Article updated on: 25 February 2025
Many business leaders assume that being a data-driven company simply means collecting and analyzing vast amounts of data. And while these are crucial components, being data-driven goes far beyond that.
Because of this misconception, they often focus solely on investing in data tools or technologies, without considering who will use them and how. However, companies that thrive with data treat it as a strategic asset, embedding it into their decision-making processes, company culture, and daily operations.
In this guide, we’ll outline everything there is to know about data-driven companies and show how being data-driven is just as much about mindset, culture, and business as it is about technology.
Here is everything we’ll cover:
What is a Data-Driven Company?
A data-driven company uses facts, numbers, and patterns to make choices instead of relying on gut feelings and guesswork. By using data to figure out what is happening and predict what might happen next, these companies make smarter, quicker, and more accurate decisions.
For example, consider a company deciding whether to expand into a new market.
- A gut-driven approach might rely on anecdotal evidence, intuition, or competitor activity.
- A data-driven approach, however, would analyze key metrics like market demand, customer preferences, competitor performance, and cost projections to drive the decision.
Notice how technology hasn’t even come into the discussion yet? That’s because becoming a data-driven company is as much about mindset and strategy as it is about the tools you use.
Now, let’s explore the key characteristics of companies that successfully integrate data into their operations.
Characteristics of a Data-Driven Organization
All companies use data. From customer data to sales insights – you probably have heaps of it lying around. However, only a handful of companies can really be called data-driven.
What sets these companies apart is their commitment to making data widely accessible, ensuring employees have the skills to use it, and embedding it into their decision-making processes.
Here are the defining characteristics:
- leaders championing the data-driven approach
- a strong data-driven culture
- availability of data across the company
- high levels of data literacy
- automation of data-related processes
Let’s explore each one in more detail.
Leaders Championing the Data-Driven Approach
People at the head of data-driven companies know they need to lead by example. As leaders, it’s up to them to demonstrate how they use data in their decision-making process and value it as a strategic asset.
But let’s be clear – being data-driven doesn’t simply mean focusing on metrics or key performance indicators. Leaders need to demonstrate their willingness to dive into the data and pull insights that might not be obvious at first. They need to continuously ask questions, challenge assumptions, and make decisions based on the available data.
To sum it up – how you treat data will also influence how your teams do. Leading by example will also make it easier to establish a data-driven culture, a crucial characteristic of data-driven companies. But more on that in the next section.
A Strong Data-Driven Culture
Your company culture influences all aspects of your business, so it’s logical that many data-driven companies have a similar organizational culture. A strong data-driven culture encourages people to consistently collect and analyze relevant information, ensuring that their actions align with overall company objectives.
This characteristic is more about a change in mindset than about processes or technology. Here are a couple of examples that illustrate a strong data-driven company culture:
- When submitting a proposal, people are asked to include clear data that supports it.
- People in leadership positions actively use dashboards and reports in meetings and discussions.
- Colleagues are recognized and even celebrated for using data to make impactful decisions or solve challenges.
As these examples show, by prioritizing data over personal opinions, a data-driven culture fosters better accuracy, accountability, and collaboration across the organization.
Data Is Accessible Across the Company
For a company to be truly data-driven, information needs to be accessible to everyone who needs it. This is called data democratization. When everyone has access to relevant data, the decisions they make are faster and more accurate, helping the business to stay flexible.
This practice also prevents the creation of data silos and ensures there is a single source of truth throughout the organization. However, this does not mean that data should be centralized or that there needs to be a central approver.
When centralization goes too far, organizations end up with a cumbersome approval process which is usually a colossal waste of time and effort. To avoid this, data-lead companies focus on self-service systems when managing data.
High Level of Data Literacy
Data literacy is your team’s ability to work with and analyze data to get meaningful, actionable insights. From this, it’s easy to understand why data-driven businesses give digital literacy a top priority.
Most of these organizations have a company-wide program to help boost their employees’ skills in this area. Gartner reports that 80% of businesses in 2020 actively worked on improving their teams’ data literacy skills.
A high level of data literacy helps teams make better decisions more quickly, but that’s not the only benefit. It also lowers the burden placed on your IT support team as they don’t have to deal with mundane data requests or issues daily. This allows them to focus on strategic activities and lowers the overall IT costs.
Automated Data Processes
Most companies today rely on manually cleaning and checking data – something which MIT Sloan suggests takes up to 50% of their people’s time. So for a company to be data-driven, it needs to take a hard look at its processes around data.
Successful data-driven companies automate their data management workflows, embedding insights directly into their business processes. For example, a retail company might integrate real-time sales data with its supply chain system. This ensures high-demand products are restocked quickly while reducing excess inventory of slower-moving items.
Automating these processes not only allows data-driven companies to save on costs but also enables them to respond more quickly to sudden changes in the market.
Examples of Data-Driven Approaches in Retail and Manufacturing
The path to becoming a data-driven company varies based on your industry, business model, and specific market context. In this section, we’ll explore how companies in retail and manufacturing industries approach this decision, based on their operational realities and competitive landscapes.
