Digital has changed the business landscape forever- brands can think, move, scale, and impact instantly. And data sits at the core of this digital strategy. So, a stronger data vision enables an organization’s capabilities at every level. In an ideal scenario, a business treats data like an asset. When it’s treated as an asset, brands can deliver value from data more consistently and even quantify its impact.

Brands and organizations that had data embedded into their core strategy have scaled much faster than others. Fast forward to the present, almost every business has a data strategy that works – a data-cloud infrastructure, a data analytics framework, and a data visualization system, and this enables them to leverage data at some level*.

Even with all this awareness, the question of democratizing data still remains. However, data visualization in business intelligence is the start of a solution to this problem. With the right visualization approach, brands will be able to see and do a lot more with data. Automation, Artificial Intelligence, Machine Learning, and many other game-changing technologies are transforming data visualization from a mere presentation tool to a reliable decision-making companion.

And this transformation is what data providers should focus on, too! Data will be democratized in the future, and not every brand can spend a significant portion of its resources to be data-positive. So, like any other product, a data visualization system should solve the problems of the end-users – CXOs, IT managers, finance officers, engineers, designers, or anyone at the other end of the deal. It should be a place where insights start rolling out.

How does data visualization solve business problems?

Right now, many brands have included a data visualization system in their grand business design, but to what extent this system adds value to the organization is debatable. Sure, it helps brands navigate through complex, large sets of data, but can it help them stay ahead of the curve or at least keep up with the market flow?

Many business leaders still think of leveraging data as going the “extra mile.” They fail to see that data sits right at the intersection of innovation, finance, and branding! Big data analytics solutions will be the most impactful drivers of the market in the coming years.

For instance, we collaborated with a global FMCG manufacturer to help them accelerate their digital transformation. As a part of their digital transformation strategy, we created a master data visualization software for our client that connects with standalone data visualization channels within various departments.

Our client was surprised by the vast amount of data at hand, particularly from their subsidiary companies which included a pet-monitoring startup. By simply making this data visible to our client, they were able to enter an entirely new market- the pet food industry, effortlessly.‍

The pet food industry is a rapidly growing, billion-dollar market that’s expected to reach a staggering $53 billion ^[1] in the next few years. Now, imagine the time and confidence the organization would have needed to move into this relatively new territory without data. That’s what visualization is all about- Exploring the unexplored with minimum risk and maximum visibility.

There are thousands of best data visualization tools out there that paint a beautiful picture of your operations, but when brands take them seriously, with a little nudge in the strategy, these tools could be a door to new opportunities, reinforcing your organization’s decision-making capabilities.

How can organizations level up their data visualization strategy?

data visualization strategy

Define the context

Think of a data visualization system as a bridge between you and your business decisions. As organizations are increasingly adopting the data culture, it is no surprise that it plays a major role in your business decision-making. However, understanding the context of the data is as important as the data itself! Data can mean different things under different lights. So, define the context and detail it as much as possible to interpret data efficiently.

Take the social media strategy of a company, for example. The follower count is obsolete if the senior management is focused on conversion rate. So, if you present to them the follower count as a metric, the whole thing misses the point. But when brand reach is in question, the data on follower count makes sense. So, align the strategy with your goals, and define the context for a better data visualization system.

Understand your audience

Now, at the beginning of this article, we would have mentioned that a data system should be crafted with its end user in mind, like a product. The same applies to data visualization. Imagine the people who will be interacting with your data visualization system. The goal of this system is to help users interpret data better and faster and ultimately make better decisions. Now, taking the audience out of this equation will exactly do the opposite of what you intend to achieve with this process. It may even confuse your user and can lead to an incorrect understanding of a piece of data.

Visuals matter

While you understand the kind of data and the audience you are gonna deal with, you also have to nail the process of presenting the information to your user. Data visualization helps the organization because people understand graphics better than text. In fact, they process images 60,000 times ^[2] faster than text! Meaning, that your visualization system does a better job when it strikes a balance between the data and its representation.

Imagine the COVID dashboard we used during the pandemic. The information layout was simple, and the data was more interactive than static, making it easier for people to understand and process the information. This way, we stopped miscommunication of facts and could follow upon the impact of our efforts. Similarly, choosing the right types of data visualization can be a game-changer in a data visualization system.

Don’t go overboard

While, in theory, more information equals better decisions, one should be aware of the time frame within which the user gets this information. Cognitive overload is real, and a user will not be able to process any more of the information when they reach this state. An ideal data visualization system arranges the data in simple patterns that users can easily understand rather than dumping them all on a single plate. The whole point is to facilitate the user in decision making- to move from data to insights.

Wrapping this up

Data visualization is a crucial part of your organization’s data culture. In many ways, an effective data visualization system will encourage the people to rely more on data, boosting the overall data vision for the organization. As we work with brands and organizations from different industries and cultures, we see this obvious gap in their structure that slows down their growth from leveraging data. And most of the time, organizations spend a fortune to bridge this gap while the problem can be solved at a fraction of the costs involved. There may be several state-of-the-art data visualization service providers in the market today, but if you need a true data solution partner who can help you overcome this data challenge for your organization, you should definitely connect with our data engineering experts today.