5 Common Mistakes Companies Make in Their Data Visualization Efforts

data visualization, data visualization tools, visual analytics

Your company probably implemented data visualization tools to get to your data faster, present it in a more digestible, or because you’ve heard that data visualization tools can help you make better decisions on every level of your company; But are you getting the most possible value out of your investment in data visualization tools? What might be holding you back? In this article, we’ll share 5 common mistakes companies make when implementing data visualization tools and why these mistakes hinder their data visualization efforts.

Although data visualization is more accessible than ever, that does not mean that your company will automatically see a benefit by installing data visualization tools. Tools are only useful when used intentionally and wielded correctly by the user, and the same goes for any data visualization tool. Behind any successful data initiative is an effective data strategy, executive and employee buy-in, consistent opportunities to form new habits, and many other best practices that make your implementation of data visualization tools a success.

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Installing Tableau or Power BI won’t form the habits and company-wide culture necessary to truly see a return on your investment. Tableau says themselves that “Equipping employees with reporting and analytics tools is just one step in a larger cultural transformation that ties data to an organization’s core mission.” And McKinsey echoes that “actually mapping out an analytics plan is complicated. You have to set a strategy; draw a detailed road map for investing in assets such as technology, tools, and data sets; and tackle the intrinsic challenges of securing commitment, reinventing processes, and changing organizational behavior.” Is all of the effort involved worth it?

The resounding answer is yes. In McKinsey’s 2019 survey of companies using data and analytics, high performing companies attributed about 20% of their earnings over the past three years directly to their data and analytics initiatives. For companies that get data visualization right and have an effective strategy, it dramatically impacts their bottom line. So how are they making analytics work for them? They are investing in data visualization for the long term and committed to making using data visualization a key part of their business mindset, processes, and strategy. They tailor their data visualization efforts to the unique needs of their business, equip employees with training and support, and keep growing their ability to use data to further inform every area of their business.

If you’ve already implemented data visualization tools and want to check in on where you have room to grow, this article is a great resource for refining how you use data visualization. If you have yet to implement data visualization, read on to learn what to avoid in the future, and we also suggest starting from the beginning by first building an effective data strategy to add purpose to your use of data visualization. (Read our complete guide here.)

Without further ado, below is a quick preview of the most common pitfalls companies face in data visualization implementation. Read on to learn why these issues might be coming up in your data visualization efforts and how to resolve each.

  1. You don’t have a clear distribution plan
  2. There’s not enough buy-in and understanding behind your data visualization efforts
  3. There’s a gap in your training or you did not invest enough time in training.
  4. Data visualization isn’t a seamless part of employees’ daily workflow
  5. Your visualizations do not clearly communicate business value

1- You don’t have a clear distribution plan.

This pitfall is key to all of the others that are about to follow. Like with any software deployment, you need to have a clear plan for distribution for any new data visualization tool. Without a distribution plan, you will easily lose focus and adoption will suffer.

Your distribution plan should answer:

  • Who is going to create the data visualizations?
  • Who is going to use them? (Are the people that create them the same ones who will use them, or is that audience different? Your response will change your communication around the new data visualization tool and will affect how you train those employees. We will share more on training later.)
  • How will employees know that a new report or dashboard is ready?

For each report that an employee will view, you should inform them on where it is, how to use it, what to use it for, how often they can expect to get that report, and how often they should access it. By having a plan for distribution, you ensure that valuable dashboards don’t get lost in the midst of day-to-day tasks and that the employees are equipped to use your new data visualization tool.

McKinsey suggests that companies treat data itself as a product with real return on investment. They say, “Business leaders often view data as a raw material that supports analytics and decision making. Instead, they should treat data as an internal product to be packaged and distributed to groups across the enterprise and manage it as such.” This prepares employees to actually use it. If you were going to roll out a new product, you would surely have thought through who the customer is, how they’ll use it, what they’ll need to know about it, and more. The same is effective when rolling out a data visualization tool— your employees are also customers and they need to buy into this product to see more results for your business. Think about how the data visualization tool will impact the employee that receives it and, likewise, how to best get it in their hands and communicate about it in a way that they’ll be glad to listen to and act upon.

2- There’s not enough buy-in and understanding behind your efforts.

Does more than your product owner know about your data visualization efforts? In order for data visualization to really make an impact at your company, you need adequate executive buy-in and to create an understanding company-wide around the importance of data visualization.

