Jasmin Ritchie - Mar 10, 2015

Small Steps on the Data Analytics Journey

When my son says, “Mom, I want to be an astronaut and go to Saturn!”, I ask him, “What can you do now to make that happapollo11_footprinten?” Granted, he’s 4, so he often needs my help to answer that question. Since I’ve never been an astronaut and never been to Saturn, it’s a bit of a stretch to help him. But, what I do know is that he’ll need to understand mathematical concepts, physics, he’ll probably even need to know mechanics and how things fit together. When you break it down like that, even at 4, he can set small goals for himself to learn to add small numbers, put together a 50 piece puzzle and learn about gravity by doing a simple experiment. Next month, we’ll have new goals.

So, what does this have to do with you and your goal to enable your association to make data-guided decisions every day? Well, it’s easier than going to Saturn!  Start by taking small steps each day. The next small step for you may differ from your colleagues at other associations because your starting place and circumstances are different. Sure, you likely have many roadblocks – your data may be of poor or unknown quality, you may not have all the data you need or you may not know how to pull all the data you are storing in many different places and in different ways.  And of course you may be dealing with lack of resources or limited budget.

The key is to focus on one deliverable that you can get done quickly (quickly may be a couple of weeks or a couple of months). Here are some examples of small steps.  It’s just a starting point to get you thinking.

  1. Make sure you have zip codes for all your members.
  2. Do an inventory of all your data related to one business question.
  3. Capture your AMS’s primary individual identifier in other data sources (google analytics, LMS, etc.)
  4. Create a mini data mart and visualization based on one business event (registering for conference, purchasing a product).
  5. Pick a few key terms used within your association and make sure there is consensus throughout i.e. make sure everyone’s definition of “new member” is the same.
  6. Identify duplicates based on one criteria and combine records.
  7. Make key fields required in the source system.

Of course, we’d be happy to help your association take this journey (made up of single meaningful steps) to data-guided decisions.

Written by Jasmin Ritchie