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Author: Meredith Low

Don’t let yourself get overwhelmed with the idea that you’re supposed to capture and analyze enormous masses of data; instead, focus on creating an organizational culture that enables evidence-based decision-making. 

Big Data is clearly a Big Trend - but so is “not-so-big data,” as we all become accustomed to ready access to unprecedented amounts of information in all facets of our lives and our work.

The costs and capabilities to gather, store, and analyze data have dropped astronomically in the past decade. Concurrently, our expectations about what information our service providers have at their fingertips – and what we are entitled to know – have skyrocketed.

But to focus on the sheer volume is to miss the key insight of this age of data: we’re drowning in data but not getting nearly enough information from it.

Associations are frequently sitting on data they don't maximize, and often don't gather data they could easily obtain. They also struggle with the cultural and political shift to a data-driven organization.

This isn't an issue about expensive IT systems; it's about developing the soft skills, the organizational culture, and the governance habits to master the new information age. The anecdata and “focus group of one” perspectives among staff or around the Board table can give way to framing issues in terms of an answerable question and then finding the data to answer it. Good data leads to good decision-making. 

The key to becoming more evidence-driven is to start by seeking the information that can add to the quality of decisions we make – what would we want to know, in an ideal world?

Then we can take the data we have – often that’s a lot already – and make it really work for us.

Finally, we can reach beyond, to gather data we don’t have now – but do so intelligently.

All of this will require a cultural shift which often challenges deeply-held ideas about the association. (But if you don’t learn anything new from this, what was the point?)


What do you want to know?

Even the companies using big data tend to forget to ask the right questions. Being purposeful about data-gathering and analysis means taking the time to think about what you will use the data for – and being open to surprises along the way.

  • Don’t rush to methodology. Take the time to define the outputs you want. What if you could find out anything you wanted to? Then you can figure out proxies or substitutes for information that is overly costly or downright impossible to get. This can be a surprisingly interesting question to answer when you really get into it.
  • Include both strategic, high-level information objectives, as well as operational data. Think of it as a car trip. You want to read road signs to tell you how far you are from your destination and whether there are curves ahead, but you also need to know how fast you are going and whether the oil light is on.
  • Engage the end users of the information. Spread the net a little wide here to include people and functions that you think might possibly benefit, and see if they can provide insight into both sources and uses of data.
  • Make sure you attach enough resources.  It takes time to pull together reporting, especially if it’s a new function for your team.
  • Expect iteration. Once you see reporting, you will learn from it, and it will raise additional questions – and the organization or environment will change in the meantime.

Use what you have


  • Use the full functionality of the systems you have. Typically organizations only use a small portion of the potential of software systems such as member CRM software or online services like Mailchimp or Google Analytics. Go back to your original training, or bring in your service provider to help you ramp up your usage of the system to extract the maximum information – or check online resources. 
  • Broaden your analytical toolbox. Frequently data is reported just on a year-over-basis; to see trends, expand to a 5 year period. Explore whether there are ratios that might help you tell a story – sometimes simple manipulations of the data, driven by an understanding of what you want to know from it, can be very compelling. Play around a bit.
  • Segmentation is an underused way to extract additional meaning from data, and basic segmentation doesn’t have to be overly complicated. However, it does have to be relevant to the natural differences in the data, not arbitrary.
  • Consider hiring, contracting, or training specifically for analytical skills, but be thoughtful about what you need to keep in-house for organizational learning.
  • Ensure employees are sharing analytical techniques with each other. This could be as simple as arranging lunch and learns or having them walk each other through their work.
  • Validate the analytics that are being done from time to time. Especially in a small organization, or where reporting is concentrated in one or two people, it’s easy to fall into a rut and overlook assumptions or quirks in the data that may turn out to be important. Do a review of sources, models, and assumptions annually, or before major decisions.

Gather what you need


  • Review your data intake points to see if they meet your needs. Should you be collecting twitter handles from new members? Can you ask conference registrants their top reasons for attending? Should staff be logging calls from members?
  • Make your data gathering consistent year-over-year for comparison. Change it judiciously when the novelty is more valuable than the ability to track changes over time.
  • The age of Google means cost-effective data collection is possible, even for small organizations.
    • Google alerts – set them for your organization, other relevant organizations, keywords that matter to you, and so on. You will be informed if they hit the news.
    • Social media – monitor your hashtags, even weekly, to track activity. As you get more sophisticated, there are social media monitoring tools available. 
    • Scores like Klout and Kred can be tracked to get a measure of your online influence, although they are nascent.
  • Surveys can be done for free via online tools such as Survey Monkey – but use them knowledgeably and sparingly. Ensure there’s time and expertise available to design and analyze the surveys. And don’t be too survey-happy as members may find it annoying.
  • Full Member Needs Assessments should be performed regularly but, to be successful, need experienced guidance.

Making the change


  • If you’ve taken the time to design properly in the first place, you should already know (some) decisions this data will influence. Make sure the data and analytics are integrated into the decision-making process, whether that’s Board-level analysis, management team decisions, or elsewhere.
  • Be alert for amnesia setting in – people tend to forget they “know” certain things organizationally, and settle back into the notion that certain things are non-verifiable.
  • Get – and stay – creative about using the results. Think hard about what the data is telling you, even if you are curious about something that goes beyond the existing questions.
  • Be transparent. Data sources should be accessible to as many people as might be able to use them, ensuring proper data integrity and privacy requirements are in place. Communicate assumptions and calculations clearly.

Don’t boil the ocean to cook a couple of fish

A more evidence-based organization results in clearer, stronger, more robust decisions. And you don’t need to be IBM or Google to get there. You don’t even need to transform the organization overnight to get started.

The last thing associations need is a complicated black box approach to data, or to be paralyzed by the onslaught of information. Connect your strategic and operational requirements to produce information you will be in the habit of consulting on a regular basis. And query your data – use it to ask good, relevant, useful questions – and to spend enough time with it to let it point us towards questions you haven’t asked yet – but now will be able to answer.

In the end, a great understanding of data aids in story-telling, about where you are, where you’ve been, and whether you’re going in the direction you want to go.