What contributes to lack of buy-in? Maybe one department started using data visualization without consulting other areas of leadership or talking with other departments. Or maybe IT didn’t bring everyone in the loop and because they already understand the benefit of data visualization and wanted to go ahead and install the tool. Sometimes organizations view data visualization as only a function of IT or marketing, so they don’t get buy-in from any other department or executives and let IT take care of paving the way for the installation.

Buy-in can also be lacking if either executives or employees don’t fully understand the purpose of data visualization and why they need to be using data regularly to make decisions. If people don’t understand the potential positive impact data can have, it will be extremely difficult to create buy-in and you won’t get as much out of your data visualization tools.

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How do you create buy-in? Communicate the vision for implementing data visualization tools with executives. More than one person in leadership needs to be excited about using data visualization tools and be ready to invest time in learning it, communicating with and training employees, and following up on adoption; you won’t see results if you set it and forget it. Bring executives from all areas into the creation of your data analytics strategy, and include them as needed in a leadership team that is in charge of your data visualization tool deployment.

It is essential that leadership is ready to devote both their mental energy and their time to implementing data visualization, as they will be asking the same of employees. It will take time for employees to learn how to use a new data visualization tool and will require that they form new habits in their workflow, but if they understand the benefit and also see that executives believe in its value enough to do the same, they are more likely to use the tool and learn it eagerly.

Tableau accentuates the importance of communication about data visualization efforts coming from the top down, saying:

"Communicating your vision to your organization is the single most important step that many leaders fail to complete. People are better suited for change management when organizations are transparent with the end goal and why the change is happening. Many organizations may choose to have the CEO or CIO send out an email communication or address the vision in an organization-wide meeting, describing the commitment to become more data-driven or to increase analytics capabilities. This message is then then echoed by the Executive Sponsors. Communication that emphasizes that users are the ultimate owners of this change can instill a sense of comfort in times of stress."

Old habits die hard, and good communication with leadership and employees will help adoption go as smoothly as possible and ensure that installing the data visualization tool garnishes more excitement than it does confusion. Just as important as that communication is the effective training that should follow, which leads to the next common mistake…

 

3- There’s a gap in your training or you did not invest enough time in training.

One of the greatest mistakes you can make in your data visualization efforts is to deploy a data visualization tool with little to no communication or training for employees. We can’t emphasize enough that installing a new tool won’t be adequate to bring transformative insight. Every employee could be coming to the tool with a different data literacy level, experience with data, and set of daily responsibilities that they’ll be using data visualization for, and all of these variables are accounted for with adequate training. Employees need to be equipped to use Tableau or Power BI like it’s second nature. It needs to be a part of their workflow (more on that later), and they need to understand how it’s going to help them do their job better and more effectively.

Training serves multifaceted purposes. Training bridges the data literacy gap and practically equips employees. It builds community around data. It helps employees get over the learning curve of using a new tool. It clarifies what specifically the new data visualization tool should be used for, and it also protects your investment by teaching employees practices for maintaining your data security and quality.

Training should start with deployment of a data visualization tool and should be ongoing so that employees have consistent opportunities to grow their data literacy and use the tool to its greatest potential. As a part of your distribution plan, make a long-term plan for training each subset of employees that will use the data visualization tool. If you don’t have enough people to train everyone who eventually will be using the tool, make a plan for first educating a group of “super users” who can then train their own department or team and follow up on use metrics. In this way you multiply your training efforts and ensure that everyone who will use the software is trained on it first. Don’t plan for deployment without planning for training as well.

Adequate training can resolve common issues around governance, creating overloaded dashboards that don’t communicate enough business value, or not sharing dashboards in an organized, accessible way. In training you are able to address guidelines for how to use data visualization effectively and in ways that are the most beneficial to your business.

In training you also cast vision around your purpose for using data visualization so that employees know exactly what their effort to learn the tool is going to do for the company. They need to know the impact of their effort and the end goal. Are you using it to track sales or returns in a timely manner, to improve day-to-day visibility of your operations, or to track and improve customer experiences? Training provides the crucial opportunity for communication around your overall vision and desired results and then practically equips employees to be a part of that vision.

 

4- Data visualization isn’t a seamless part of employees’ daily workflow.

Data visualization shouldn’t be viewed as a hindrance or an interruption. Obviously, employees will have to learn how to use the data visualization tool, and there might be a learning curve if they are still gaining data literacy, but by the end of training, employees need to be equipped to practically use data visualization within the context of their current workflow. If it’s not integrated into their workflow and data visualization isn’t brought up as a matter of course in meetings or discussions with employees, there’s a greater likelihood that they’ll opt to making decisions the same way they used to or making decisions without the data.

