August 13, 2019


This article is part of a four-blog series that takes an in-depth look at data visualization. Follow the links below to see the other stories:




Photo of data analytics

When developing an analytics platform, the discussion around how insights and results are presented for consumption by end-users should begin early in the development process.

In fact, investing in technology, infrastructure and data sources before completing a comprehensive discovery on what information people need and how they want to interact with it is one of the biggest reasons companies produce solutions that never get adopted.

Below are the six big questions WebbMason Analytics consultants ask at the start of every visualization project to ensure its value to departments across the enterprise.

1. Are your champions powerful?
Data visualization solutions automate the generation, creation and display of business information so that decision-makers can make informed, fact-based choices quickly.

Each dashboard draws on vast quantities of complex data and converts it into easy-to-read charts and reports that can be viewed by anyone with the right permissions. They enable management, but they also take a lot of control out of the hands of the business units. Strong champions help to smooth the process.

“Asking people to let go of their Excel spreadsheets in favor of a more global view makes many employees at all levels feel disempowered,” said Michael Lang, Partner at WebbMason Analytics.

When the decisions about which data to include in reports are no longer handled at a local level, leadership’s trust goes up. Because all the source data is thoroughly validated and is purely quantitative, executives know the insights generated by the solution are agnostic to office politics.

2. Do you have a clear idea of the questions you need to ask and the problems you need to solve?
Data visualization dashboards offer data clarity by presenting information in a format that helps decision-makers grasp difficult concepts and identify patterns they couldn’t see by looking at the raw data.

To effectively extract the right insights, you need to have a clear understanding of the business questions and how those questions cascade through different departments. The objective is to create dashboards that give each user group what they need to do their jobs.

For example, if you are using the solution to help improve productivity, the shop floor may be focused on the number of units produced, but logistics will be interested in the just-in-time delivery of raw materials and finance will be keeping a tight handle on the production costs.

3. Have you adequately engaged subject matter experts and product owners for each business area?
Subject matter experts, who understand the processes, procedures, data and nuances of their departments are essential to every data visualization project. Their input into selecting data sources and the scope and nature of dashboards are critical.

You also need to look ahead and determine what roles in each department will function as product owners after the solution is deployed. While they don’t need to be technically skilled they do need to understand the data, make sure any changes are reflected in the dashboard and manage requests for new visualization features.

4. Do you understand all the users, their needs and their skills?
Data visualization solutions are valuable because they use data from across the entire organization and have the ability to give the senior team a holistic view.

But, many users need information that is specific to their role. For example, knowing if the repair department is over-committed or the status of product recalls may be essential dynamic information for a customer service operator, however, it’s not something the marketing team needs.

Once you know what data each role needs, you have to consider how to present it. Does the sales manager want to see overall sales figures before being able to drill down to what products sell best in each territory or is the performance of his team members a higher priority? And which kind of graphical tools most effectively distill the information and trends he wants? Do you need graphs, lists or charts?

From the standpoint of a visualization project, understanding what people need as well as their technical skill levels helps to determine the best technology to use.

5. Do you have a plan for who can access what data?
When creating a data visualization solution, you need to have a comprehensive map of what information is needed for each user’s job role. This ensures that the right people get access to the data. It also ensures that valuable information does not fall into the wrong hands.

Restricting access to particular data within your data visualization has several benefits including:

  • Safeguarding sensitive information such as that used by the human resources or finance departments.
  • Helping a company meet its compliance requirements.
  • Focusing attention on the data a person needs to do their jobs rather than overwhelming them with information they don’t need.
  • Providing a separation of duties.

6. How often do you need to refresh information?
The question of refresh has significant implications on the type of technology your project needs.

In some instances, where the data is gathered many times a second, immense data storage is required. For other applications, where decision-makers need to see changes in real-time, high-speed computational power is essential. Both add to the complexity and cost of the final solution.

The rate of refresh must be in direct correlation with the speed of decision-making. Data architects and engineers are responsible for balancing this requirement with their choice of technology as well as development and operational costs.

Successful data visualization projects are incredibly powerful. Graphs, charts and other presentation techniques help people interact with vast quantities of data in a way that provides actionable intelligence and insights that are impossible to generate manually or on an ad hoc basis using spreadsheets.

When developing a particular data visualization, clearly defining the scope and requirements of all the users upfront helps to ensure the most appropriate technology is deployed, all relevant source data is ingested and that the right insights are presented to each user in a way that makes complex information easy to apply to business challenges.