ORI News

Data Analytics Steps

6 Steps for Successful Data Analytics

How to Turn Your Association’s Data Into Dollars

By Taylor Clarke, Data Analyst, ORI

Overcoming data challenges is a daunting task for most, and associations are not immune. Obstacles such as a lack of easy access to data, a lack of capacity to analyze data, or changing member expectations can severely impede your association’s ability to truly understand your members. Figuring out how to overcome these hurdles is imperative to the success of any organization—and, increasingly, the topic of conversations ORI is having with association executives. So how can your association overcome the multitude of data analysis challenges that may be keeping you from better understanding your members? Gaining clear insight into customer needs is an important step in creating value and ensuring revenue growth in the future.

The key to winning the race to competitive advantage is to tackle your data challenges with a strong strategic focus. The objective is not to simply store all the data you can get your hands on (or to clean it, for that matter). Rather, you must use data to derive value and insight that can be tied to a business plan driving actionable outcomes, return on investment (ROI), and profitability. ORI recommends six high-level steps to begin your data journey and succeed with data analytics:

1. Identify business use cases tied to key business outcomes. 
Align your analytic efforts with critical growth strategies. Each strategy should have hypotheses that are tested through continued measuring and tracking of defined key metrics.

2. Designate data champions from both the business and IT sides of your association. 
Select internal team members (ideally from different areas of the organization) with an aptitude for data analytics to work toward progressing the cause of data through the entire organization.

3. Select infrastructure, tools, and architecture for your data project. 
Ample tools and services exist to help your association navigate through planning and executing your data project. Utilize tools that your data champions and staff are comfortable using, but be prepared to manage change as traction gains.

4. Staff your project with the right data/analytics resources or a strategic data implementation partner. 
While your own data champions might lead the way in advancing data within your association, they may need resources from which they can draw help. Choosing a partner who is flexible and can work with different project management approaches to deliver the value you need is essential.

5. Run the project in sprints or phases, with tangible and measurable outcomes. 
You must walk before you can run, so take one step at a time. Prioritize key business areas and aim for successful implementation of one area at a time. As you make progress—and can demonstrate the return on strengthening the quality and usability of your data—senior leadership can justify subsequent investments in the next phases of your project.

6. Establish data integrity protocols. 
Evaluate your data early in the process to gain an understanding of what elements are truly critical and require improvements now in order to allow for high-quality, data-informed decision making. Additionally, define how this data quality will be maintained going forward and begin discussions across departments and operating units to frame data as an organizational asset that is everyone’s responsibility.

To help ensure successful adoption, you need the support and buy-in of leadership and staff. Your data champions and analysts also need to commit to spending time training, providing analysis, and working more generally with the team. Communication throughout the project is key, so be prepared to continuously demonstrate value through sharing “quick wins” and success stories. Publicize and promote internal data analytics work in much the same way you would promote external benefits to members. Data always tells an interesting story. Pick an area and provide a weekly summary to the team about the “story in the data.” Offer examples or surprises found in the data that defy any preconceived assumptions. Encourage the analytical mindset by posing a “question of the week” or highlighting “flash insights” to increase visibility and stimulate interest. Much like data can help you better understand your members, effective data analysis can also bolster your association’s internal structure and ingrain its value in your culture.