Background
Will you be surprised if tomorrow’s Leonel Messy and Micheal Jordan are known as 2030-89/18 and 2081-67/75?
Economic globalization was meant to connect markets, but today’s technology-inspired globalization is wiring Individuals and not stopping there. The more we connect through technology, the more data we generate, making our world exceedingly data-driven.
The moot question is whether data is enough for businesses. Data is the new oil, which appears to be true, as data needs to be refined like oil to produce fine products.
Synopsis
Raw data is as good as a rock that needs to be polished into a diamond. However, 80% of businesses struggle to get actionable insights from the data they collect, buy, or extract and to present them in visually compelling ways to clearly understand market trends and customer behavior.
Therefore, we will cover data visualization and data maturity in this blog and will explain why data maturity is essential and how businesses can leverage data visualization with its long-term impact on decision-making. Finally, we will share some crucial tips for creating compelling data visualization.
Introduction
Businesses are holding on to gold mines, literally. It is surprising to know that 90% of data was generated in the last five years. And yet, businesses have no idea how to put those data to use efficiently.
Businesses worldwide may arrive at data maturity when they actually process data that unveils actionable insights. Data maturity basically means businesses’ ability to leverage raw data effectively.
When data becomes mature and valuable, it creates a visually powerful presentation that enables businesses to draw definite conclusions about market trends, customer behavior, and demand-supply dynamics. Based on these insights, businesses can make intelligent business decisions and grow beyond competition.
Why Data Maturity Matters for Businesses
Let’s assume your data is your pie, and the sweetness of the pie is decided by how you slice it. Data maturity is how effectively businesses use data to extract desirable results at various stages.
From data collection and compilation to data classification to advanced insights, each stage ensures businesses improve decision-making, gaining more efficiency and competitiveness. Companies with the highest data maturity can see a 20% increase in their profitability.
Basic: Data is scattered and hardly used
At this stage, businesses collect minimum data but rarely use them for decision-making. Over 50% of businesses are at this stage.
Reactive: Data used for simple reporting
Businesses collect more than minimum data and use it for basic report purposes. However, they can’t track performance adequately.
Proactive: Data guides some decisions
At this stage, businesses collect considerable data to solve basic business problems. It can help businesses solve problems 10% faster.
Strategic: Data drives most business choices
Businesses become data-centric, preparing advanced analytics to make better choices and gain a competitive edge, acquiring new customers 23 times better.
Transformative: Data creates new opportunities
At this stage, only 4% of businesses reinvent and streamline business processes using data and create fresh market opportunities to stay ahead of the game.
Higher maturity, Better Outcome:
Imagine having a pile of dollars on the table but not knowing where to invest for higher returns. High data maturity enables businesses to achieve 2.5 times better outcomes. Data-driven decisions streamline business processes to reduce cost and optimize resource allocation, and enhance customer journeys through personalization and targeted ad campaigns.
Advanced analytics can help businesses outperform their competitors by 20%. Data visualization based on advanced data insights empowers businesses to see through future market trends, consumer choices, supply chain problems, and possible time-to-market innovations.
Do you know how data visualization works with advanced analytics?
What is Data Visualization
Have you ever tried turning numbers into a beautiful picture? Data visualization is a method of transforming analytics into graphs, charts, and maps to simplify complex insights into clear and understandable graphics. It uncovers hidden patterns, identifies developing trends, and empowers businesses to forecast outcomes and make sound business decisions.
It is no surprise that psychology suggests that individuals can process visuals 60000 times faster than written text. Meticulously prepared data visualization boosts understanding by 28% and decision-making by 64%. Converting scattered and inadequate data into growth opportunities is the science of big data analytics. Are you ready to see your businesses in a whole new light?
How Data Visualization Accelerates Data Maturity
Insights are no longer enough if businesses want to go past competition and dominate the markets. Businesses are required to navigate through minute details relating to customer behavior, market dynamics, supply chain trends, geopolitical events, and more to make decisions.
Data visualization empowers businesses to utilize data effectively, ensuring data maturity at exceptional levels. It allows businesses to spot even minute details of trends, patterns, dynamics, and opportunities through graphs and charts and see the big picture instantly.
1. Visualize how sales are increasing, or customer behavior is shifting.
2. Visualization presents you with correlations among data points.
3. It presents simplified data to stakeholders for clear understanding.
4. Visualization stimulates decision-making for quick turnaround.
Key Components of Effective Data Visualization
What ingredients are to the rare dishes; components are to data visualization. Data visualization techniques help businesses prepare tailored insights and avoid a one-size-fits-all approach to get to the bottom of the data.
Each data visualization technique allows businesses to see insights in a different light and from diverse perspectives to present a wholesome performance picture. As a business, you should be inspired to make decisions 65% faster and more accurately with data visualization.
Bar Charts:
Bar charts are a simple yet highly effective technique for comparing the performance of different periods or parameters. 76% of businesses leverage bar charts to compare sales data or customer satisfaction ratios.
Line Graphs:
If you want to witness changes in business dynamics, line charts exquisitely reveal patterns and trends over some time. They help businesses understand the cyclical nature of the market and forecast future trends.
Pie Charts:
Pie charts help businesses see the big picture by displaying variable components that influence business. They are used to bifurcate one component into pieces to understand minute details like customer demographics.
