AGAYA Consulting: Data Confidence for Nonprofit Leaders

Hi, I'm Indu.

For over twenty years, I worked in infrastructure finance, recommending investments of $50 million to $350 million and then sitting in the room to defend those recommendations to people whose job was to find the holes in my reasoning.

When something went wrong, I was the one explaining what happened, why, and what was being done about it. That is what fiduciary accountability looks like, and it shapes how I approach this work today.

I moved into nonprofit work to be more connected with my community. What I found was the same pressure showing up, just with smaller numbers and much higher personal credibility at stake for the person carrying it.

What I kept seeing was this: the issue wasn’t a lack of data. It was that the reporting had been built to satisfy funders and auditors, not to support the person responsible for the next decision. The Executive Director was rarely the one the reporting infrastructure was designed for.

In my nonprofit project work, I often saw the same pattern. The reporting would look solid at delivery. The gaps showed up later, when decisions had to be made and questions started coming in.

As I wrapped up projects, I could see the risks and questions likely to come up down the line. But the scope of the work didn’t extend to that.

That’s what led me to build a fractional model, staying alongside organizations past the point where most project engagements end. This work is designed for organizations typically between $3–10M, large enough to have real complexity across finance, fundraising, and programs, but not yet large enough to have dedicated data support.

The focus is straightforward: build reporting that supports the decisions Executive Directors are actually accountable for.

Some organizations come in with a specific reporting or data problem. Others are trying to make decisions without fully trusting what sits underneath them.

The starting point isn’t the delivery model. It’s the decision you need to make and how well your current reporting supports it.

From there, the work can begin in different ways.

In some cases, it’s a focused piece of work to fix something specific. In others, it involves stepping back to understand where the reporting breaks down and what needs to change underneath.

That may look like a short engagement to resolve a defined issue, or ongoing support to build a system that holds up over time.

For organizations where leaders are regularly having to explain or reconcile the numbers behind their decisions.

This involves working alongside leadership to identify where decisions are being slowed down or weakened by fragmented reporting and inconsistent definitions.

The work typically starts with a plan built around the decisions you are currently responsible for and what sits underneath them. From there, the focus turns to implementation — inside the numbers, in board preparation, and in the conversations that happen before high-stakes decisions are made.

The goal is not just better reports. It is a system that holds up when questions get asked. That’s the standard the work is built to meet.

I am not reviewing reports from a distance. The work happens directly in the data, where those decisions are actually being shaped.

The aim is not to create ongoing dependence. It is to leave behind clear definitions, working processes, and reporting structures the team can manage and stand behind independently.

Best fit for: organizations that need consistent decision support but do not have dedicated internal capacity.

For organizations with a specific reporting or analytics problem to solve.

This may involve redesigning a dashboard, clarifying KPIs, fixing inconsistencies across reports, or building a performance tool that the team can actually use in practice.

These engagements are scoped and deliverable-focused, but still grounded in the underlying data (not just surface-level fixes or presentation changes.)

The emphasis is on making reporting usable for decisions, not just technically correct.

In some cases, this work stands on its own. In others, it creates the conditions for more consistent decision support over time.

Best fit for: organizations with a clearly defined reporting, dashboard, or analytics need.