What is a data strategy, and why is it so essential for every business?
Data strategy can help minimise risks, increase operational efficiency, identify customer insights, and create competitive edges.
Did you know that every single online activity can contribute to the volume of global data creation? For example, finding information on a search engine, checking and replying to emails, browsing websites, using mobile applications, sharing information and making connections on social media platforms, etc.
In 2010, the first Techonomy conference took place at Lake Tahoe, California. At this event, Google CEO Eric Schmidt revealed incredible statistics: “Every two days we create as much information as we did from the dawn of civilisation up until 2003”.
Nowadays, with around 5 billion active internet users, have you ever wondered how much data is generated every minute?
As the amount of data continues to multiply daily, the future belongs to companies that can leverage an innovative data-driven approach. When data is put at the heart of a business, it considerably benefits its decision-making process.
Instead of intuition, observation, or guesswork, decisions are made based on the insights of verified and analysed data.
What is a data strategy?
If you are running a business, your company is sitting on large volumes of data. Previously, this free and available resource was only considered a by-product of a business process.
It had limited value and was rarely re-used after the process was complete. Fast-forward to the fourth industrial revolution, the vision has changed significantly.
Nowadays, data has become one of the most valuable corporate assets. Yet, the raw data itself won’t become the guiding light for business and unlock its hidden power. That’s where data strategy comes in.
This term refers to a comprehensive plan or roadmap that a company develops and implements to gather, identify, store, analyse, and govern data to achieve its overall business objectives.
Why is a data strategy important?
Companies can benefit from data in a variety of ways. Below are the four most important reasons a company should adopt and implement a data strategy.
#1 Minimise risks
With the ever-increasing complexity of business models and advanced technologies, and the ever-changing regulations enacted by policymakers, companies are facing significant challenges and potential risks. How data strategy roadmap can help identify and minimise risks?
A specific answer to this question may vary depending on different industries. However, in general, leveraging multiple data science techniques enables companies to:
- Resolve data-related issues such as data silos, quality, privacy and security, etc.
- Ensure compliance with regulations;
- Use analytics to detect and limit fraud;
- Build systems to prevent theft.
#2 Increase operational efficiency
Operational efficiency reflects the relationship between a company’s input (the production expenses) and output (the revenues). No matter whether it is a family-owned or multinational one, managers always make every effort to minimise resource waste. Thanks to that, the company can operate more cost-effective, which results in greater efficiency.
A robust data strategy can help companies to:
- Detect unseen bottlenecks which lead to slow and inefficient processes;
- Connect workflows and enhance collaborations between different departments;
- Automate processes and streamline complex operations;
- Ensure the effective allocation of resources;
- Drive smarter decision-making;
- Increase productivity and profitability
#3 Identify customer insights
In an increasingly customer-centric world, the ability to gain customer insights is the fundamental foundation for most sales and marketing activities. The more a company understands its customers, the better it can personalise products and services. Obviously, customer satisfaction is a key to any company’s success.
Fortunately, there are a variety of sources a company can collect data. For instance, day-to-day business transactions, customer history, media platforms, mobile applications, and so on. An effective data strategy can enable companies to interpret data to get a whole picture and understand customer behaviours: What are customers’ wants and needs? How often do they buy a new product? What price are they willing to pay?
#4 Create competitive edges
“If I look at enough of your messaging and your location, and use artificial intelligence we can predict where you are going to go,” Schmidt said in the Q&A part of the first Technonomy conference. His statement provides a brief explanation of how a data strategy framework can support companies in creating competitive advantages.
When data is put in a specific context for analysing and interpreting, it provides hidden insights into customer-related patterns. As a result, a company can truly understand why a customer is doing what he is doing. Knowing what customers want before they even know themselves provides companies with endless and exciting opportunities for predicting future outcomes and market trends that their rivals are unaware of.
What should be included in creating a successful data strategy?
Until now, virtually every company acknowledges the importance of adopting a data strategy. However, many of them are still in the early stage of adoption: try and fail, but never fail to try. That is the reason why most of them don’t really understand what makes an effective strategy.
In fact, many companies adopt data as just one aspect of a technology project. As a result, they are excited about pursuing state-of-the-art technology even though it isn’t suited to them. Technology is not sufficient enough to implement a successful data management strategy. There are other important elements that need to be considered such as business goals, human resources, and processes.
Each of these elements will be discussed in detail below.
#1 Business objectives
No matter how well your process, technology, and human resources are, all become meaningless if it does not serve overall business goals. Thus, a chief data officer (CDO) must ensure that both long-term and short-term data strategy goals must be clear, measurable, and aligned with the current company’s objective.
The company objective, for instance, is to cut off as much resource waste as possible. In that event, a CDO should set a data strategy that helps to automate manual and repetitive tasks. These tasks are obligatory but add no value to the company. Automating processes helps to reduce the number of staff needed.
#2 Processes
When it comes to the data strategy roadmap, it will be an omission without mentioning processes. A process will vary according to business requirements. However, in general, to ensure high-quality and security of data used across an organisation, the process typically involves five stages:
- Gather: How, what, and where is data collected?
- Identify: How will data be identified?
- Store: How to store data for easy access and sharing?
- Analyse: How to interpret data into insights to achieve business goals?
- Govern: How to shape behaviours around data quality, security, and privacy?
#3 Human resources
Human resources are crucial in creating a successful data strategy. To facilitate collaboration and avoid duplication, a company should pay attention to defining and managing data roles. Who is responsible for collecting, identifying, storing, analysing, and governing data?
Not everyone in an enterprise uses data in the same way and for the same function. Thus, there will be a variety of data roles for each different stage mentioned in the previous section: For example:
- A data entry is responsible for gathering and inputting the information into a database system.
- A data architect is tasked with designing the physical structure of the data framework.
- A data scientist’s duties include conducting data testing and experiments, developing predictive models, algorithms, etc.
- A data analyst will specialise in analysing and interpreting data into insights.
- A CDO is a C-level executive who will involve in a wide range of strategic data activities.
In reality, there is often overlap between these titles. They also vary from company to company.
#4 Technologies
Of course, technologies play a vital role in the success of a data strategy. However, before investing in fancy software, ensure that you have a good overview of the company’s pre-existing infrastructure and technologies. Then, consider whether you can leverage the existing tech ecosystem, update and innovate it, or invest entirely in new technologies.
Become a Data Expert
According to Statista Research Department, the total data volumes created, consumed, and stored can reach 180 zettabytes in 2025. For those who aren’t familiar with data units, one zettabyte equals 1021 bytes. Businesses will need skilled workers who can interpret and understand this data. Data science is a space that can bring endless opportunities for not only employees, but also the businesses they work with.
So whether you are a student looking for career paths or you’re trying to upskill for career progression, there are many data positions that can fit your skills sets and expectations. This industry offers great job opportunities with diverse options, attractive incomes, and long-term growth. If you want to find out more about these opportunities, schedule a call with an industry career consultant today.