In today’s world, leveraging data to further your organization’s cause or mission is a must, even for small organizations. The struggle for many organizations, unfortunately, is that few (if any) existing team members have the necessary analytic training to support the team or project to the extent that is required. As a result, organizations find themselves in dire straits and often scrambling for a “good-enough” solution. For example, when an RFP is released there will be a flurry of emails to see if anyone knows of an analyst who may be able to drop everything and jump on a call (or ten) to help sort through issues. In some cases, certain opportunities are not pursued because analytic support couldn’t be secured or was too expensive. In other cases, efforts are duplicated or wasted, or data remains untouched and unused, potentially abandoning tremendous potential for knowledge gains.

When trying to contract with an external firm or individual for analytic support, organizations often struggle to even get started:

“We can’t seem to find an analyst when we really need one.”

“We don’t even know where to start; how do we know at what stage we should involve an analyst?”

If they are able to locate someone, the experience itself often leaves much to be desired:

“The person we contracted with didn’t seem to understand what we needed.”

“They offered us a ‘cookie-cutter’ solution when we really needed a custom solution.”

“We just couldn’t afford what they said it would take.”

In response to these types of experiences, more and more organizations are exploring alternative models of analytic support, including subscription-based membership models.

In a membership model, the organization invests a low monthly fee to have access to analytic expertise and resources whenever they need them. This has several benefits:

  1. It eliminates challenges associated with finding analytic help. Instead of scrambling to find someone when an RFP is released, there is already someone familiar with the organization and their goals, who is ready to help.
  2. It allows for greater planning and efficiency; the analyst gains an understanding of the organization and its mission, and can anticipate the needs of the organization and help guide project planning to minimize wasted or duplicated efforts.
  3. It is much more affordable than employing an analyst, and spreads the cost of analytic support over a longer period of time, allowing the organization to plan and budget for their analytic needs.
  4. It fosters a data-driven culture where measurement and evaluation are seen as an integral part of achieving that organization’s mission; there is on-going thought, discussion, and learning about analytic concepts and how to think about them.

For many, these benefits encompass the driving force behind the decision to leverage this type of model. Depending on the type of membership, it may also provide specific training resources and connection opportunities (meetings, calls, etc.) with other organizations facing similar analytic challenges. For some, there is an interest to connect and share best practices with others in their industry or area.

However, membership models are not without their potential pitfalls. The two most common include: 1) the organization fails to utilize the service they pay for, and 2) their needs don’t match what’s offered. The first case happens when the organization has high hopes for leveraging data and analytics but never takes the time to pursue it. Membership models are great when there are no specific goals identified and there is simply a need to prepare and be ready for analytic needs that will inevitably arise. But, without a specific goal in mind other priorities can take over within the organization. To avoid this, organizations should collaborate with the analytic support to create a plan for how they will integrate analytics into their current working processes. The second case typically occurs when there is a disconnect between what the organization thinks they’re getting and what they’re actually getting. Many analytic membership models will be advisory only. That is, you are paying for access to analytic expertise to answer questions and receive guidance, but to have analysis performed or deliverables created, there is often an additional fee. Make sure you understand the terms up front, and ask questions using real examples to understand the support you would receive (e.g., “Last year we needed an analyst to draft language for a proposal and create an analytic plan – how much of that would be covered in the membership and how much would be extra?”).

For the most part, those pitfalls are rare because organizations who are ready for an analytic membership model already know what they want and why. Often, the have previously “felt the burn” of not having analytic expertise when they needed it, and have made the decision that it’s too important to not have a plan going forward. In general, organizations who chose to pursue these types of engagements tend to be similar in a few ways:

  • They believe that “data literacy” is no longer optional and shouldn’t be limited to a few members of the organization; they believe the organization benefits when everyone develops an understanding of measurement and evaluation.
  • They want real, practical, and custom solutions that will have an immediate impact on their ability to carry out their mission.
  • They want access to information, resources, and an expert on-demand, so that data and analyses inform and support their larger efforts, as opposed to being a barrier that stands in their way of doing their job.

It can be a bit of a mind-shift for those organizations who have lacked analytic support in the past. But, for those who are able to find a good fit, they often find it to be an invaluable – and affordable – tool for achieving their mission.

If you want to learn more about the membership model I offer, please visit:

And, if your organization utilizes an analytic membership model (or has previously), I’d love to hear about your experience with it!