How Data Science Can Improve Business Efficiency – 10 Ways!

The hype for Data Science has been going around for quite a while now. Large organizations and businesses are jumping into this venture and are incorporating Data Science and Analytics into their pipelines. With all this hype about Data Science and its spread in businesses, a question arises; Does Data Science improve business efficiency? 

Businesses need to ensure customer satisfaction and always provide value. By adopting Data Science, exploring its insights from historical data, and using it to iterate business processes, product innovation and design, marketing strategies and offers, businesses assure happier customers and higher efficiency.

Stats show that the businesses who efficiently integrate data science into their pipelines do remarkably better than their competitors and dominate the rivalry.

So how does it all happen? In what ways Data Science improve Business efficiency? We will talk about it in this article. So, make sure you give this piece a thorough read! Let’s start!

Big Data - Categories, Attributes, ...
Big Data - Categories, Attributes, Applications
What is Data Science?

Data science is a vast and multidisciplinary field that combines the use of scientific methods and algorithms, intending to use data available to make certain decisions and make certain processes more efficient. It also includes the collection, cleaning, modification, and integration of this data. 

Data science lets companies make more organized and data-driven decisions instead of following one’s basic instinct.

What is Data Science in Business?

Data Science in business refers to the collection, management, and processing of business data to analyze customer behaviors and market trends. It makes organizations more data-driven in their approaches, such as decision-making and marketing strategies, etc.

How Can Data Science Improve Business Efficiency?

Data science is all about facts and stats; while the human brain certainly has a limit to the volume of data it can process and make use of at a certain point, machines do not. Data Science enables stakeholders to make data-driven decisions and offers an evolution in terms of management, customer satisfaction, used methodologies, and much more! 

Data Science is not only useful for large organizations; small and midsize businesses can also be greatly influenced by adopting data science practices.

Each subsequent year is witnessing a surprising increase in the amount of data available. So, it comes as no surprise that data science is more needed now than ever before. There are numerous ways data science improves the efficiency of a business.

“Data will talk to you if you’re willing to listen.”

Jim Bergeson.

10 ways Data Science can improve business efficiency

Data-driven companies can do wonders from simple databases to complex machine learning algorithms compared to other companies. The results a company can achieve with efficient Data Science are remarkable. We will list down a few of these; here are ten ways in which Data Science helps improve business efficiency:

Data Science can improve business efficiency

Investing in creating a good data science team and proper collection and maintenance of data revolutionizes a business. We will dive deeper into the subject and see exactly how Data Science adds value to a business in the aforementioned ways.  

1. Identification of trends

For a long time, most decisions being made in businesses were simply a result of the basic instincts of a few top-tier managers based on their experience and simple market analysis. Not only was this heavily dependent on the experience and ability of a few people, but it was also highly vulnerable to missing any small details that are not readily apparent.

Luckily, data science is changing this trend, with many businesses already adopting this approach, known as data-driven decision-making. There is sufficient evidence available to prove that using data science results in a lot more efficient decisions for businesses

According to McKinsey’s Analytic study published in Forbes; U.S. retailer supply chain operations that have adopted data and analytics have seen up to a 19% increase in operating margin over the last five years.

2. Business planning

Setting up a long-term or even a short-term plan for your business isn’t a walk in the park. It is a hefty task that requires precise calculations and extraordinary predictions. To make a strategic decision, there must be proper motivation and reasoning behind it. Data Science enables organizations to make these decisions keeping all the factors such as market trends, historical data, customer needs, demand-supply ratio, and numerous other factors to chalk out the most efficient plans. Businesses can also opt for plans based on the direction they want to excel in. 

Predictive models are highly flexible and enable stakeholders to analyze the impact they would create before deciding. When data is used effectively, and the team is skillful, data science predictions become unbelievingly accurate!

McKinsey estimates that analytics have increased manufacturer’s gross margins by as much as 40% when used in design-to-value workflows and projects.

3. Sharp Eye For Opportunities

One of the primary applications of data science, which we have mentioned above, is determining patterns and trends in data. There are numerous examples of data-driven companies prospering just because they have a competitive advantage over other companies. Data science enables companies to capitalize on new opportunities by foreseeing the trends and demands. This is the most important aspect in which data science increases the efficiency of a company.

EDI (Existent Data Interpretation) is a very powerful tool. When used in the long run, it can provide businesses a way to capture small opportunities that only occur seasonally. Without the help of such methods, these opportunities are very difficult to spot.

Recommended Article: 11 Reasons Why Data Analytics is Important in Marketing

4. Help The Stakeholders Make Data-Driven Decisions

Data science is a stakeholder’s most trusted advisor. Who else would be a better advisor than a Large-scale data-driven Machine Learning model? This personal advisor speaks with numbers and provides evidence-based facts and figures. With data at companies’ fingertips, decision-making becomes easier, faster, and much more efficient. Stakeholders can make quick decisions based on low-risk plans or otherwise based on the confidence of the model.

