For years, policy-makers in Abuja have quietly worried that Nigeria’s industrial plans were being built on shaky foundations. Ask three agencies for the country’s raw-materials import figures and you were likely to get three different answers. Customs, the National Bureau of Statistics (NBS) and industry associations all kept their own datasets, with mismatched formats, missing fields and unexplained gaps.
“That’s how we’ve been flying—half-blind,” one senior official in the Federal Ministry of Industry, Trade and Investment admitted. “You cannot design serious backward-integration policy if you don’t trust the numbers.”
Now, a low-profile technical project inside the Raw Materials Research and Development Council (RMRDC) is quietly changing that story.
According to an internal audit report seen by BusinessDay, a new Secure Data Ingestion Framework (SDIF) has cut error and anomaly rates in the National Raw Materials Import Index (RMMXI) from 22.4 percent to just 0.48 percent in less than two years.
The framework, designed by RMRDC data-security specialist Daniel Ihenacho, sits between RMRDC and its data providers—Nigeria Customs Service, NBS and the Manufacturers Association of Nigeria (MAN)—and acts, in his words, “like a very stubborn gatekeeper.” Any file that doesn’t meet its strict standards simply doesn’t get in.
“What this gives us is a foundation we can trust,” said a senior official in RMRDC’s Planning, Statistics and Policy Department. “Without this, any industrial policy built on the old numbers was standing on quicksand.”
External analysts who have reviewed the audit call SDIF “one of the most important, if least glamorous, innovations in Nigeria’s economic-data infrastructure over the past decade.”
The data problem nobody wanted to own
The RMMXI was created to track the value and composition of raw-materials imports feeding Nigerian factories, from petrochemicals and packaging materials to pharmaceutical inputs and industrial starches. On paper, it should be an industrial planner’s dream: a single index that shows which sectors are dangerously import-dependent and where local production could realistically substitute.
In practice, it was a messy compromise.
“Customs has detailed shipment-level data, NBS has its own trade tables, and MAN collects what its members report,” explained an economist familiar with the system. “None of these were designed from the outset to feed one harmonised index.”
Each institution used different product groupings, inconsistent HS codes, and bespoke Excel templates. Some files arrived without currency codes, others with commas and spaces embedded in numeric fields, or with missing values for entire months. Reconciling them was a monthly ritual of frustration.
The result: up to a fifth of incoming records were either flagged as suspicious or dropped entirely, distorting the index and eroding confidence in its outputs.
“The easy option was to shrug and say, ‘Well, that’s just how Nigerian data is,’” the RMRDC official said. “To his credit, Mr. Ihenacho refused to accept that.”
Building a “gatekeeper” for raw-materials data
Recruited to RMRDC as an IT and data-security analyst, Daniel Ihenacho was initially brought in to harden the Council’s systems and support the digitalization of the RMMXI. Very quickly, he realized the core issue was not the database itself, but the chaotic way data arrived from partner institutions.
“What we had was not a database problem,” Ihenacho told BusinessDay in an interview. “It was a data-ingestion problem. If you pour dirty water into a brand-new tank, it will still be dirty.”
His answer was the Secure Data Ingestion Framework—a set of technical rules, validation checks and security controls that sit between external data providers and the RMMXI database.
At its heart, SDIF does three things:
1. Standardises the language: All providers must now submit data in a common format, with a shared data dictionary for HS codes, units of measure, sectors and time periods. Files that don’t conform are automatically rejected.
2. Runs multi-stage validation: Before any record enters the index, SDIF checks:
o whether quantities and values fall within plausible ranges,
o whether totals reconcile across agencies for the same period,
o and whether new data is internally consistent with historical trends.
3. Secures the pipeline: Data is transmitted via encrypted channels, stored in controlled environments and accompanied by audit logs that track who submitted what, when, and from which system.
“If a file arrives with maize imports in metric tonnes but the unit code says ‘kg’, or if we see negative values, the system doesn’t delicately whisper— it shouts ‘No’,” Ihenacho joked. “We’d rather bounce a bad file than pollute the index.”
