The Role of Data Analytics in Digital Transformation

Calford Wong, Writer
Calford Wong, Writer


It is all too easy to get swept into the hype and jargon. But companies cannot avoid digital transformation to remain competitive. As they digitize, data begins taking a more important role as feedback. Without it, transformation is limited.

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Digital transformation is business transformation. Put simply, businesses future-proof themselves with technology to innovate, disrupt and differentiate. Today, even companies at the forefront of technology are transforming themselves. Google has shifted from being mobile-first to being AI-first. Facebook plans to expand its content-driven platform to enable economic transactions with its own cryptocurrency.

Smaller companies need not invest in such drastic changes to stay competitive. They can adopt simpler approaches to improve their operations with technology. One example is the deployment of a guest Wi-Fi at a coffee shop. Customers love it, and when they use the network, data is generated. The store gains insights into how long people are staying and what content is consumed. This feedback can then be used to make decisions about products and experiences that will keep them coming back. 

Data analytics supercharges the transformation journey

Making decisions based on data is a crucial tenet of digital transformation. Your business data is a treasure trove of insight – a raw but rich asset. However, true value can only be obtained after the raw data is sorted, processed and analysed.

More advanced analytics are designed to become smarter over time. Insights generated becomes more accurate and robust for sharper business decisions. Find out more about what data analytics is here.

The many roles of data analytics in digital transformation

Besides the guest Wi-Fi example, data analytics has a variety of uses in digital transformation. Below, we list three common use cases that enterprises of different sizes will find useful.

1. predicting consumer behavior

American Express uses predictive data indicators that analyses historical transactions and 115 variables to forecast potential churn and customer loyalty. The company believes it can identify 24% of accounts that will close within the next four months. By knowing which accounts are likely to close, allows management to make better business and marketing decisions to retain customers.

Improvements in such predictions can be derived through advanced analytics. As machine learning models absorb more data, they can relearn the scenarios multiple times and better anticipate what is the likeliest outcome.

2. Optimizing sales pipelines

Closing deals is the key objective of any salesperson. Hence, shorter sales cycles enable salespeople to increase their sales volumes. However, this is not always the case. Some deals may take a longer time to close than others but may be worth several times more in terms of profit. So how can salespeople optimize their efforts to increase both sales volume and value?

Customer Relationship Management Systems (CRMS) are digital tools that help sales teams track each step of the sales process. By analyzing past data, CRMS like HubSpot and Mailchimp offer users lead scoring features to estimate the likelihood of conversions as well as its potential value. This way leads with higher scores can be prioritized.

3. Streamlining supply chain processes 

Toyota has been managing its supply chain successfully for decades. Before its transformation, the car-maker struggled with inefficient manufacturing cycles and high inventory costs. Once the company introduced the Just-in-time (JIT) system, its staff was able to track stock levels in real-time and automate processes. Underproduction and overproduction issues were resolved, which led to reduced inventory costs. Data Analytics is the linchpin of the JIT system as it enabled companies like Toyota to optimize each part of their supply chain with near perfect accuracy.


Digital transformation is an ongoing process that companies must pursue to remain competitive. When relevant business processes are transforming, there is a need for its success to be measured. Analytics enable companies to monitor the state of their business at any given point. The findings that are derived then allows managers to take the best actions to improve business performance.

If you need help to adopt data analytics for your business quickly and affordably, start a conversation with us today. DataVLT is a PaaS platform that helps enterprises to make meaningful sense of their data. Find out how we can guide your business through its transformation journey here.




The Forefront of Data Analytics — AI Builders of the Future 
DataVLT provides artificial intelligence as an outsource solution. We exist to help enterprises accelerate their growth through digital transformation by way of data analytics. 

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