Analytics adoption: Creating data visualizations people will actually use
If seeing really is believing, then data visualizations are one of the most effective ways to convince stakeholders and end users to take action. A well-designed dashboard, populated with relevant analytics, condenses even complex information into an accessible form, so that viewers can extract at-a-glance insights and streamline their decision-making processes.
In this way, visualizations are effective remedies to the problems of information overload. Many workers regularly waste considerable time searching for the right data points, unsure of where they’re located or whether they’re even fresh and applicable to the projects at hand. Dashboards and other visual creations cut through the noise — as long they’re tailored to match user requirements and supported by reliable data sources as well as sustainable processes.
The recipe for a practical and useful visualization
A data visualization is only as good as its level of adoption — perfect design counts for nothing if the analytics surfaced by a dashboard don’t mean anything to the audience. Ensuring that they do requires a multi-step process, beginning with user and stakeholder input.
Gathering and synthesizing input
The analytics within a visualization should be clear answers to specific questions from stakeholders and users, such as “why is our Net Promoter Score declining?” or “what is the sales forecast for the next quarter?” A visualization will ideally provide the insights that can be turned into corresponding actions. That might mean it illustrates a key relationship between business trends or supplies a real-time stream of information that serves as a vital sign of a project’s status.
Interviews with users and stakeholders will clarify which questions are most in need of the answers that visualizations can provide. Use clear language and gather continuous feedback so that you always have your finger on the pulse of the primary audience of the visualization — these steps help you determine what KPIs and data sources to incorporate into a dashboard or other product.
As part of the interview process with both the users and the stakeholder, you will also define what the user action should be, based on the data. By thinking through what the exact user action should be before you build the dashboard, you will be able to drive change in the business.
Optimizing data sources
Just as it’s a good idea to regularly connect with the people who will use the visualization, you should also kick the tires on the underlying data that will support your creations. It’s far from given that everything will be perfectly set up for a sophisticated dashboard without requiring some optimization and fine-tuning first.
Without getting too far into the weeds, the technological issues associated with building data visualizations run the gamut from storage-related challenges that might necessitate new and additional cloud computing services, to the need for middleware to glue together disparate systems. An experienced partner with a technology-agnostic approach can navigate these risks and many others en route to building the right infrastructure for sustaining your visualizations.
Managing change and iterating on success
According to Aristotle, excellence is a habit, not an act. This wisdom is as relevant as ever for analytics projects, which require continuous attention to remain valuable to end users and stakeholders.
For example, ongoing training can help employees prepare for new project roll outs and learn the ropes early, perhaps even through carefully structured pilot phases. Compiling user feedback is also the perfect bookend to a process that began with gathering user input on initial requirements. This feedback is invaluable when expanding upon an originally sparse design and making decisions about particular elements like colors and layouts.
To learn more about the road to analytics adoption, check out our full eBook on analytics adoption or connect with the Logic20/20 team of experts today.
