Everyone today is talking about being data-driven; this includes individuals and companies. Even the world we live in today is called a “data-driven” world. So, what does a data-driven world means for you? And how does it affect your business or profession?
In the modern business world, digital marketers, product managers/launchers, project managers, business leaders, and even employees rely on data to know the next step to take in delivering their services, making decisions, and optimizing flows.
The term data-driven literally means being obsessed with data, relying upon information derived from data analysis and visualizations to make strategic decisions and predictions. In today’s data-obsessed world, one needs to be data-driven to thrive in virtually all business aspects.
Interestingly, this article analyzes what it means to be data-driven and why you should start relying on data analytics to deliver your services. Whether you’re a business/team leader or a freelancer, being data-driven is now more like a compulsory yardstick for employing or hiring business personas.
Wonder What a Data-Driven World Means For You?
Let’s start with defining the term “Data-Driven” comprehensively. As hinted earlier, it means to be data-obsessed. But comprehensively, being data-driven means basing all your actions, predictions, and suggestions on what is shown in your data analytics dashboards.
In other words, being data-driven keeps your expertise aside while you focus on what is obtained by analyzing your data sets. This is most especially important to drive more sales, improve customer satisfaction, stay ahead of the competition, and increase ROI significantly.
We live in a data-driven world where data has an impact on our everyday lives – and in everything we do daily. A more clearer way to explain what it means to be in a data-driven world is through these examples pointed out by Bojan, a senior leader in Deloitte New York.
According to Bojan, “Facebook is the most popular media company, but it has almost no content. Uber is the world’s largest taxi provider, but they own no vehicle. Airbnb is the world’s largest accommodation provider and owns no real estate. Also, Alibaba is one of the most valuable retailers in the world and owns no inventory.”
These are all big companies, and they deal with a ton of “Big Data” daily. Data is obtained in various formats; we have structured, semi-structured, and unstructured data. These companies mentioned above rely on the information they get from analyzing, visualizing, and interpreting the multiple datasets they have, and that’s why they’re excelling.
There are, of course, many other successful companies, and if you dig deep into the cause of their success, you will discover nothing else but the fact that they are data-driven. Big, medium and small businesses are rapidly embracing data analysis to make clearer decisions, drive insights, and take critical steps to go about their daily business activities.
Furthermore, in today’s world, the better insight, the better decision you will make. So, data analysis and visualization tools are now among the most sort after business tools by every business professional around the world.
The Evolving Data Landscape
Over the past years, the data landscape has evolved – some people say it is a revolution – in many ways. Businesses are still finding new ways to perfect the way they mine, analyze, and utilize data.
On its own, data landscape refers to the representation of data assets, channels through which they are created, storage options, and the analyzing tools. It is the systematic representation of how data is gotten (created), stored, analyzed, and utilized by different companies, organizations, agencies, or corporations.
The widespread technological changes have continuously influenced data landscape patterns, from the revolution of data warehousing to cloud-based technologies.
On-premise data warehouses helped organizations to collect tons of data from multiple sources into one system where the data is saved for reporting. However, since it was majorly on-premise data warehouses that existed, the opportunities were well limited because they were highly structured; only technical data experts could interpret them – a process that takes many weeks to actualize. As technology kept expanding and customer touchpoints kept increasing, data opportunities were soaring high too.
Since data warehouses only housed structured data, which wasn’t enough to satisfy the growing demands of data usage in the business world, data lakes were introduced to hold up unstructured data. With data lakes came specialist data roles, such as data scientists; these individuals could address data demand and help organizations prepare for a data-driven future.
Data lakes became an integral part of the data architecture, which was a big development in the big data landscape for securing data that may be used in the future. But then, demands kept increasing, and businesses needed to scale easily to meet their data usage demands; then came AI and ML solutions and BI suites.
Cloud-Based and AI Integration
Currently, we’re in a time where cloud-based data warehouses and storage solutions are becoming an integral part of organizational data architecture and landscape. With companies like Microsoft and Informatica developing some of the best software solutions to address enterprise – big data – needs, from data creation to collation, analysis, and visualizing/interpretation. Data landscape has evolved over the years for everyone’s good.
Benefits of a Data-Driven Business World
The benefits of working with data-driven insights are quite enormous and cannot be overemphasized. By practicing a data-driven culture for your business, you’d be able to serve your customers better, increase sales and ROI (by optimizing your campaigns and tactics), and identify new opportunities worth trying. Hereunder are noteworthy benefits to know of.
1. Make Accurate and Informed Decisions
Utilizing data to the fullness helps companies to make informed decisions that keep them ahead of competitors. Also, this allows companies to plan and take decisive short- and long-term actions that would influence their productivity positively.
