There’s an old saying: “Even a blind chicken will sometimes find a grain of corn”.
The proverb might be more than 400 years old, but it carries a lesson for business leaders today.
Just like the ‘blind chicken’, if you rely on gut feeling when making decisions you’ll only be right some of the time – when you’re lucky enough. Having loads of experience can slightly change that equation in your favor, but not enough to get you in the lead.
For that you need data. And it’s not just about having it – you need to actively use it and find ways to embed it into your business processes so that your teams start using it as well.
Adopting a data-driven approach – and transforming your business into a data-driven company – is the best way for you to take full advantage of your data and turn it into value.
And yes, this does include using cutting-edge AI and machine learning solutions, as well as data analytics platforms, but they are just a part of a complex caleidoscope.
In this guide, we’ll cover everything you need to know about data-driven companies – what they are, the benefits they bring, and the steps you need to take in order to become one.
Here is what we’ll talk about:
What Is a Data-Driven Company?
As a leader, a big part of your everyday job is to make decisions. These can be simple ones, like approving this month’s marketing spend. But they can also have a lasting effect on your business or teams – for example, if a new market is worth pursuing. That’s why it’s crucial that you make the best one possible and – even more importantly – do it again and again.
Traditionally, leaders made tough decisions based on their ‘gut feeling’. That was back when data was not readily available, and it was customary to rely on experience and a little luck. But this kind of emotional decision-making is notoriously inaccurate and hard to reproduce. So as a result, it often happened that you were just one bad decision away from a ruined business.
However, the rise of data science gave way to a new era where data and information are prized above all else. Companies hoard data in hopes of revealing insights that will get them ahead of the competition.
A recent survey by EY has shown that 81% of interviewed companies understand the importance of data for a successful business. However, most of them fall into a trap here. Because having data is not the same as using it properly – and that’s where data-driven organizations have the edge.
But what does it mean to be data-driven, and how do you ensure your business takes full advantage of your data?
The answer is simple enough – being data-driven means that you systematically and methodically use data to make decisions. In a business context, this means that you ensure that data is treated as a strategic asset throughout the business and used to make informed decisions.
This way, your teams can consider all the variables when making a decision. But, more importantly, they can repeat this process again and again, leading to more positive outcomes.
Now that we know what data-driven organizations are let’s go through some characteristics they have in common.
Characteristics of a Data-Driven Organization
There’s no doubt that all companies use data on some level. From customer information to regular sales or usage reports – you are sure to have heaps of it lying around. But the problem is that you are probably not using most of it – up to 73% of it, according to a Forrester report.
And this is what sets data-led companies apart. They treat data as a strategic asset and make sure everyone throughout the company is enabled and empowered to use it. Following are some characteristics that ensure this:
Leaders Championing the Data-Driven Approach
People at the head of data-driven companies understand that leading by example is a must. As leaders, it’s up to them to clearly demonstrate how they use data in their decision-making process and value it as a strategic asset.
But there is an important distinction to be made here – being data-driven does not mean focusing only on metrics or key performance indicators. A researcher’s mindset is a huge benefit, as is the willingness to dive into the data and pull insights that might not be immediately obvious.
So, it’s not surprising that leaders running most data-driven organizations have demonstrated great curiosity and a disposition towards challenging the status quo. They are not afraid to disrupt their market with data and AI-driven innovations (before a new competitor does) and proactively shape their verticals based on these new approaches and technologies.
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 – from the employee benefits you offer and the way your teams communicate to how they approach and solve problems. So, it’s not surprising that data-driven organizations often have a similar organizational culture.
A data-driven culture helps leaders establish data as a strategic resource throughout their organization. It ensures that teams understand the value of data and are empowered and enabled to use it in their everyday work.
By building a robust data-driven culture, leaders help their employees understand the business better and their role in ensuring its success.
Data Is Democratized across the Company
For a company to be truly data-driven, information needs to be accessible to everyone who needs it – ideally instantly. When everyone has the appropriate level of access to data, the decisions are made in a matter of seconds or minutes, helping the business to stay flexible.
The democratization of data also helps businesses avoid the pitfalls 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 runs amok, 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 data and get meaningful, actionable insights. From this, it’s easy to understand why data-driven companies 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 IT 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 Processes around Data
Data-driven organizations understand that just having insights isn’t enough to stay in the lead. That is why they focus on embedding these insights into their business process and automating the data management workloads.
