In 5 Steps, Your Business Can Journey From Data to Insights

Sifting through vast amounts of information to pull out the most valuable insights can be a cumbersome task. In fact, this challenge prevents many organizations that have so much data from discovering crucial insights in the first place. Imagine the amount of useful business information that is being overlooked entirely.

For these reasons, transforming data to insights can seem very overwhelming. But it does not have to be.

Zencos Follows a Straightforward Data Visualization Methodology

Data visualization being one of our core competencies, we know a thing or two about it. We have a tried-and-true approach for our customer projects to ensure success.

Step 1: Gaining a comprehensive understanding of business requirements

At the start of every data communication project, our focus is to learn and gain a clear picture of the overall scope and business objectives. This first step, understanding the business requirements, is important to ensuring clear awareness of the information needed and better delivery of final insights that will position our customer to access ongoing intel. We encourage an iterative process to ensure delivery exactly meets or exceeds the expectations of business and stakeholders.

It is important to include key business stakeholders in this step, especially those that will be using the visualizations, when setting requirements. This will ultimately guarantee success in the form of user adoption.

Step 2: It’s all about data before visualizations enters the game

We cannot have data visualizations without the data!

Once the business requirements are understood, we use them to decipher what is important in the data. What questions do our customers need answered? What puzzles do our customers need to solve? This is a key phase in any data visualization project.

Data availability plays a vital role in ensuring project success. It is always good to involve someone with deep knowledge of the source system who can answer any questions we have during data extraction. It is of utmost importance that we collect the right data, so that we have procedures in place that follow industry best practices.

There is so much data because we have gotten so good at generating it. Companies are collecting data in more places than ever before, this often creates silos. Where organizations often have an issue is extracting and gaining value from the disconnected data. Integrating data from multiple sources has been a top priority in most of our recent data visualization projects. In today’s global marketplace, organizations are looking to go beyond displaying sources separately to looking at data in a single view.

Step 3: Centralized Exploration

Bringing multiple data sources into one centralized location plays a vital role in revealing key insights and even hidden insights. Selecting the right visualization tool unlocks the power of your data. Many of the tools we use, including SAS, Tableau, and Microsoft Power BI, provide the first window to insights. These tools can significantly reduce data exploration times and make it easier for analysts and general business stakeholders alike to get insights faster.

Your company may have a tool of choice or you may be in the market to bring in a new tool. The major players in the visualization space have strengths which may dictate how much data you can process, whether you can automate your processes, and ultimately what visualizations you can produce. The bottom line, understand what your choices are before you decide on your actual visualization strategy.

Step 4: Visualization deployment strategy

You have successfully defined the business needs, discovered the data sources that will be used to drive your visualizations, and understand the capabilities of your visualization tools. Now it’s time to deliver insights—the ultimate stage of the data-to-insights journey.

This step can be as simple as generating a single tabular or graphic report, creating effective dashboards for executives who need to quickly respond to key metrics, or implement real-time visualizations as part of a complex system for a larger digital transformation project. Whatever it is, it is important to design for maximum impact.

The data we share via visualizations should cultivate action. Poorly designed visualizations can make all the prep work be for nothing, The best data in the world means nothing if it’s not presented in a way that helps decision making.

Data visualization is crucial in communicating your findings.

Step 5: Adoption

User adoption determines the success of a data visualization project. A perfect report or dashboard design means nothing if the data surfaced by the visuals are meaningless to the audience.

To ensure user adoption, we encourage companies to go through all the steps in the process. To be successful, generate the requirements we talked about in step 1 with all key players. Plan for iterations at each step and get approvals from all the key players before moving on. This task should never fall on an individual person. If all the parties approve early on, there will be fewer surprises at the end.

A truly successful data visualization program creates a data-driven business culture that empowers users from the highest levels of the boardroom to the newest intern to drive the business forward.