How independent advisory helped an organisation understand why a multi-million rand data platform failed — and restored leadership confidence before any rebuild was considered.
The organisation was not anti-data. It was exhausted by it.
Over an 18-month period, the company had invested between R2–5 million in what was positioned internally as a “modern data capability.” The initiative included a centralised data warehouse, reporting tools, and process automation intended to improve executive visibility and operational efficiency.
On paper, the project delivered outputs:
In practice, leadership confidence declined.
By the time the initiative was formally paused, the executive team shared three views:
The board’s instruction was explicit:
“Before another cent is spent, someone independent must explain what actually went wrong.”
Initial internal post-mortems focused on familiar explanations:
These explanations were unsatisfactory to leadership because they avoided accountability. The concern was not that dashboards were unused, but that decisions still relied on gut feel, spreadsheets, and side conversations.
Executives were asking harder questions:
The problem was not technical failure. It was decision failure.
Leadership specifically did not want:
They wanted an external party with no implementation agenda to answer one question:
“Was this the wrong solution, or was the problem upstream of the solution?”
This framing mattered. It shifted the review from how the system was built to why it was built in the first place.
The review deliberately avoided tooling, configuration, and architecture.
Instead, it examined four areas executives actually care about.
The review found that no shared agreement existed on:
As a result:
The platform delivered data. It did not deliver decision authority.
Data ownership was assumed, not defined.
Key findings included:
When numbers were challenged, escalation stalled because:
This created risk aversion instead of confidence.
Automation had been introduced to reduce manual effort, but:
The result:
Automation amplified ambiguity that already existed.
Data governance was described as “phase two.”
In reality:
By the time governance issues surfaced, the organisation had already lost confidence in the initiative.
The most important outcome of the review was not a recommendation to replace systems.
Leadership concluded:
In short:
The organisation automated disagreement.
Before considering any new investment, leadership made several non-technical decisions:
Only after these decisions did the conversation about data capabilities resume — with materially different expectations.
The review carried weight because it:
This allowed executives to discuss failure without blame and reset expectations without reputational damage.
The value was not in diagnosis alone, but in restoring decision confidence.
Organisations that have already been burned do not need another solution.
They need:
Only then does it make sense to try again.
In this case, no systems were rebuilt during the review.
What was rebuilt was trust.
This demonstrates the value of independent advisory when data initiatives have already failed. If you’re considering how to approach data strategy or automation decisions, these resources may be helpful:
If your organisation has experienced a similar situation, or you’re evaluating data or automation investments and want to avoid these pitfalls, get in touch to discuss how independent advisory can help.