You may wonder why automation is so important. But just think about how much time it takes to manually generate intelligence reports or dashboards. In fact, a study by MIT Sloan suggests that employees spend 50% of their time dealing with mundane data-related tasks.
Automating these processes not only allows data-driven companies to save on costs, but also enables them to respond more quickly to sudden changes on the market.
Benefits of Being a Data-Driven Organization
A data-driven approach is not easy to achieve. But once you do, it brings many benefits across the organization. These cover everything from knowing your customers more intimately and predicting their behavior, to ensuring your internal processes run smoothly and with minimal costs.
In this section, we’ll explore several that significantly impact your business success.
Data-Driven Decision-Making Leads to Better Decisions
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 your company – from salespeople to finance teams – to make better decisions based on evidence.
But making smarter decisions is not the only benefit of DDDM. It allows you to benchmark and learn from your past decisions, as you have historical data to rely on. It also helps you mitigate the risks of making the wrong decision, and even in the case of making one – it allows for a faster recovery 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.
The Data-Driven Approach Enables You to Understand Your Customers
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, and 19 times more likely to be profitable.
So, how do they do this? The answer is surprisingly easy – by keeping their customers happy.
If you know what your customer likes, needs, and wants, you can make sure you are always there for them. Even if they become unhappy with your business at some point, a data-driven approach allows you to understand the cause and pivot 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.
Data-Driven Companies Have Increased Organizational 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.
Data-Driven Organizations Show Higher Efficiency and Lower Costs
The vast improvement it provides for your behind-the-scenes processes is an often overlooked advantage of the data-driven approach. As you gather and analyze more information on your operations, you find ways to adjust and optimize them in real-time, achieving two main benefits for your business.
First, you can improve your customer experience by ensuring your internal processes run like a well-oiled machine. For example, by monitoring your supply chain, you can predict potential bottlenecks in shipping or manufacturing which might delay the delivery to the end customer – and find ways to avoid them before they happen.
Secondly, you lower the overall costs of running your business – especially regarding capital investments. By constantly monitoring the state of your equipment, you are in a great position to know when it requires regular servicing or if it’s nearing the end of its life cycle. This information helps you lower the overall costs and prevents expensive breaks in production.
Examples of Data-Driven Approaches in Different Industries
Data Analytics Improve Customer Experience in Retail and CPG
Retail and CPG industries are highly dynamic and competitive, which means that companies need to constantly customize their marketing and customer service efforts to stay ahead of the competition. To do this successfully, brands rely on data analytics to understand their customers better and anticipate market trends.
Changes in technology have caused a massive increase in the volume of data that is processed – the global retail analytics market will be valued at more than $9.5 billion by 2025. This growth is fueled by retail and CPG businesses that continue to invest in digital transformation and replacing legacy systems with data management solutions and modern apps to run a data-driven business.
The main goal for them is to increase profits by providing unique customer experiences – and that’s where data analytics plays a vital role:
- A deep understanding of the customer and predictive analytics enable data-driven personalization that helps brands build long-term loyalty.
- AI models and solutions that come on top of deep customer data uncover new segments and hidden opportunities, and improve in-store experiences.
- Data lakes or data warehouses enable a holistic overview of the business and trigger the optimization of processes such as forecasting, product assortment, or distribution.
Data Is Transforming the Manufacturing Industry
Manufacturers work with a wide variety of operational data to optimize business processes. From sensors to connected devices, the volume of information and data they collect is on the rise.
Even though manufacturing data is still fragmented in many cases, it holds massive potential not only for process optimization but also when it comes to making strategic, data-driven decisions. Industry leaders have recognized this opportunity and are implementing digital transformation projects to eliminate data silos and create a foundation for future growth.
Here’s how data analytics drives the transformation of manufacturing businesses:
- Data-based understanding of the system behavior helps organizations introduce preventive maintenance to streamline costs and improve worker productivity.
- Combined production and shop floor data enable manufacturers to improve inventory management, redirect resources, or do better forecasting – leading to overall cost reduction and process optimization.
- Analytical data – especially when enhanced with AI and machine learning – helps manufacturers understand market trends, gaps, and future needs to introduce innovation faster than their competition.
