As you begin a new project with data visualization firm or partner, here are a few things to keep in mind that will help streamline your efforts.
1. The most important thing you can do before you start a data visualization project is to make sure your data is clean, well-structured, and complete.
The root of a good data visualization is in the strength of its data, and your data visualization partner will need to understand its relationships, codes, and the mechanics of accessing it. Whether you plan to create your visualization internally or use an external partner, the better organized and more complete your data is, the better your results will be.
2. Be prepared to work with a data scientist, analyst, data wrangler, or a statistician to reveal your data’s patterns, trends, and outliers.
Compelling data visualizations are designed to reveal insights, and these come from careful analysis and planning. If you haven’t already conducted internal research, look for a data visualization partner who can do analysis as well as design. Many data partners will rely on you to be the domain expert.
3. Data exploration tools are often used in scientific and analytical settings and can be the best way to provide access to your data when a point of view is not required.
Sometimes the goal of your project will be to develop a tool that allows others to explore your data and find their own insights. Tools such as these are particularly useful when viewing real-time data, including social media content, automated data collection efforts, and time-sensitive information.
4. Whether you plan to do your visualization work yourself or with a partner, the success of your project will depend on how well you define your requirements.
Your project’s definition will largely be informed by your data analysis, because what your data reveals will influence how you present it. Identify your target audiences, your goals for each, your organizational and technical requirements, key internal milestones, and set a budget. The more information you can provide, the easier it will be to develop an effective solution.
5. The creation of a data visualization is often a group effort that can span many weeks or months, and involve a distributed team of specialists.
Many data visualization efforts are complex and can involve multiple people or groups at various stages. Most require input from a domain expert, a database administrator, a client decision maker, a project manager, and skills covering strategy, design, and potentially technical development. The contributors to your project will look to you to ensure access to data, services, and information are all handled efficiently.
6. Consult with your communications or marketing group to obtain a copy of your style guide, brand guidelines, or similar documents that define your identity.
The rules for visualizing your data and presenting it to the public will be guided by your organization’s brand and visual identity. These documents contain information about how your organization should be represented, details about your colors, fonts, logo, and more — and will directly impact the approach your data partner takes when developing a branded data visualization.
7. Your organization’s policies for onboarding a new vendor can often involve multiple people, take many weeks, and might impact your overall project schedule.
Prior to starting a project, alert your accounting and procurement departments that you intend to work with an external vendor. Prepare a Nondisclosure Agreement and other vendor-related documents (like invoicing and contracting terms) before your project begins. Your partner will need to review your data and other sensitive material in order to provide an estimate and proposal.
8. A visualization partner will depend on you to commit to regular meetings during which you will need to provide clear feedback and sign-off on deliverables.
Projects run smoothly when everyone has the same expectations, and this comes from good communication and clear decisions. An external team will be very aware of their project schedule and will require predictable review times and final approvals. Projects can easily be derailed when feedback is unclear or approvals are reversed, resulting in delays or increased budgets.
9. The success of your visualization will depend on the effectiveness of your marketing and promotion efforts.
If your goal is to provide access to your data and highlight its unique findings, developing a compelling data visualization will not be enough. This is an often overlooked aspect of a data visualization effort and it can lead to unmet metrics and lack of engagement. Set aside time and budget in your development plan to be sure to consider how your visualization will be made available to the public.
10. Your raw data will support others who will learn from it, allow for public verification, and will confirm your organization’s commitment to transparency.
A data visualization is a great way to help raise awareness of your organization’s key issues, and providing access to the data that was used to create it is essential. When sharing your data through direct download or an API, be sure to provide access in an easily readable format, and include documentation and a data dictionary.
11. If your project is expected to be delivered in less than 6 months, choose a data visualization partner directly, rather than issuing an RFP.
Defining your project is essential, but issuing an RFP is often not the best way to start your data visualization project. A thoughtful response to an RFP takes time, as does vetting the responses, and this comes at the expense of your overall project schedule. The process is often prohibitive for boutique firms, and consequently only large firms or agencies will have the resources to submit a proposal, often at a higher rate. In many cases, a design brief will be sufficient for your internal and external teams to get started.
12. Do good with data.
The data you have collected is powerful. It represents tiny bits of our world that can lead to insights, epiphanies, and truth. Be aware of the impact it can have when it is transformed from a series of datapoints to a rich visual exploration, and be honest with your presentation methods. It will become part of a larger social conversation and have the potential to change our worldview.
And that’s a great responsibility.