Big Data is everywhere, but it would not have any intrinsic value without the actionable insights provided through data science. There isn’t any question that contemporary businesses are drowning in data. According to a report from IDC, bad data costs the U.S. around $3.1 trillion annually.
Further, as a result of the COVID-19 pandemic, many businesses have moved five years forward in terms of digitization – in around eight weeks.
Change is never easy, but customer behaviors and methods of interaction have evolved and will continue to do so. The surge in the use of digital services will become permanent in various ways, shapes, and forms. Even consumers who have shifted to using digital channels for the first time will continue to use them despite components of normalcy returning to businesses. So then, companies need to ensure that their digital outreach and use of data insights are either on the same page as their competition or exceeds it to thrive in the current environment and moving forward.
As a result, data processing and analysis provide tremendous value in terms of enhancing core business applications – especially in a post-COVID world. Let’s find out how.
Harness the advantages of data science for your core business applications
The significance of data science is far from marginal, especially in the Big Data era. Further, there are specific ways you can enhance your core business applications through the application and execution of data science principles. Many companies often overlook new streams of revenue, new ways to provide valuable propositions, and new ways for solving persistent issues. The solution to any of these business components relies on whether your business is ready to leverage data science.
For instance, Lyft, Airbnb, and even Google have many of their core products supported by both data science and machine learning – these aspects are crucial to their overall success. The key is unlocking the insights that will have the most impact on the business.
After this data science foundation is secured, it can lead the way for more machine learning, advanced analytics, and statistical modeling that pushes the envelope in ways a business may have never imagined on their own.
Another advantage of data science is for risk and fraud prevention by using predictive fraud propensity models so that time alerts are sent to ensure right-on-time responses before any damage is done.
Next, data science can help organizations determine where and when their products sell and how to deliver and promote the right products at the right time to ensure the company remains relevant to their target audience.
In addition, personalization is the key to current and future business success. Tech-savvy consumers have higher expectations and much less patience. Data science can truly improve your core business applications by using insights to design the best possible customer and employee experiences. Decision-making processes can be improved throughout the entire organization which also includes tracking, measuring, and recording key performance indicators (KPIs).
So then, what happens next? Well, you can take specific actions based on data insights to strengthen performance, engagement, and organizational profitability. This is about extracting insights to drive relevant action.
Enhancing your core business applications is also about using insights to develop better business processes that then drives quantifiable and data-driven decision making so that your company no longer engages in high-stakes risks. Instead, you can use data models to simulate any variety of potential actions and outcomes.
However, all of these advantages can become even more powerful through testing by using key metrics to quantify the success of your business applications and their full alignment with your company’s objectives. You see, if data isn’t used well, then it no longer proves useful. On the other hand, when you can combine Big Data with other data points to establish important insights, then you can learn more about your end-users and what matters most to them.
With this type of knowledge, you can then tailor your core business applications to create a flourishing environment.
Drive innovation and mitigate challenges quickly. When new market challenges arise, core business applications can impede your ability to respond quickly. Not to mention, your staff requires real-time decision making in the digital age where data will become even more immediate.
How to incorporate data science into your business
Gartner predicts that 90% of core business applications will still be in use by 2023 but with insufficient modernization. Invariably, this issue can contribute to business paralysis in the hyper-connected age and mounting technical debt trying to connect all the disparate legacy tech stacks and silos. Moreover, the security risk will become unmanageable as cyber threats become increasingly sophisticated every year.
So, how do you incorporate data science into your business? You start by asking the questions data science can answer. With affordable storage options and faster computing, you can retrieve outcome prediction in minutes. The sectors where data science application is on the rise include the following:
- Healthcare
- Internet search
- Fraud detection
- Speech recognition
- Gaming
- Augmented reality
- Online recommendations
- Route planning
- Targeted advertisements
Consider the airline industry, where many companies struggle to retain operating profits even before the pandemic. Yet, with data science, airlines are able to identify key areas to strengthen such as:
- Flight delay predictions
- Creating more profitable and relevant loyalty programs
- The most efficient airline routes based on consumer demand
- What types of airplanes to purchase
Another sector to look at would be the use of data science for virtual reality. Remember the infamous Pokemon GO game? Perhaps you’ve played the highly-successful game that took you all over your city collecting Pokemon on walls, in restaurants, and on the streets that weren’t actually there in real life. All of the data involving where to pick locations came from insights gleaned through data science.
There isn’t any doubt that modern businesses are data-centric and must use data science to grow their companies. As the world is on the cusp of global 5G adoption, companies must use the right insights to provide their customers with the most relevant products and services and guaranteed satisfaction.
To illustrate, Airbnb incorporates data science to improve both its services and available facilities. It’s all about finding the hidden patterns to create meaningful analysis and predictions of specific business decisions. Both enterprise and mid-sized businesses can channel growth by transforming raw data into cooked data. Only then, can businesses make the necessary calculations to accurately evaluate performance and then implement the right course of action to mitigate current and future losses.
Walmart collects around 2.5 petabytes of unstructured data from customers every single hour. And, Walmart utilizes data science to derive critical insights from this data such as how many checkout lanes to open during rush hours. Data science is also used to determine customer purchasing habits to ensure the store is always stocked with the most in-demand products, at the right times whether they be seasonal or common grocery items such as cat food and flaming hot Cheetos. In fact, Walmart backs all of its decisions using data science including optimizing supply chain routes.
Final thought
Now you can see how important data science is to business for improving products and services, as well as for predictive analytics. You also can’t deny how efficient Walmart has become through data science utilization. Whether or not data science is the current foundation for your core business applications, it is critical to incorporate insightful data analysis. If your business applications are found to be untrustworthy or to spew dirty data, then the repercussions can quickly lead to profit leaks.
Regardless of where your company lands within the data science journey, reach out to Data Products to find out how we improve lives through data.