Creating Unforgettable Experiences in Retail
Retailers face intense competition and must deliver exceptional experiences both online and offline. With competition just a click away, they are investing heavily in data and AI to ensure they can keep up. Experts predict that AI in Retail market size will grow from $7.30 billion in 2023 to $29.45 billion by 2028.
Our customer, the Douglas Group, leverages a data-driven approach to stay ahead, creating seamless and personalized interactions for every customer. As the leading premium beauty platform in Europe, they are laser-focused on integrating their online and offline channels into a comprehensive customer experience.
By integrating customer data from various sources like websites and social media, we helped Douglas build unified 360-degree customer profiles. This enables them to deliver a truly omnichannel experience while tailoring every interaction to individual preferences and past behaviors.
Taking it a step further, Douglas is now using their first-party data as a new revenue source through their Retail Media efforts. This way, they offer brands the chance to engage with customers while they are in a buying mood, resulting in much higher conversion rates.
With these tools, Douglas creates unforgettable retail experiences that set them apart in a competitive market.
Driving Efficiency and Growth in Manufacturing
With B2B buyers expecting seamless, consumer-like experiences, the manufacturing industry is turning to data-driven strategies to streamline operations, improve customer satisfaction, and drive growth.
One of the biggest shifts in manufacturing has been the adoption of digital self-service platforms. By automating low-value tasks like managing orders, tracking deliveries, and updating inventory, they can lower operational costs and improve overall efficiency.
The use of AI in manufacturing is another approach that companies have adopted to help them cut costs. For example, companies can automate routine customer service inquiries, such as answering questions about shipment status or product availability. This frees up customer support teams to tackle more complex and strategic issues, ensuring customers receive faster and more effective service.
The combination of digital self-service and AI creates a ripple effect across the organization. By automating repetitive tasks, manufacturers see lower overall costs and improved workflow efficiency. At the same time, customers benefit from more reliable, responsive service, which improves their overall experience. These improvements ultimately lead to increased revenue and stronger customer relationships.
Benefits of Being a Data-Driven Organization
There are many benefits associated with becoming a data-driven organization. From differentiating through stellar experiences to capitalizing on the latest AI solutions – business benefits are the true reason why companies decide to go through the transformation.
In this section, we’ll outline the biggest benefits we see in our work with customers:
- increased efficiency and cost savings
- higher customer satisfaction and loyalty
- improved decision-making
- greater organizational agility
We’ll spend some time going through each one.
Increased Efficiency and Cost Savings
In the current economic environment where every cent counts, being able to cut operational costs by as much as 25% sounds like a dream. But that’s exactly the kind of improvements data-driven companies are seeing.
By relying on data, these companies can pinpoint areas where resources are being wasted and streamline their processes. For manufacturers, this can happen through a more efficient use of raw resources and reduction of waste.
On the other hand, automation solutions powered by data help reduce repetitive tasks, saving both time and effort and allowing them to focus on what brings value. Retailers, for example, can lower the costs of their customer support operations by offering self-service options to customers and creating automated workflows for their teams.
Overall, leveraging data allows businesses to operate smarter, not harder, resulting in lower costs and better use of resources.
Higher Customer Satisfaction and Loyalty
A McKinsey and Co. research has shown that data-driven organizations are:
- 23 times more likely to acquire customers
- 6 times more likely to retain customers
- 19 times more likely to be profitable
So, how do they do this? Easy – by keeping their customers happy.
If you know what your customer likes, needs, and wants, you can make sure you are always there to provide. Even if they become unhappy with your business at some point, a data-driven approach allows you to understand the cause and offer something they would value before they leave you for a competitor.
Remember that the key here isn’t gathering the data – it’s in the analysis. You need to bring together data from disparate channels and touchpoints and unify it into a single customer profile before you can begin to truly understand your customers.
Improved Decision-Making
Data-driven decision-making (or DDDM for short) relies on facts and hard data instead of your gut or intuition when making decisions. When embraced fully, it allows everyone in the company – from salespeople to HR – to make better decisions.
Being data-driven also allows you to learn from the past more easily, as you keep going back to historical data and your old decisions. It lowers the chance of making the wrong decision, and even when you make one, it helps you recover faster afterward.
By abandoning guesswork and gut feeling in favor of data and facts, you create more clarity throughout the organization and give your people more confidence when making decisions that are crucial for the business.
Greater Organisational Agility
As your teams get used to making decisions based on data (increasing the amount of information they can process), the decision-making across your organization becomes faster – leading to a more flexible business.
When market conditions change, your teams can quickly pivot based on the newly available data. The increased agility helps you stay ahead of the competition and reap the benefits of being an early adopter or the first market entrant.
But that is not the only advantage. Since everybody in the organization has access to the same data (remember, data democratization is vital), there is less need for constant alignment meetings and cumbersome approval processes.
How to Become a Data-Driven Company
Based on everything we’ve covered so far, you might assume that becoming a data-driven company is a painful and overwhelming process. But with the right planning and focus, it doesn’t have to be.
In our work with customers, we advise them to adopt an iterative approach – one that encourages experimenting and continuous optimization. By going step by step, you make the transition smoother and more effective, while being able to learn from past mistakes.
