At PayPal, I built the master file for Financial Planning and Analysis. The one that reported how the entire business had performed each month and forecasted the next and full year.
The single source of truth that leadership relied on. More than 30 analysts and finance managers would feed their numbers into SAP, the enterprise resource planning system. Then I pulled it all together.
Month after month, the process was the same. On the fourth day of the month, the system would lock at 3pm PST. That was my cue. I’d go in and start updating the report for the entire organization. I had one for engineering, one for product, one for marketing, one for sales, one for HR, one for finance, and one for the whole company. It took hours. I was consolidating an entire organization’s financials, reconciling numbers that came in from every corner of the business, making sure everything tied. I worked late into the evening, long after everyone else had gone home, so that the report would be ready for the first leadership meeting the next morning at 7am.
I didn’t think much of it at the time. It was just the job. That file took months to build, and we used it for over a year before we finally automated it. But looking back, that’s a striking image: one person, alone, manually holding together the financial truth of a $40B company.
I tell you this because over the last few months, I’ve sat across from leaders at insurance companies, fintechs, and banks across Africa. People who are sharp, experienced, and deeply committed to their organizations. And almost every single one of them has told me some version of the same thing whether it is for finance, for reconciliation, or for day-to-day operations. The words vary, but the meaning doesn’t. They know something is off. They can feel it in the operations, in the delayed payments, in the questions from partners. But by the time the numbers catch up, the window to act has already closed.
That gap between what you know and what you can prove is what I keep thinking about. It’s the space where good leaders end up trusting instinct over data, not because they want to, but because the data arrives too late.
The Report That Takes Weeks
Let me show you what that gap looks like in practice.
A leader needs a report. Revenue vs. targets. Operating expenses. Cash flow. Budget variance. The data exists. It’s sitting somewhere in the organization. But getting it into a single view takes days, sometimes weeks or months.
Someone has to pull from the core banking system. Someone else exports from the policy management platform. Another person downloads the Excel that the regional office emailed on Friday. Then it all lands in a master spreadsheet that one analyst - usually the most overworked person on the team - spends a weekend stitching together.
By the time leadership sees the numbers, they’re already 30 days old. Decisions that should have been made three weeks ago are just now getting the data they needed.
Every team I’ve talked to has their version of my PayPal story. Their master file. The one that lives on someone’s desktop, or in a shared drive folder with a name like “FINAL_v3_USE THIS ONE.” The one that gets emailed around before every leadership meeting.
I’ve seen finance teams spend entire days reconciling two versions of the same spreadsheet that somehow got out of sync. I’ve seen month-end close processes that stretch for weeks because no one can agree on which numbers are right. I’ve seen analysts manually cross-checking data between systems that should never have been disconnected in the first place.
The spreadsheet isn’t the problem. The absence of infrastructure that should replace it is.
When It Takes Two Years to Reconcile
Here’s a story I heard recently that stopped me.
An insurance company needed to reconcile policies that had been sold and make payments to their business partners. Simple enough on paper. But in practice, it took them over two years. Two years to match policies to payments, to figure out what was owed and to whom.
Think about what that means. For two years, business partners were waiting on money they were owed. For two years, the insurance company was operating without a clear view of their own liabilities. For two years, someone or some team was buried in spreadsheets, trying to solve a problem that should have been solved by infrastructure.
That’s not an isolated case. I’m hearing versions of this everywhere.
Why This Is a Specifically African Problem
I want to be precise here, because I’m not making a general argument about finance teams everywhere.
The infrastructure gap I’m describing is deeper and more acute in African markets. Not because of capability, the finance professionals I meet are sharp and sophisticated. But because the tools that exist were built for a different context.
Most enterprise analytics and data platforms were designed for organizations with dedicated data engineering teams, stable and standardized data environments, and budgets that can absorb six-figure implementation costs. To put that in perspective: at PayPal, when we decided to solve some of our own data problems, I worked with a team of five engineers to implement Looker and build PayPal’s first Finance Data Mart. It took two years. That’s what it costs to do this properly at scale and that’s at one of the most well-resourced technology companies in the world.
That’s not the reality for the vast majority of companies operating across Africa and emerging markets. The data environments here are messier. Systems are more fragmented. Integration is harder. And the resources to bridge that gap, the data engineers, the developers, the infrastructure teams, simply aren’t available at the same scale.
So teams adapt. They build workarounds. They make the spreadsheet work. And they absorb, quietly, an enormous operational burden that limits what they can actually contribute to the business.
What Should Be Possible
Here’s what I believe every finance team at an African financial institution should have and doesn’t.
A single, real-time view of how the business is performing. Not a report that takes weeks to build. Not a dashboard that only gets updated when someone touches it. Not a spreadsheet updated on Sunday night. A live view that updates as the data changes, that anyone with the right access can open and trust.
A team that spends its time analyzing, not collecting. Where analysts are modeling scenarios and advising leadership not cleaning data and chasing down numbers.
And a leadership team that can see problems before they become crises. That doesn’t take two years to reconcile policies. That doesn’t learn about a margin issue three months after it started.
This is not a futuristic ask. The capability exists. What’s been missing is infrastructure built for the actual reality of African companies. The systems, the data environments, the constraints, and the opportunities that are specific to this market.
I spent years as the person staying late to stitch the numbers together. I know what it costs in time, in clarity, and in decisions delayed. That’s why we’re building at Baza.
If This Sounds Familiar
Baza connects your fragmented data sources, cleans them, and gives your team instant access to dashboards, deep-dive intelligence reports, and plain-language querying - no data engineers required. We’re currently onboarding a small group of companies into our pilot program. If any of this feels familiar, apply for the pilot here or reach out directly at info@usebaza.com.