists have, but we have spent less time on the soft skills they need to possess. First and foremost, they must be able to communicate well.
The most effective data scientists will be able to explain their work clearly and in terms of business opportunities. Data disclosed to company leaders must be relevant to the business, in other words, rather than tangentially related. This means that data scientists must understand the ins and outs of the business in question and its overall business goals.
This is especially important in positions where data scientists are expected to interpret data for non-scientists. It isn’t as simple as handing out a table full of data and moving on.
Many people don’t understand how data science works, much less how to read a table of data and draw conclusions from it. Data scientists must be able to explain the connections they’ve found and what they mean for the business in practical, easy-to-understand terms.
Let’s say that a data scientist works at a large clothing retailer and has been tasked with identifying trends in the market. When they give this information to upper management, they must be able to talk about what those trends mean.
Who do they affect and what items do they encompass? How can the business use these trends to increase revenue? Effective data scientists can take raw data and turn it into answers.
What Training and Education Should Qualified Data Scientists Have?
Different data science jobs have different educational requirements, but the vast majority of them require a formal college education. A 2021 annual survey conducted by Kaggle, a Google subsidiary, found that while 30.1% of survey respondents had a bachelor’s degree, roughly 62% had advanced degrees.
The most common of these degrees, attained by 47.7% of respondents, was a Master of Science in Applied Data Science and Data Analytics Online degree, such as the qualification offered by Kettering University.
If you’re looking to pursue a career in data science, this course is not only valuable as it is formally recognized but also as it offers transferable skills to prepare you for various challenges you may face throughout your career.
How Does Data Science Help Businesses Grow: 7 Important Ways
It’s probably clear at this point that data scientists are incredibly important to the business industry. It can still be difficult to envision the practical applications of data science on business success.
From strengthening management to attracting talent, here are some of the ways data science helps businesses succeed. Now let’s see how does data science help businesses grow.
#1: Recruiting talent
The first way data scientists help a company is via recruitment. Many industries are saturated with qualified candidates, and sorting through hundreds of resumes can be difficult. This sometimes means that the perfect fit is overlooked. Data scientists can help prevent this issue.
A candidate’s resume used to be the main, if not only, factor in hiring. Today, that couldn’t be further from the truth. There is now an immense amount of data to sift through, including social media, job search websites, and corporate databases. All of this information can be used to narrow the candidates down to those who are best aligned with the company’s values and goals.
Data scientists can also help analyze data-driven tests and games designed to measure candidate aptitude for the job. These even further reveal the perfect candidates from a sea of applicants who are a good fit on paper but sometimes lack the important skills needed to thrive.
#2: Empowering management via better business decisions
The next way data scientists help businesses thrive is by empowering their workers to make smart decisions. They do this in a few different ways. First, data scientists collect and maintain a database of analytics. Upper management, in particular, can ensure that they are up to date with the latest data and use that data to make decisions.
Data scientists make this easy by demonstrating the value of the data specifically in helping the decision-making process. Tracking, recording, and measuring performance metrics, for example, tell management in real time how their decisions are impacting the organization.
#3: Testing business decisions
In addition to enabling leaders to make data-driven decisions, data scientists can also help leaders understand the impact of those decisions. They do this by collecting information about performance metrics after the change and comparing them to those same metrics pre-change. Data about other areas relevant to the decision can also be collected and measured.
A business that changes the way they advertise, for example, might collect information not only about sales performance pre- and post-change but also about customer satisfaction. They can even sometimes collect information about why customers find the advertising attractive or not.
With this information, businesses can even further refine their advertising strategies to better appeal to their target audience. Businesses hoping to expand into new markets can do this to discover effective marketing strategies there, too.
#4: Recognizing opportunities
It can be difficult to break away from established best practices and business operations. This has become a particularly important issue for some businesses, in fact, with some organizations stubbornly holding on to strategies that no longer benefit them. Luckily, data science can come to the rescue here – as long as upper management pays attention to it.
Data scientists collect data about existing assumptions and processes and then analyze them to see where there is room for improvement. These areas of improvement present opportunities for increased efficiency and better productivity.
Note that data scientists can also make it easier for staff to adopt changes. They can provide data to prove that changes are working as well as how they impact the organization.
This information often makes it easier for staff to understand why they are being asked to change the way they work. Once they understand why they have to make tweaks to their processes, they are often more receptive.
#5: Identifying target audiences
In order for a business to thrive, it must understand to whom it is selling. What does the population need that they provide? What pain points can they address to attract new buyers (or users) and keep returning customers loyal to the brand?
Before these questions can be answered, the brand in question must understand its target audience. It is not enough to have a vague understanding of their buyers, either. It must be able to pinpoint exactly why they are buying.
As you might suspect, gathering and analyzing this information is a data scientist’s bread and butter. They collect data about buyers, including demographic information such as age, education, job, and family status. All of this information can be used to help refine marketing and advertising strategies.
Even beyond more general information, data scientists can help determine why people are buying. This is done either by creating questions customers answer at checkout or by analyzing the frequency of purchases. The latter can be cross-referenced with demographic information to identify trends.
#6: Increasing security
In addition to helping businesses in more obvious areas, data scientists can also help boost security. Banks might use information about a user’s normal financial activities and use it, in combination with intricate machine-learning algorithms, to determine fraud. In fact, this is the more accurate and efficient way to recognize fraud.
Data scientists can improve security in more industries than banking, of course, although the methods vary. Implementing effective encryption, for example, helps maintain the data privacy of an organization’s customers.
They might also implement a strategy similar to the banking strategy discussed above. This machine-learning algorithm might track how employees typically use customer information and identify potential misuse.
Because the customer data collected is so sensitive, including medical information, credit card details, and social security numbers, depending on the business in question, it must be protected at all costs. Data scientists can help keep customers safe and, in the process, protect businesses from potential legal action over data fraud.
#7: Predicting market trends
Businesses aren’t impacted only by internal decisions. Properly identifying a target audience and streamlining business methods are important, but so are outside trends. Let’s say that you run a baking business with a variety of products on the menu.
Every day, you must decide the quantity of each product to make before opening your business. This decision is largely made by reacting to customer wants — but what if there is a way you could attract even more customers or meet rapidly increasing demand before it hits you?
Data science is also important here. Identifying trends makes it easier to predict and proactively react to customer demands. Maybe the popularity of hot chocolate bombs is rapidly increasing, for example, but you typically don’t offer the product.
If you have enough notice of the rising demand, you can add the item to your menu. This will inevitably lead to more customers searching for the product, and might even lead new customers to your shop.
Instead of waking up and finding that customers overwhelmingly demand one specific product — a product that you have made too little of — trends means you can plan ahead. At the same time, they can help you decide if increased demand is temporary, perhaps tied to local events or a trend that will grow for a while.
Maybe your community runs an annual bake sale, for example, and you see a rise in the demand for chocolate chip cookies, which happen to be a community favorite. Instead of preparing for a long-term rise in chocolate cookie demand (and ordering the supplies to meet long-term interest), trend tracking can help you identify small “blips” on the radar.
Final Note on How Data Science Help Businesses
What do you think about data science? The field is only growing in importance, with the employment of data scientists rising as more industries note the benefits of making data-driven decisions.
It is an excellent industry to enter as long as you are ready to earn an advanced degree for the best-paying positions. Keep the information above as you consider career options, and you’ll find the perfect fit before you know it!