Building a Dashboard: Framing the Problem and Getting Started Outline Goals and Objectives Mapping Out Project Timelines and Resources Step 1: Acquire and Explore Step 2: Designing the Front-End Step 3: Designing the Back-End Conclusion About Chisel Analytics:

As mentioned in our prior article on on dashboard development, framing the problem is a critical first step in your process, and one that will ultimately drive utilization and outcomes if done correctly.

It sounds simple, but it’s also equally important to outline and follow a project plan. Doing so will allow you to effectively organize your efforts, keep the project going, and ground you to core goals and objectives.

Outline Goals and Objectives

Goals should be your long-term expected outcomes for the project.

For example, perhaps you’re aiming to increase customer satisfaction or sales. From there, you can outline the tactical objectives that you believe will help to achieve these outcomes.

At a high level, these objectives could be to build the dashboard itself or increase the utilization of an existing one. These objectives are good starting points but should also then be decomposed into sub-elements and planned for and supported accordingly.

Concrete stepping stones to developing a dashboard might include acquiring the relevant data, highlighting initial insights, designing the front end, and creating a data pipeline to regularly ingest and update the data as new information becomes available.

Objectives for increasing usage might include scheduling training sessions for analysts or executives, conducting outreach, and presenting use cases.

Some useful questions to ask yourself when defining goals and objectives could include:

  • What is the purpose of the dashboard?
  • Who will use the dashboard? For what purpose or decision-making process?
  • What outcomes are you trying to measure?
  • What patterns or insights on customers, sales or operations are you trying to discern?
  • What previous trends or patterns have you anecdotally noted that are worth monitoring?

Putting Goals and Objectives into Action

Once you have defined these objectives and goals, you can then lay the road map for how to proceed. As discussed in Designing Dashboards, a useful procedural framework for building a dashboard would be:

  • Outline
    • Define Goals and Objectives
    • Decompose the project into distinct phases (as shown here)
    • Map out anticipated project resources and timelines
  • Acquire + Explore
    • Acquire the relevant data, as planned in step 1.
    • Begin to explore the data; what relationships exist?
    • Optionally, you may also wish to build some initial data models
  • Design
    • Take a look at your explorations. What visuals (maps, charts, tables, etc.) are most compelling and relay outcomes effectively to the user?
    • Begin to layout the dashboard and supporting detail
  • Back-End
    • How is the data currently formatted? (Raw Text, HTML, JSON, CSV, SQL, MongoDB, etc.) Is there a better format?
    • How will new data be ingested? Are there live data feeds that power the dashboard? Outline how the data will make its way from the wild into your preferred formatting.
    • Will you need to add more data later? Keeping this door open is often advantageous.
  • Implementation
    • You probably have most of what you need at this point to stand up the initial dashboard. Finish actualizing the front-end and back-end and then link them together for your initial working prototype!
  • Iterate
    • Once your initial prototype is operational, return to your original goals and objectives from step 1. Did you meet them? What new goals and objectives would you now set?
    • Continue working towards your updated goals and objectives, and repeat subsequent project stages.

This outline is not set in stone. Certainly, some will prefer to build the back-end infrastructure for the dashboard before proceeding to design the front-end visual layout.

Whatever process you choose to follow, be sure to align your work to the goals and objectives you defined. While new insights are apt to surface and pull you in new directions, mapping out a project plan will help keep the project on track and aligned to your intended outcomes.

Mapping Out Project Timelines and Resources

Mapping out project timelines is a fuzzy endeavor, as it can be hard to anticipate all of the nuances and challenges which will inevitably arise. That said, all projects are bound by time and resource constraints, so estimating these factors is essential to making an informed cost-benefit analysis of the work involved and benefits gained.

Determining where to allocate time and resources will also depend on project specifics as defined by your objectives and goals.

For example, a client-facing dashboard warrants additional focus on design and aesthetics. Similarly, a dashboard that is meant to serve live updates by the minute or second will require considerably more focus on back-end optimization than one which is updated weekly.

Of the project phases outlined above, the time required for data acquisition and exploration will likely have the most variation. You may already have data on hand and have a deep familiarity with it. Or, you may have no formal data and this is a completely new endeavor. If so, the acquisition phase will probably require some form of preprocessing, depending on where the data lives and how it is to be used.

No matter what, some form of data exploration is warranted. Focus on a minimal viable product, and which directions are most aligned with your overall goals.

In assessing these needs, here are some further questions to ask yourself in planning the various stages:

Step 1: Acquire and Explore

General Questions:

  • What data do you have on hand?
  • What data can you acquire?
  • What do you expect the data to show?
  • Are there specific patterns or trends you want to explore?
  • What are you trying to measure? What variables do you think would influence decisions?
  • What are the Key Performance Indicators?

Timing / Resources:

  • How complex is this data?
  • How much preprocessing will be required?
  • Where is this data stored?

Step 2: Designing the Front-End

General Questions

  • Who will use the dashboard?
  • How important is UX/UI?
  • What tables, maps, charts, or other representation would be most clear, compelling, and insightful?
  • How can you present the KPIs?
  • What interactivity can be integrated? (Search? Filtering? Toggle buttons? Drop-down menus? Hovering over data points? Selecting data points? Panning and zooming maps? )

Timing / Resources

  • Will a template suffice?
  • Can you use Tableau, Looker, or DataWrapper?
  • How much customization is needed?

Step 3: Designing the Back-End

General Questions

  • How often does the data need to be refreshed?
  • What preprocessing is involved to transform the raw data?
  • How big is the data-set(s)?
  • Will scaling be a future concern?

Timing / Resources

  • Will this require a database?
  • How complex are the data-relations?
  • How complex is preprocessing or modeling?

Admittedly, there is no substitute for a working knowledge of your team’s abilities to execute these phases and the maturity of your data infrastructure. A skilled practitioner may be able to design a Tableau dashboard in hours or less, while a custom JavaScript version that relies on a complex set of information could take considerably longer.

Similarly, building a database might be a routine endeavor, or require extensive design, depending on the scale and complexity of the information. No matter what, building an initial prototype and iterating is an advisable approach. Working through the full process will create a natural feedback cycle where you can assess strengths and shortcomings from end-users, allowing you to make informed decisions for how to update and improve your dashboard.

Conclusion

Outlining a project plan when creating a dashboard is essential to a productive and timely development process. While new obstacles and insights will surface during this process, this initial plan will ground you to tangible outcomes, helping to define project needs and direction. With this vision, you’re bound to have dashing results!

About Chisel Analytics:

At Chisel Analytics, we are focused on helping organizations make headway with their information. From data engineering and acquisition, to advanced analytics and data science or machine learning implementations, or dashboard design and development, our teams can help you move forward — quickly. Our advisory and talent solutions can help you define your roadmap and build the team you need to move forward. Contact us today to start turning your data into action. 

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