Integrating data visualization into an employee’s workflow can be as easy as making sure, for example, that the dashboard with data on customer engagement and purchases is available on the CRM platform that the employee will use when communicating with the customer. It might mean that a salesperson has a specific link on their desktop to a dashboard with their performance, and that might coincide with their manager requesting that they bring up that dashboard in weekly or monthly performance reviews. It could look like assigning one person within the department to create a visualization weekly that everyone discusses on the team’s Slack channel at the beginning or close of the week.

The information that needs to be digested should be made as easily available as possible at a decision point to get the most value out of data visualization. Is the visualization available when the employee needs it? Do they understand when throughout their day they need to use it? And does their manager or department head follow up on the metrics with them, setting the expectation that they consult the data to make decisions? All of these factors will determine whether data visualization is a seamless part of the employee’s workflow or a second thought.

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A final note to consider when adding data visualization to employees’ daily workflow- a few things can hinder employees’ motivation to use data visualization. If there are too many dashboards to sort through in Tableau and employees aren’t trained to remove unnecessary or old dashboards, employees might opt to not view dashboards at all. Additionally, if a dashboard is so cluttered or full of information that employees can’t quickly look at it and gain insight, this lessens the likelihood that employees will use it regularly. Lastly and in the worst case- if your data doesn’t seem trustworthy and employees often experience that the data on the dashboard doesn’t seem accurate or up to date, then there isn’t incentive for them to access regularly. Your data must be trustworthy, updated regularly, communicated clearly, and easily accessible in order to be a seamless part of employees’ workflow. Otherwise, they risk wasting their time and could lose trust or passion for the data.

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5- Your visualizations do not clearly communicate business value.

Finally, do your dashboards communicate clearly and deliver more than just information for information’s sake? With adequate training and combining data literacy, proficiency in using the data visualization tool, a few data visualization best practices that they learn in training, and their own business experience, employees can create dashboards that clearly communicate valuable business insight and have business impact.

Dashboards that don’t communicate business value clearly are either too intricate, are made without the audience and their data literacy level in mind, don’t extrapolate further on the data if it’s very detailed, or don’t make conclusions from the data apparent enough in the visualization. These miscommunications often come up when the person creating the visualization doesn’t understand how it will be used or have knowledge in that area of business, or they may create a visualization that is more intricate than the understanding level of those reading it.

Clearly communicating business value through visualizations is crucial when it comes to using visualization for effective presentations or communication during meetings. People need to know what to do or takeaway from a visualization after seeing it, and the person who creates it should fill in those gaps for them without leaving room for assumptions. The visualization should be detailed enough to provide value but simple enough to provide key takeaways. If it needs to be extremely detailed, the creator can get around that by providing summary statements with the visualization.

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A few other ideas for communicating business value effectively in visualizations include:

  • Communicating in layman’s terms as necessary when presenting complex data
  • Summarizing conclusions and findings
  • Adding glossaries to the visualization if the audience needs it
  • Including why this data is important, whether in the presentation or on the visualization itself. (Answer what practical impact this information has on the business.)

One of the best ways to ensure that dashboards deliver business value is to train employees to always tie the creation of a dashboard to a purpose, initiative, or use case. Design dashboards with the most pertinent information around the dashboard’s purpose and eliminate unnecessary information.

Also train employees to keep the end viewer and their data literacy level in mind and to design the visualization around how they will use it. Deliver visualizations in a way that the viewer will best be able to digest. If an IT employee is designing a visualization that will be used regularly in sales, this could be as simple as asking the salesperson what they need to know most often about a customer before they get on a call and designing the dashboard around that. They also should consider what types of visualization or data presentation the salesperson is familiar with. For example, if they’re not used to reading a certain type of chart or haven’t learned how to use it yet, design something simpler so that the dashboard still delivers quick value until they learn to read more intricate visualizations.

This type of open communication will allow the designer to make the visualization as detailed or simple as necessary and only convey useful information. (Better yet, if you equip employees to make these visualizations for themselves, they can tailor their dashboards to their own needs and see immediate value.)

By designing dashboards around specific business processes and for the right audience, you’ll see the greatest return on your investment in data visualization, and employees will be energized by including visualization in their workflow rather than overwhelmed or more confused because of an overabundance of data.

 

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