That's nice, but what does it mean?
Nov 08, 2017
What is the most critical deliverable for an analytics solution? It's not the final visual product: the dashboards, the charts and graphs. It's not the warehouse tables, or the extract-transform-load (ETL) that pulls it all together.
The foundation of success for an analytics solution is delivering an understanding of the data available for analysis.
Unfortunately, this crucial element is often passed over in favor of the simpler task of training users on a specific tool. Most analytic tools now offer a drag-and-drop interface, and users can quickly be taught to refresh delivered analyses, glean a basic understanding of that data, and repeat a stepwise procedure to reproduce a similar report. However, this technology-focused approach is not an effective long-term strategy, as it doesn’t fully consider the people behind the tool. What happens when the results of an analysis aren’t what you expect, or you have a more complex research question? That level of abstract critical thinking requires delivering additional user training and guidance on the data itself, beyond the standard approach to analytic solutions. The technology will give you access to your data, but it’s people that give that information meaning.
Learning how to use a tool does not automatically guarantee learning and understanding the data behind it. New users expected to perform analyses with your institutional data first need dedicated training on that data, to explore its sources and discern its meaning before they’re asked to analyze it. Discovering the relationships between data integrated from different sources and across business units takes time and effort, and a commitment from the institution’s leadership to provide training and resources to the staff for whom that knowledge is essential. Without a true understanding of the data, the capacity for effective data analysis is diminished. This can lead to misinformed decisions, and prioritizing the wrong initiatives within the institutional strategy.
An investment in an analytics solution must be more than an investment in technology. It must also be an investment in your institution’s human capital. No matter how you document information describing and explaining the data being made available, the critical part is actually taking the time to teach and explain the data to the people who will be using it. But how do you go about that? There are many methods for delivering this component of the solution. Look for future posts regarding techniques for data governance, training on the data, and managing that knowledge.
The more information you can access, the more questions you will have. You’ve invested time and money in your analytics solution; make sure your investment includes training for your staff on understanding and creating meaning from the data.