Logistics Companies Turn Data into Insights for Better Performance
The global logistics market was valued at $7,641.20 billion in 2017 and is projected to reach $12,975.64 billion by 2027. So it’s no surprise that logistic leaders gather data on everything from shipment tracking to weather and traffic data to improve their market position.
Data analytics can help industry players streamline operations, improve routing and introduce personalized customer service.
This is how logistics leaders leverage the power of data:
- To optimize the shipping process, route optimization software and algorithms analyze various data sets such as GPS data, weather, or road maintenance data.
- Ongoing analyses of warehouse operations, including the data such as capacity or flexibility, can significantly improve warehouse management and increase supply chain performance.
- Customer insights combined with artificial intelligence improve communication with customers and enable more intelligent customer service.
How to Become a Data-Driven Company
You probably understand by now that there is no single path to becoming a data-driven company. Instead, every company faces a different context and challenges that influence the overall process.
However, several key elements need to align for the transition to work:
Build a Data-Driven Culture
Do you know the saying “Culture eats strategy for breakfast”? Well, you can bet it applies to data-driven organizations as well.
So, before you start working on implementing the newest technology solutions or developing a new data strategy, think about how your organizational culture needs to change to facilitate this shift.
Change is never easy, especially when it impacts a lot of people. The “this is how we’ve always done it” objection is tricky to overcome. And it requires support from the entire leadership as well as champions throughout the organization to make it work.
When trying to motivate people to accept change, a crucial question is “What’s in it for me?”. And the best way to answer it is by showing your teams how data can help them do their job better or more easily.
You need to consider other culture-related questions, for example: Does everyone have access to the information they need? Are your teams motivated to share their data with others? And do they have a high enough level of digital literacy to know how to manipulate the data?
All these questions will highlight the areas you need to work on to ensure your organization and your teams are ready to embrace a data-led mindset.
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.
Develop a Data Strategy
To transform your company into a data-driven business, you need to understand the role data plays in your organization and how it contributes to its overall success. And a good data strategy does 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 people.
In our strategy consulting work, we always start by doing an audit of the client’s ecosystem which provides insights for the next steps. You start by answering questions like: What data are you using now? Where is that data coming from? What kind of data will you need moving forward?
These will help you understand the status quo, and identify the gaps you need to bridge on your way to becoming data-driven.
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 a common mistake of setting unrealistic goals or defining a strategy without a clear way of delivering on its promise.
Improve the Level of Data Literacy
When building a data-driven organization, you have to pay special attention to your teams’ digital literacy levels. This is because 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.
Working on data literacy becomes even more pressing if you consider recent research by Qlik. It shows that just one in five employees believe their employer is preparing them for a more data-oriented and automated workplace.
An excellent way to start is to assess the data literacy levels of your teams. However, when looking at the results, it’s good to remember that different groups throughout the organization require different levels of data literacy skills. After all, 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 people to company-wide training on the basics of data analytics. Whichever you choose, you will need to regularly reassess your teams to measure how successful these programs are and make any potential course corrections.
Chose the AI, Machine Learning, or Data Analytics Solution That Supports Your Overall Objectives
Solutions such as AI, machine learning, and data analytics have revolutionized every aspect of how we do business. From knowing what your customers want before they do, to completely digitalizing your customer service efforts – there are plenty of ways you can take advantage of what they offer.
But here lies a mistake many companies make. Seduced by all the possibilities, they implement new solutions before thinking about how they will support their overall business goals or if their teams can fully take advantage of what they offer.
So, before you choose that shiny new AI-powered solution, make sure your culture, strategy, and data literacy levels are where they need to be.
A key thing when implementing new solutions is for them to fit your current digital infrastructure. After all, what good is an advanced data analytics program if you can’t fully embed it into your other systems?
For companies that haven’t already, this usually means transitioning to cloud computing, which enables the storage and processing of vast amounts of data more quickly and efficiently.
Whether working with customers on a new data analytics platform or AI and machine learning solutions, we start by creating a shared understanding. We define what we are trying to achieve and how this fits their overall objectives – ensuring we all have the same end goal in mind.
Interested to learn how we can help you transform into a data-driven company? Get in touch and we’ll book a short introductory call where you can tell us more about your specific context and challenges.
