The emergence of advanced technologies as AI, Big Data, IoT, Sensors, Additive, Hyperspectrum,… has blurred the core value of digital transformation: Data.

Data is the future of every enterprise

When we surveyed a variety of Vietnamese enterprises in different fields, their top leaders mentioned a lot about data, especially customer data. It means that digital transformation has actually changed businesses’ thinking toward focusing on decision-making in a rational way instead of basing on leaders’ intuition as before. Owning and using big data effectively can help businesses optimize their traditional production and business activities toward:

In the future, in addition to improving the quality of existing business, businesses that own a large amount of user data may open up various ways to create disruptive business models. Take Grab as an example, when starting a business, this is a ride-hailing application model that connects drivers and customers. After possessing a sufficient amount of user data, they began to penetrate into adjacent markets as goods delivery, food delivery, booking applications to cater to the needs of customers who do not want to ride by themselves. And now, what can you find in the Grab app? It’s e-commerce and fintech – a completely different business model from the core model of traditional ride-hailing. As a customer, I prefer to use this kind of one-stop app over downloading multiple apps to my phone, each serving a purpose. And the fact also shows that Grab has grown spectacularly in recent years with revenue growing nearly 300% in 20181

Fishing in the data lake

Maybe you have heard a lot about Big Data, IoT, and AI as the three driven technologies of digital transformation. If you look further into the general picture, you will see that the connection point of all three technologies is Data. If the IoT is built to collect real-time data from sensors/wearables machines…, then Big Data is the collection of all these types of data into the data lake, and from this data set, AI will conduct analysis and make suggestions, and even make decisions on the user’s behalf.

Coming back to the story of data in Vietnamese enterprises, the biggest difficulty that these businesses mentioned, according to them, is how to collect data. They think that owning a large amount of data might help them find certain patterns that can assist in optimal decision-making, so they try to store as much data as possible even when they do not know how to use them. This took me by surprise, but most of the businesses we surveyed gave the same answer. They have a fairly clear understanding of the importance of data but have no idea how data would serve business purposes. The fragmented and manual in data storage leads to a waste of resources and time. At the same time, since data is stored out of sync, it is also difficult to find anything useful out of it.

I do not think finding ways to collect data should be considered the first step in digital transformation. Just like before you decide to catch fish, you need to know what you’re going to do with it. To make it clear, today you are trying to eat fish & chips, so you’ll have to fish, not shrimp, crab or clam. Therefore, you focus on the purpose of using fishing rods and bait appropriately for fishing. As a result, you will be able to eat fish & chips. But if you do not know what you want to eat today, you spend time wandering around the lake to catch something, resulting in time-consuming and not knowing if what you caught is either edible or able to be cooked into what you like or not.

Through this story, I want to remind that you should not fish when you have no purpose unless you like to spend your time and money fishing out of passion. You need to know the purpose of using the data first, then you will proceed to use IoT solutions to pump the fingerlings, water, microorganisms, food to grow data fishes. When the data fishes are big enough, you will need to use AI fishing rod with automatic rotation to catch these fish instead of using a bamboo rod to help reduce fatigue and increase the chances of winning. Big Data, IoT, and AI are just tools for you to achieve your goals.

How to effectively utilize data

When consulting how businesses should digitize, we often refer to the phrase “Begin from The End” – which means that you need to know what your house looks like first, then proceed to build it. This also reflects the spirit of FPT Digital Kaizen – FPT’s digital transformation methodology – that you must define your business strategy and critical operational tasks first, and then define your digital transformation strategy, followed by digital initiatives. So how can we exploit and utilize data effectively? To solve problems like this, we often use a hypothesis-driven approach.

  • Firstly, you need to define the data use purpose. The purpose of using data can be business optimization or creating new value as I mentioned in the first section. For example, you want to use data for optimal price management.
  • Secondly, you need to identify the analysis required to achieve that goal. For example: If you want to use data to manage optimal prices, you need analysis such as consumer feedback on prices, price comparison with competitors, comparisons of suppliers’ price, price comparison of carriers’ freight rates, optimal commission for distributors…
  • Thirdly, you need to identify the data required for the above analysis. For example: If you need to analyze consumer feedback on prices, you need to have data such as: Statistics on the frequency of customer feedback on prices through email channels, calls, at stores, messages…; Statistics of customer feedback in content groups; Response statistics by demographics…
  • Fourthly, you need to define how you need to do in order to collect the above data. For example: If you need statistical data on how often customers respond to prices through channels, you need to review the number of feedback with “price” mentioned in the content and build report from it. This is when technology hits, instead of counting the numbers and rereading customer feedback, you just need to do a few steps on CRM, then statistical data can pop out in seconds. If the system is smarter, it can pull real-time data from the CRM by itself, then generate reports and use algorithms to send push notification to your smartphone to recommend you to act instantly.

Above are 4 basic steps based on hypothesis-driven approach to help you “swim properly” in the huge data lake.

¹Grab 2016-2018 business results, CafeF

Thao Nguyen – FDX Hanoi

Related posts: