An analytics strategy offers many benefits to your organization and now more than never, analytics is changing the way organizations run their day-to-day operations.
For your organization to stay relevant in the minds of your members, your team needs an analytics strategy to guide the decisions, so you can deliver an optimal customer experience. Without a proper analytics strategy, you’ll see a loss in productivity among your team members, incorrect decisions being made, and an incohesive customer experience.
With these costs in mind, it’s worthwhile for your team to invest the time and money into an analytics strategy.
Wondering how to even proceed with developing an analytics strategy? Consider breaking it up into these 4 focus areas.
1. People
An analytics strategy isn’t tangible without a team of people who see the value in having data analytics. When building an analytics strategy, one of the first things you need to do is assemble a team. This team is comprised of data champions in key business areas. These people also assist in creating a training plan that helps those who are not as data literate. This is also a good time to evaluate the need to staff additional people to get the analytics strategy off the ground.
Creating a data culture is not an easy task, but it’s by no means impossible. A strong emphasis needs to be placed on change management and even after your analytics strategy has been created, it’s essential to continue to empower your team to use data to guide their decisions. And for incoming hires, incorporate data literacy into their onboarding.
2. Process
Processes play an instrumental role in moving an analytics strategy forward even if there are bumps along the road. In some cases, organizations might not have established processes in place when it pertains to data governance. And when you’re accustomed to not having processes, this leads to poor data quality and redundancy because there’s no established way of entering in the data. Implement a repeatable process to get your team into the habit of inputting data the correct way to improve data quality in the long-run. And don’t hesitate to review and refine the process over time.
3. Technology
When creating an analytics strategy, you need to examine all the systems your data could be residing in and then determine which data is the most accurate, up-to-date, and relevant. Ideally, your data needs to reside in one central repository that’s accessible and viewable across your organization. And ensuring data accuracy is essential to maintaining the integrity of it so it’s seen as the “single source of truth.”
Having the data in a central repository isn’t enough to utilize to its full potential though. You need a tool that allows you to view it in a visual manner to effectively tell your data story. Charts and graphs present data in a way that’s easy to convey to your team. Think about it – what’s more likely to carry credibility among your team? A bar graph or a spreadsheet full of numbers? It’s easier for the mind to absorb a data visual than a page full of numbers that may or may not be relevant to your audience.
4. Data
Data is what ultimately guides your organization’s strategy because it reveals what your members want from you – be it better products or services, an alternative way to communicate with them, or even membership renewal opportunities. However, data is only as valuable as what you already have so it’s imperative that it’s accurate and consistent. If you have multiple data sources, then it’s hard to pinpoint which data is ultimately the “single source of truth” your team relies on. Let’s take a simple example of an email blast for membership renewal. What happens when half of those emails bounce back to you because the email addresses were incorrect?
Inaccurate data leads to distrust in it and a loss in productivity trying to track down the correct information. In order for your analytics strategy to come to fruition, a data cleanse needs to take place before it moves to a single repository. Consider performing a data cleanse every quarter to maintain the upkeep. Some other best practices to keep your data in good shape are to create a data dictionary and to conduct a data augmentation.
At the end of the day, analytics is all about outcomes. When you have an analytics strategy in place, you’re emboldened to make decisions faster because the data is consistent and accurate. This in turn impacts other areas of the business, the team’s productivity, and your members. A data analytics strategy creates an enhanced member experience by allowing you to deliver targeted, relevant member communications and product and service offerings aligned with member preferences. And when your messaging and offerings resonate with your members, you’ll see more conversions which helps drive revenue.
Learn More About DAMM for Associations
To learn more about our DAMM for Associations and what a data analytics model can do for your organization contact us and sign up for our monthly newsletter.
