Sprinting Towards an Open Source Platform

Author: Jessica Langelaan, Non-Profit Practice Lead at Traction on Demand
Audience: Non-profit organizations
Technical Understanding: Moderate
Cloud: Salesforce.org with the Nonprofit Success Pack


NPSP Sprint

Earlier this month, a community of Salesforce admins, developers and implementation partners came together to “sprint” towards a better NPSP for all users.

Two weeks ago, Salesforce.org hosted a two-day NPSP Sprint in Chicago. The Sprint brought together a community of non-profit admins, developers, app partners and implementation partners (like Traction) for two days with the single goal of making the Nonprofit Success Pack (NPSP) better for everyone. Sprints have happened across the States and are a great example of the unique, community-driven development of the NPSP.

So much happens in those two days, but the reason we’re all there is the same: to come together and help non-profit organizations make a difference on the platform.

Sprinting for NPSP

Throughout the Sprint, there was a mix of reflection on the past, a focus on the present and a glimpse of the future. When Salesforce.org had less than 10 employees, a group of 20 community members came together to begin sorting out a consistent framework for non-profits on the Salesforce platform. Now the NPSP Sprints build on Salesforce’s expanding capabilities to help non-profits manage all aspects of their organization on a single platform with centralized data to back it up.

Chicago was my second NPSP Sprint, and I had two key takeaways:

  • There’s a lot we can do to make a difference in the community right now. With 90+ people working towards a common goal, we accomplished a lot in two days.
  • Salesforce is going to keep evolving and NPSP Sprints enable non-profits to use these new capabilities to the fullest. Einstein, Salesforce’s artificial intelligence (AI) offering, is next.

Making a Difference in the Community Now

With 90+ people in the room, there were more than 12 topics covered in two days. From volunteer management to impact tracking, everyone had the chance to contribute where they were interested, and could add the most value. For the most part, my most difficult decision is choosing what I’m I willing to miss out on, in order to add value elsewhere!

Collaborate at the NPSP Sprint

Collaboration is key to an NPSP sprint! Everyone has a chance to contribute and provide value.

As I surveyed the opportunities to contribute, I zeroed in on working with the team finalizing documentation on the process of upgrading to Household Accounts. Although the conversion utility has been available for a while, the supporting documentation was limited.

Together, we created documentation that provides advanced system administrators and consultants guidance to move from the historical data model, with custom Households, to leverage Accounts as Households. The upgraded data model enables your organization to:

  • Take advantage of new NPSP features as they are built.
  • Engage constituents efficiently with a complete understanding of each household.

My hope is that the work we did becomes public shortly and that organizations that haven’t yet converted, find the documentation helpful to make the jump!

Keeping an eye to the Future

One of the areas of focus for the Sprint was Einstein. It’s a relatively new offering that brings together several of Salesforce’s AI offerings. It will be a few more Sprints before we’re actively building content that can leverage this functionality, but in the meantime, here’s my take on the upcoming offerings and potential uses in the non-profit sector.

  • Image recognition as a service: This service lets you leverage existing image classifiers, or create your own, to bring an image recognition use case to life. For example, an organization may use image recognition to scan responses to a direct mail campaign or read cheques.
  • Natural language processing: This data processing recognizes language and the many ways it can be used (grammar, short hand, etc.) to find patterns across large datasets. A non-profit may want to use this capability to match volunteers to volunteer opportunities.
  • Machine learning: Machine learning looks at mass sets of structured data to find patterns and outcomes with limited programming. This opens the opportunity for non-profits to begin scoring Leads to determine who has the highest propensity to give.

The timing to make each of these examples a reality is still to come, but I expect we’ll be putting machine learning to work in 2018. Stay tuned for more on Einstein at Dreamforce 2017.

I had an amazing time in Chicago getting to meet and work with the NPSP community and I can’t wait to see what we’ll achieve in 2018. If an NPSP Sprint sounds like something you’d be interested in, keep an eye out on the Power of Us Hub for details on 2018 Sprints.

Check out #WhyWeSprint on Twitter to hear from more Sprinters.


 

resize-sara-dicksonWritten by Jessica Langelaan, Non-Profit Lead at Traction on Demand.