2. Serve Customers Better
You can’t possibly serve your customers better without knowing exactly what they want. Monitoring your customers’ behaviors and journeys and analyzing the data helps businesses understand where they need to improve, mitigate, or optimize in order to serve their customers better. When customers are served better, apparently, you’d make more sales seamlessly.
3. Easily Identify New Business Opportunities
One benefit of being data-driven is that you discover the loopholes in your business and fill them up. By analyzing and visualizing the data obtained from campaigns and diverse marketing/feedback channels, businesses can figure out new opportunities they can seize to grow their revenue – by offering additional – related – services/products or improving on existing ones based on the insights obtained from the analyzed and/or visualized data.
4. Easily Adapt to Business Changes
The business world changes rapidly, and this applies to all sectors: hospitality, engineering, manufacturing, retail, wholesale, government, and others. Through data analytics and visualization, data-driven companies can detect when new changes are set in the market and start making early plans to adapt to the changes. So to say, data analytics and visualization help businesses make data-driven predictions that are practically accurate.
How to Become More Data-Driven?
“Data-driven decisions went from being a priority goal to absolutely necessary in order to survive the unplanned and significant changes to the business environment,” Jeremy Blaney, the director of customer solutions at Tableau.
However, “data can only take an organization so far. The real drivers are the people.” Gartner. The first step to becoming more data-driven is to embrace and practice a data-driven culture for your business. You can’t run a data-driven company without building a similar culture; it’s harder to build a data-driven culture than merely hiring data experts and implementing Business Intelligence solutions.
1. Establishing Data-Driven Culture
Infusing and establishing a data-driven culture means shifting the mindsets of your team members, employees, or co-leaders and teaching them the benefits of being data-driven; this may take some time to achieve; however, the time is worth it – considering the long-term benefits.
To become more data-driven means implementing the right internal processes and culture, making your team members or employees accept and work with data technologies to analyze and visualize data obtained from various sources.
Sadly, many organizations and companies of today do not utilize the data they have at hand, which causes them more valuable resources. If data is misused or not fully utilized, the result is quite discouraging, and it could cost the business more money and time. Yes, data has to be utilized to the fullness if you want to become more data-driven to make decisions, predictions, and trend analysis.
Well, being more data-driven is pretty hard; while many companies claim to be data-driven, only a few are actually data-driven because they treat data as a business asset. Data literacy is also important to becoming a data-driven organization; you must know the potential of the data collected by your firm and find out the best way to analyze data and utilize the potential for making decisions.
2. Data Literacy
Organizations jump-start their data-driven roadmap by broadening data-collection channels, launching Big Data initiatives, employing or hiring a Chief Data Officer (CDO), and implementing data analytics functions; while all these are needed to become data-driven, there’s more to it than this.
In creating a data-driven company, culture is primary; data literacy is the second most important factor. Definitely, people can’t understand what they don’t know at all. Data literacy is simply the “ability to read, understand, create, and communicate data as information,” according to Wikipedia, and that remains the best definition of data literacy.
To establish a data-driven organization, you must first educate all your employees on how to collect, store, analyze, and utilize the information contained in the datasets from multiple channels. Data literacy also includes understanding data sources and constructs. It is essential for all workers at all levels of a data-driven company to be data literate.
- Data literacy and establishing a data-driven culture, among all other factors, are the main keys to becoming more data-driven.
- Making data-driven decisions is now necessary for modern businesses that want to be in the spotlight and continuously generate more revenue.
What Does The Data Future Hold?
What does the future have in stock for data collation and utilization? Apparently, it can only get better – and better. Full utilization of data has proved to be very useful to businesses across the globe in driving incredible sales numbers and skyrocketing their revenue by up to 200%.
The deep insights derived from data analysis and visualization help businesses make crucial decisions and optimizations to improve many aspects. These things are already happening, and we can only expect them to get better in the coming years.
Apparently, the future of data mining, storage, interpretation, and usage would take new turns, and we’d be seeing more advancements. The majority of changes would revolve around market transitions, global compliance measures, and BI/AI improvements.
So, what does being in a data-driven world/environment imply? It means being in an organization where data is treated with great value – as one of the business’s greatest assets. Organizations are becoming more data-driven to meet the demanding needs of their customers and align with the constant changes in their respective sectors.
Data is relevant to all modern businesses looking to thrive and remain in the spotlight. However, becoming data-driven is quite challenging; organizations need to instigate a data-driven culture and educate all workers to better understand how to collate, store, aggregate, and utilize data for everyday operations.