Heat Maps:
Heat maps showcase the intensity of data sets, using various color gradients to underline the performance of one metric against others. They reveal where businesses need to focus and which metrics are performing better.
Scatter Plots:
Scatter plots are generated to uncover the hidden correlation between two metrics variables. They reveal the interdependency of the variables to identify areas for improvement, especially in marketing campaigns.
Benefits of Data Visualization
Clear Communication: In business, it is essential for stakeholders to be on the same page. Data visualization makes insights easy for all stakeholders and employees to understand.
Quick Decision-making: When the performance-related outcomes are clearly communicated, it becomes easy for management to make decisions and create growth opportunities.
Collaboration Boost: When decisions are made based on identified trends, collaboration among employees for common goals and smooth execution improves multi-fold.
Quick Evolution: Businesses can analyze data faster to identify the bottlenecks and eliminate them to quickly adapt and improve according to growth opportunities for greater competitiveness.
Improves Storytelling: Captivating visuals and artistic presentation make it easy for everyone to remember performance metrics and to be reminded of areas requiring improvement.
Competitive Advantage: Faster decisions, improved efficiency, and future forecasting help businesses successfully target and engage customers, improving sales and gaining a competitive edge.
Best Practices for Effective Data Visualization
Design Principles:
Once the science of data analytics ends, the art of design begins. Effective data visualization isn’t only about lines and circles; it also involves useful and valuable visuals that simplify the understanding of data. Key design principles are part of the best practices for data visualization that stimulate actions.
Simplicity: Keep it clean and clear
Too many details and too much design result in ambiguity. Keep the design minimalistic and data precise, focusing on the core message.
Accuracy: Tell the truth with data
Data visualization should be trustworthy and truthful. Doctoring data for desirable results adversely affects business performance.
Relevance: Show what matters most
Data Visualization design should showcase only relevant data. Stakeholders and employees should not get confused about the outcomes.
Consistency: Use a unified style
Data visualization design should adhere to the branding guidelines of colors and fonts to help stakeholders quickly understand the moot points.
Color: Choose wisely and meaningfully
Too many colors in visualization design do not convey the message. Besides, relying on colors only increases confusion.
Interactivity: Let viewers explore
Visualization design should be attractive enough to let the viewers interact with data to explore more possibilities of insights for deeper nuance.
Aesthetics: Make it visually appealing
Visualization should not consist only of lines, circles, and curves. Instead, it should be visually attractive to remember data points and outcomes.
Storytelling:
Datasheets and reports look cold and complex mazes for anyone to decipher. Each data set and report should have compelling stories that help businesses comprehend the insights with ease and accuracy. Therefore, storytelling has a special place in data visualization. A story weaved with data is memorable and persuasive.
Start with a clear message
Determine the critical message that a data visualization should convey. Prepare a narrative around that central concept.
Know your audience
Weave your narrative with data that surprise viewers and captivate them toward the central theme of information.
Use a familiar structure
The story’s flow should be classic and non-experimental. Prepare scenes that explain the challenges and solutions afterward.
Highlight key data points
Do not get carried away by the storytelling; instead, focus on the numbers that should be told to viewers. Let the facts shine.
Create context
Your story should be able to explain such data, which is essential for stakeholders to understand. Relate data with real-world situations.
Use visuals to enhance the story
Make sure your story has relevant visuals that speak to the narrative and data insights. Visuals make stories more impactful.
End with a call to action
The story should end with a persuasion. Stakeholders and employees should feel motivated to act on insights presented by visualization.
Essential Tips For Creating Compelling Data Visualizations
· An irrelevant graphic fails to create nuance from the data. Select the right graphic type for your data to eliminate ambiguity and promote clarity.
· Don’t try to include too many details; this can mess up the presentation. Focus on critical findings and narrative around the message.
· Use different color schemes and background patterns to highlight various data sets and set one apart from others to clearly explain data.
· Data visualization should be interactive and inspire viewers to explore data in depth. It increases stakeholders’ participation in decision-making.
· Weave your story with data to prepare background and context for the insights that signify the importance of each data set and visualization.
· Cross-check and double-check each data set and its relevant scale to avoid inaccuracies in data visualization. Prioritize facts before fiction.
· Determine your viewers’ knowledge base and interests to craft a story around data that captivates them with inquisitiveness.
The Future of Data Visualization and Business Intelligence
The next destination of intelligent automation solutions is data visualization. Enterprise software solution providers are not satisfied with combining AI with RPA; they are now integrating AI with augmented analytics to ensure that not only experts but even laymen can understand the advanced insights.
The big data market is expected to reach $103 billion by 2025, and AI will further advance the nuance-making of these data. Almost 100% of companies adopt digital transformation solutions and big data analytics as part of them. Automating data analytics and data visualization will ensure that charts, graphs, and images are updated in real-time on the company’s analytics dashboard.
The future belongs to quick, easy, and real-time data visualization, which will allow businesses to evaluate their performance and instantly change strategies.
Conclusion
With the pace at which data analytics is growing and becoming automated, it is no longer a luxury for businesses. Data analytics and data visualization have become critical parts of digital transformation solutions. In fact, they are a must for business success in 2024 and years to come.