5. Selection Of Target Audience

The most important thing for a business is its value in the eyes of the audience. If a business is making excellent products, but the products are not creating value for any specific customer segment, it is bound to fail. So, recognizing your potential customer base is one of the foremost tasks a business should focus on.

Luckily, Data science has got you covered in this domain as well! With adequate customer data, data science could provide a business with top-notch predictive models that can help determine the customer base interested in a specific product and their count. In this way, stakeholders can focus on products that are more in demand to increase sales.

Audience targeting through data science is a great way to boost the efficiency of any business, be it a medical store or a toy shop. You do not waste your resources trying to reach customers, and since no company has unlimited resources for marketing or branding, it is crucial to target your audience wisely. Wise targeting can help save an enormous amount of money and time.

6. Better Recruitment Of Teams

For nearly all companies, recruitment drives are long and exhaustive. Even after thorough screenings and interviews, employers are not usually satisfied with the recruits. With data science, this process gets a lot faster and much more accurate. Automatically Extracting, sorting, and shortlisting clients based on their work and tests saves a lot of time for the employers and they can utilize this time to carry out meaningful activities with the applicants rather than scanning through thousands of resumes and checking tests.

Data Science can improve business efficiency

Taking this to the next level, today’s data science models can utilize big data streams into a customized Employee data profile based on their social media presence, work history, corporate profile, etc. Organizations can now recruit new talent with small Human resource teams without making any compromises.

7. Effective Automation

Gone are the days when companies had to spend time performing recurring tasks repeatedly. With the advancement of Artificial Intelligence, data scientists have come up with pipelines to automate the most repetitive tasks and consequently enabled the employees to work on more impactful tasks rather than wasting time on these repetitive tasks.

Efficient automation in companies greatly affects the overall performance. It enables the company to channel all the workforce in important domains rather than spending time and effort on these simple tasks. On the other hand, automated systems are much more accurate and faster in performing these tasks than a human. So, automation results in a win-win situation, making it highly vital for large businesses.

8. Better Advertisement

According to a report, We produce more than 2.5 Quintillion Bytes of data every single day, and 90% of this data was generated in the past two years!

With the data science industry capturing the markets, it will not take long for Newspapers and traditional forms of advertisements to become futile. Targeted advertisements through Social Media are the new and the most effective way to go. 

Recommended Article: Defining the Role of Data Visualization in E-Commerce

Tech giants like Facebook, Google, YouTube, etc., are making fortunes by showing ads to a targeted audience for businesses. On the other hand, well-targeted ads boost the reach and sales of small to large businesses exponentially!

9. Better Customer Experience

Customer satisfaction is the utmost priority of every business, be it small or large. Data Science not only helps strengthen this bond but also helps segment customers based on their preferences. This data can then be used to target and work on specific products to ensure customer loyalty and satisfaction.

Some businesses rely on frequent customer interactions heavily. Hiring large teams for dealing with customers round the clock is very inefficient. This is where real-time reporting comes in; It helps companies to produced immediate actionable insight and considerably improves the response time. Real-time reporting also provides a more meaningful interaction between the customers and service representatives.

10. Increased Efficiency And Commitment

Companies with high-quality data science teams can keep track of minimal signs of progress in sales, reach, customer satisfaction, etc. In this way, they can analyze the methods and techniques being used in real-time. Employees are content about their tasks, and constant updates keep them focused and motivated to achieve their long-term goals.

Is Data Science Useful For Small To Medium-Sized Businesses?

The straightforward answer is a big YES! Small companies that make accurate decisions can benefit even more than large size companies. Data Science helps small to medium-sized companies to make analytical decisions and enter the trend market. It can also help management hire better talent and thereby scale the company and production. 

Data Science can improve business efficiency Small Businesses

Not only this, if businesses incorporate data science into their pipelines and manage their data from the start, they reap the fruits in the long run as well. So, Data science is essential for small to medium-sized businesses and can increase efficiency by a factor! It all depends on how a company chooses to use its data.

Torture the data, and it will confess to anything.”

– By Ronald Coase

Conclusion

Businesses, be they small or large, are often reluctant to adopt the data science culture. According to a study by Forbes Insights, 59 percent of the companies aren’t using data science practices, and 23 percent of the companies are still relying on spreadsheets for their analytics!

In this fast-paced era, businesses that don’t take analytics seriously are bound to struggle in this data war and wouldn’t be able to compete with their rivals. 

So, let go of any misconceptions you have regarding data science, difficulty implementing, change of infrastructure, complexity, etc. Data science can easily be incorporated at a small to large scale in a company and, in most cases, provides exceptional results, especially in the long run. So what are you waiting for? Adopt data science for your business at the earliest!

Emidio Amadebai

As an IT Engineer, who is passionate about learning and sharing. I have worked and learned quite a bit from Data Engineers, Data Analysts, Business Analysts, and Key Decision Makers almost for the past 5 years. Interested in learning more about Data Science and How to leverage it for better decision-making in my business and hopefully help you do the same in yours.

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