Here is our process to becoming a data-driven company:
- asses your data maturity
- define your data strategy and governance
- build a data-driven culture
- improve the level of data literacy
- implement the right technology
Step 1: Asses Your Data Maturity
The first step to becoming a data-driven company is assessing your current level of digital maturity. This evaluation will help you understand how effective the company is in collecting, integrating, and using data – crucial for setting priorities and allocating resources for the whole process.
Some of the questions we ask our customers during this process are:
- Do you have access to the data you need, and is it reliable?
- Are your data sources integrated, or do you struggle with silos and inconsistencies?
- Do you have clear KPIs and metrics tied to your business objectives?
Once you’ve gone through the evaluation, you’ll have a clearer picture of your organization’s strengths and weaknesses. This will help you plot your path from your current state to your desired future state – something we will talk about more in the following chapter.
Step 2: Develop a Data Strategy
Once you know where you are, it’s time to decide where you want to go – and a good data strategy will help you do that.
Put simply, a data strategy highlights how data supports your overall business objectives and identifies the challenges and opportunities related to data. Based on your company’s size, this can be a relatively simple task or a complex process that needs to include your data experts.
Three key areas in your data strategy are:
- Ownership and Roles: By establishing clear roles and responsibilities, organizations can ensure accountability, streamline workflows, and maintain consistency in how data is managed and used across teams.
- Data Quality Standards: By establishing clear protocols for maintaining data quality, organizations can minimize errors, reduce inefficiencies, and build trust in their data.
- Security and Compliance: Organizations must ensure their practices align with regulations such as GDPR, CCPA, and other industry-specific standards to protect sensitive data and maintain user trust.
A good data strategy always includes a series of steps designed to help you achieve your objectives. By thinking ahead to the execution, you are avoiding the common mistake of setting unrealistic goals or defining a strategy without a clear way of delivering on its promise.
Step 3: Promote a Data-Driven Company Culture
Before you start thinking about the right technology, think about how your organizational culture needs to change to facilitate this shift toward being more data-driven.
Every company culture is different so depending on yours, there are different areas you’ll have to improve. In our experience, three key factors will make this shift easier:
- Leading by example – make sure people in leadership roles reflect the mindset and behaviors you want your people to adopt.
- Change management – for a smoother transition, answer the age-old question of ‘What’s in it for me?’ by showing people how data can help them do their jobs better and quicker.
- Data literacy – check if your teams have the knowledge to use the data they have available and, in case they don’t make a plan to improve it (more on that topic in a later section).
Of course, organizational culture is a living thing, so you’ll need to course-correct from time to time. Just be sure that the culture you’re trying to implement fits with your overall business and the goals you’re working to achieve.
Step 4: Improve Data Literacy
No matter how big your data team is, you can’t have a data person in every room where decisions are made. So you need to ensure that people making those decisions understand the data and know how to extract insights from it.
Start by assessing the data literacy levels of your teams. There are many ways to do this out there from online assessment packages to customised testing done in-house.
When looking at the results, it’s good to remember that different groups throughout the organization require different levels of data literacy skills. Your graphics designer doesn’t need to know statistics on the same level as your market researcher.
The assessment helps you identify gaps that serve as a basis for defining the objectives of your future data literacy programs. These can take any number of forms depending on your needs – from mentoring programs with your key data analytics and governance people to training programs for specific teams or roles.
Whichever you choose, remember to regularly reassess to measure how successful these programs are and make any potential course corrections.
Step 5: Implement the Right Technology
Once you have gone through the previous four steps, or are on a good path to getting there, it’s time to choose the right technology solution. Which one that is will depend on factors such as your:
- business goals
- industry
- business model
- market situation
As covered in the section about use cases above, a retailer who wants to be in the lead might focus on growing their market share through automated and personalized customer communication. A manufacturing company might opt tostrengthen its relationship with key customers through an intuitive and easy-to-use customer portal.
Whatever you choose, don’t fall into the trap of going for the shiny new thing everyone is talking about. Instead, ensure that the new technology fits not only your business but also your existing digital landscape. After all, the new solution would not be of much use if it can’t communicate with your ERP to access the business data it needs.
In our work with customers, we usually recommend transitioning to cloud computing at this stage. This move enables the storage and processing of vast amounts of data more quickly and efficiently while ensuring you can easily connect new elements to your infrastructure.
Final Thoughts on Data-Driven Companies
Becoming a truly data-driven company is a complex transformation that goes beyond implementing new technologies. It requires new processes and governance, a shift in company culture, and alignment across all levels of the business.
Technology may provide the tools, but the way your team approaches decisions, integrates data into daily operations, and fosters collaboration ultimately defines success.
Navigating this process alone can be daunting. That’s where working with experienced partners can make all the difference.
Our digital strategy consulting services are designed to help you assess your organization’s unique needs, build a realistic roadmap, and implement strategies that align technology with your goals.
But we don’t stop there – we also guarantee that we can work with you to build the technical solution we designed, so it’s not just a slide in a PowerPoint presentation.
Reach out to us today to start your data-driven transformation with the confidence and clarity you need to succeed.
