TEARS Foundation digitizes data capture and elevates reporting with Yellowfin BI



TEARS Foundation is a non-profit organization (NPO) based in South Africa that provides access to confidential crisis intervention, advocacy, counseling, and prevention education services for victims of domestic violence, gender-based violence, sexual assault and child sexual abuse.

Established in 2012, Founder & Director Mara Glennie created a network that connects survivors of abuse to an appropriate support provider. TEARS sources and collates a specialized database comprising a network of free medical, legal, and psychological services, in order to support all victims of rape and sexual abuse.

“Our path with Yellowfin that got us from paper to electronic systems was basically to not let anyone down. We wanted to make sure we get to every one of our clients in time, every time. If we schedule we need to phone a client on Monday, we now get a pop-up to do so, consistently. This really was the driving force for us – to make sure nobody is left behind.”

Mara Glennie, Founder, TEARS Foundation


Lack of digital database, analytics solution and reporting experience

TEARS Foundation experienced certain challenges around its ability to report on gender-based violence (GBV) data across South Africa, and ensure the accuracy of the statistical information it sourced and collated.

  • Lack of data on GBV, with existing studies lacking tangible data or omitting details
  • Paper-based processes (communication, filing and reporting)
  • No digital reporting solution to present data to funders


“Our biggest pain-point was not having a data system to capture such detailed GBV information,” explained Mara Glennie, Founder of TEARS Foundation. “TEARS used to be a paper-based organisation, and what we eventually realised was there were a lot of important files that fell to the cracks and were not being followed up or being misplaced.”

In time, TEARS identified its desire for better internal capability to collate and report on the very specific parameters across age, gender, race and type of GBV that it wanted to, and assessed the need for a data solution that could assist them in overcoming these recurring challenges.

“We started looking for customer relationship management (CRM) software in 2016 to rectify our problems, but we found many off-the-shelf CRM solutions did not work for our use-cases – follow-up schedules, comments, and the many kinds of gender-based violence we needed to capture to have statistical information on and report. We needed something more capable.”


Scalable embedded BI with greater data capture ability

TEARS was introduced to software development house MIP, who they partnered with in December 2019 to develop the software system it desired to capture GBV in greater detail, while also investigating how the company could accurately and visually report all of that information.

In August 2021, MIP introduced TEARS to Yellowfin, who offered their embedded analytics solution to TEARS pro-bono via South African-based Yellowfin distributor AIGS. AIGS was soon tasked with managing the relationship between TEARS, MIP and Yellowfin and communicating expectations, needs, and business requirements for the deeper analytics that TEARS required.

“Initially, we were only looking for a CRM solution that could capture GBV-related information,” explained Mara. ”When MIP came on-board and told us they could build this, that we could do better, that’s where our journey really started – and, of course, later, MIP advised us on AIGS’s own expertise in delivering Yellowfin embedded business intelligence (BI) dashboards.”

TEARS launched its first beta system with MIP in September 2020, called DAISY (Digital Abuse Information System). DAISY is used by TEARS intervention specialists to input and capture client information onto its CRM system and develop data capture screens, inputs, and workflows to facilitate all aspects of the company’s call centers, and data gathered via other sources.

“Going from a paper-based system to an electronic system was great, but it took us a lot of time to get our existing data onto the new system and sort things out,” explained Mara. “TEARS had to take 7,000 files and capture that onto DAISY, but not all the information was captured correctly during the transition, and some vital files were left out.”



Seamless embedded BI with built-in data privacy

As time progressed, both TEARS and MIP worked out further enhancements to many of the systems involved like standardising data capture and workflow processes, and addressing issues such as gender spelling discrepancies. “MIP added pre-set drop-down options for specific case-types to help the TEARS team more easily see how many of each there were, and allowed for users to capture specific clients on the system if the client gave consent to not remain anonymous, so TEARS could refer back to those people in different cases and use that data in Yellowfin dashboards,” explained Melissa Spencer, System Design and Process Engineer at MIP.

That last point – data privacy of its clients – was a core factor of the DAISY solution, according to Mara. “Both the system and the team only use personal information of clients as an identifier, but then we remove it and only report on aspects such as what the incident was, what time and date it happened, and the outcome.”

The integration of MIP’s DAISY system with Yellowfin dashboards was its own journey, according to Gustav Piater, Sales and Marketing Director at AIGS Insights: “AIGS assessed what TEARS managed on a daily basis and the information they were getting to then build operational type reports, capture and select gender as a drop down option and leverage other data the public might be submitting like geo-locations and addresses – although we want to anonymize and keep the individual private, we needed to know what type, where, when, what all of those elements for effective reporting.”

“It’s amazing how AIGS came on board and broke Yellowfin’s capabilities down,” recalled Mara. “We didn’t know what we wanted to see in dashboards, so AIGS examined the data we were capturing and then provided ideas of what we could do with our reporting. Now, we understand the impact dashboards can have with our reporting efforts, because telling someone we’ve assisted 20 people versus showing the executive a compelling dashboard with complete breakdown of what’s been done – that’s huge.”



Data-driven decision-making and better data GBV capture

Today, TEARS has experienced significant maturity with its DAISY system and Yellowfin dashboards. The company has made substantial improvements to their reporting, including:

  • Better ability to capture and input a broader spectrum of GBV data with DAISY
  • Better ability to report and present said data to funders using Yellowfin dashboards
  • New potential partnerships with several organizations that can contribute to a richer data ecosystem within TEARS’ portal



“At the beginning of our journey, we didn’t actually know what we wanted to see because we had never implemented analytics like this before”, said Mara. “Once we could use the new capture system and dashboards and find what did not work, MIP, AIGS and Yellowfin advised us along the way and we are grateful for their help.”



As the company looks ahead, the next phase will revolve around harnessing the potential of this vastly expanded data set. AIGS and Yellowfin aim to empower TEARS with the right capabilities to make more informed decisions and extend reporting to encompass additional dimensions such as funding and financial status, thereby moving beyond incident data analysis only.

Ultimately, for Mara, TEARS’ main driver in developing a better data capture solution was for the people they served. “Our path with Yellowfin that got us from paper to electronic systems was basically to not let anyone down. We wanted to make sure we get to every one of our clients in time, every time. If we schedule we need to phone a client on Monday, we now get a pop-up to do so, consistently. This really was the driving force for us – to make sure nobody is left behind.”

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