We are living with a wealth of information and data like never before. The availability of all this data has enabled businesses to utilise it to their advantage and have a more competitive edge. Companies such as Adobe, Citigroup, Eli Lilly, Microsoft, and Philips have built their focus on wiring a deep understanding of customers into the heart of their business models and their operations. By doing so, they are able to differentiate themselves and remain relevant1. In fact, 83% of CEOs see the value in data and want a data-driven organisation2.
As this becomes more widespread, more businesses are exploring the fields of data analysis and data science. With the aid of artificial Intelligence and machine learning, data analytics is reshaping the business landscape. Its transformative capabilities can guide decisions and forge paths to potential success.
What is Data Analytics?
Data analytics involves collecting, cleaning, processing, and analysing data to extract new and meaningful insights. It can be used to find patterns, correlations, and insights that can help transform businesses, accelerate innovation, and predict future outcomes3. This can then help solve a variety of business problems, from improving customer satisfaction to reducing costs.
With the progression of big data, artificial Intelligence, and machine learning, this process has become more sophisticated, allowing businesses to harness historical data and make data-driven decisions.
Why is Data Analytics Important to Business?
In today's competitive market, businesses need an edge, and data analytics offers just that. It provides evidence-backed insights, enabling businesses to discern market patterns, optimise supply chain dynamics, and troubleshoot business problems in real time. By transforming raw data into meaningful insights, companies can strategise with clarity, assess the supply chain, and solve intricate business problems efficiently. Businesses can refine their product offerings, personalise marketing messages and even enhance customer experience. This leads to increased customer satisfaction, loyalty and a competitive edge in the market4.
How Can Data Analytics Help Business Decision Making?
Utilising Quantitative and Qualitative Data for Insights
Data analytics can be used to analyse both quantitative and qualitative data. Quantitative data is numerical data, such as sales figures or customer satisfaction ratings. Qualitative data is non-numerical data, such as customer feedback or employee surveys. By combining quantitative and qualitative data, businesses can get a more comprehensive understanding of their customers, make well-informed decisions, and develop effective strategies5.
Uncovering Patterns and Trends
Data analytics can be used to uncover patterns and trends in data. This information can be used to identify risks and opportunities for growth, predict future demand, and improve operational efficiency. Analysing historical data isn't about dwelling on the past; it's about learning and innovating for the future.
Reducing Uncertainty and Bias in Decision-Making
Objective data analysis reduces uncertainties or human error, ensuring that decisions are based on facts rather than mere hunches. By making decisions based on data rather than intuition, businesses can reduce the risk of errors for better outcomes6. Data-driven decisions, not influenced by human emotions or biases, can lead businesses to make more informed choices and are more likely to succeed.
Identifying Potential Risks and Mitigating Them
Data analytics can be used to identify potential risks and mitigate them. For example, businesses can use data analytics to identify customers who are at risk of churning and then develop targeted interventions to retain those customers.
An example of a business using data analytics is Grab, a renowned SEA super application. It leverages data analytics to optimise its ride-hailing algorithms, factoring real-time traffic, weather data, users, driver speeds, and routes for better efficiency and accuracy7.
DBS Bank, a prominent Singaporean company, has actively employed data analytics to tailor financial products to its diverse clientele, seeing a notable increase in customer engagement and retention. With a combination of multiple data analytics, artificial intelligence, and machine learning projects, DBS has yielded a revenue uplift of SG$150 million in 2022 and saved SG$30 million in risk avoidance8.
Which Industry Uses Data Analytics the Most and its Impact?
Data analytics is used in a wide range of industries, but it is particularly prevalent in the financial, retail, healthcare, and manufacturing industries9:
- Financial services: Financial services companies use data analytics to assess risk, manage portfolios, and detect fraud. It is also used to develop new financial products and services, such as robo-advisors
- Retail: Retailers use data analytics to understand customer behaviour, optimise inventory levels, and target promotions. This allows retailers to personalise the shopping experience for each customer.
- Healthcare: Healthcare providers use data analytics to improve patient care and identify disease trends. It can even be used to develop new drugs and treatments, as well as to improve the quality of care for patients.
- Manufacturing: Manufacturers use data analytics to improve product quality and optimise production processes.
From healthcare to retail, data analytics is seeing an expansion of its application. This is especially true in e-commerce, where understanding consumer behaviour is crucial. Through data insights, sellers can personalise user experiences, refine their inventory, and boost sales. Multinational corporations and even small businesses harness data analytics to refine their business strategy and predict future trends.
Future of Data Analytics in Business
The trajectory indicates a future where data analysis will be synonymous with business success. As artificial Intelligence and machine learning become more advanced, businesses will have tools to make even more accurate predictions. Whether it’s refining the supply chain, launching a new product, or charting growth strategies, data will be at the helm of decision-making.
The realm of data analytics is boundless, and its potential in business decision-making is game-changing. If you're aiming to be at the forefront of this transformation, consider furthering your understanding and skills in analytics with Singapore Institute of Management’s
Graduate Certificate in Analytics (E-Learning) programme. This online programme opens the door to various analytical tools, and students will get to learn how to make informed decisions and present data in a user-friendly visual format.
Delve deep, decode data, and be the catalyst for unparalleled business growth. Talk to our student advisor today and find out more.
- How to Gain a Competitive Advantage on Customer Insights
- What do data-driven companies have in common? Research reveals five key trends
- What is Data Analytics?
- How Data Analytics Can Transform Your Business | Entrepreneur
- Quantitative vs Qualitative Data: Differences & Benefits
- The Importance of Data Analytics in Business Decision-Making
- Data science brings the smarts to Grab Maps | Inside Grab
- DBS Bank uncovers big data challenges with AI use - and solutions, too | ZDNET
- Data Analytics: 10 industries making big strides and why