From 22.4% noise to 0.48% anomalies
The impact, according to RMRDC’s Internal Audit Division, has been dramatic.
A baseline audit of 2017–2018 data—the years immediately before SDIF—found that roughly 22.4 percent of incoming records triggered anomaly flags or required manual correction. In some months, entire sectoral series had to be reconstructed from scratch.
After the SDIF’s full deployment in early 2019, repeat audits of 2019–2020 ingestion cycles recorded anomaly rates of 0.48 percent, mostly for minor issues such as late submissions and formatting errors.
“From an auditor’s standpoint, this is night and day,” said a member of the internal audit team, who spoke on condition of anonymity because he is not authorized to speak publicly. “Before, we spent our time firefighting basic errors. Now we can focus on deeper questions: what the numbers actually mean for policy.”
The new regime has not been painless for RMRDC’s partners. Officials at Customs, NBS and MAN had to overhaul their own export routines, adopt the SDIF data dictionary and train staff to resolve failed submissions.
But they say the trade-off has been worth it.
“We had some frustrating weeks at the start,” admitted Dr. Simon Harry, Statistician-General of the Federation. “Every audit failure felt like a personal insult. Then we realised the framework was forcing us to clean up our own house. It’s annoying—but it’s the right kind of annoying.”“One of the least glamorous innovations – and one of the most important”
Outside RMRDC, the SDIF has begun to attract attention among economists and data specialists.
In a recent working paper circulating among researchers, two renowned academics, Professor Siyanbola Tomori and Professor Dayo Phillip from the University of Lagos and Ahmadu Bello University respectively described the framework as a “structural break” in the quality of Nigerian import data, arguing that models built on the post-2019 RMMXI series are more stable and predictive than those based on earlier numbers.
“Everybody loves to talk about big, shiny projects—new rail lines, new industrial parks,” said one of the authors, Professor Dayo Phillip, when reached by phone. “But if your underlying data is rotten, all of that is just wishful thinking. What Mr. Ihenacho and the RMRDC team have done with SDIF is one of the least glamorous, and yet most important, innovations we’ve seen in years.”Policy analysts agree.
Alhaji Abubakar Abdulkadir, an industrial-policy consultant described SDIF as “a classic case of boring-but-transformational infrastructure.”
“If you halve your error rate, that’s nice,” he said. “If you drive it down from 22 percent to below one percent, you’ve changed the game. You can now credibly say whether, for instance, Nigeria is overexposed in pharmaceutical inputs or food additives, and what kind of incentives would meaningfully move the needle.”
From quiet technical fix to policy engine
The real test of any data reform, however, is whether anyone outside the statistics community uses it.
On that front, there are signs that the SDIF is beginning to shape concrete decisions.
Officials in the Federal Ministry of Industry, Trade and Investment confirmed that the Ministry’s draft Raw Materials Import Substitution Strategy (2022–2026) relies almost entirely on post-2019, SDIF-validated RMMXI data to identify priority sectors for local production and to estimate potential foreign exchange savings.
“We had to draw a line in the sand,” one of the drafters said. “Anything before SDIF we treat with caution. For serious cost–benefit analysis, we work with the cleaned series.”
The Manufacturers Association of Nigeria has also started using SDIF-processed figures in its own advocacy.
“When we go to government with a position paper now, we can say, ‘These numbers are from the SDIF series; they’ve been cross-checked against Customs and NBS’,” a MAN economist told BusinessDay. “It changes the tone of the conversation.”
Can the model travel?
RMRDC officials say they are already fielding questions from other agencies—and from outside Nigeria.
The Chartered Institute of Taxation of Nigeria (CITN) is exploring how SDIF-style ingestion checks might be applied to other composite indicators, such as tax-expenditure estimates and sectoral tax-gap analysis.
Regionally, ECOWAS and development partners have invited RMRDC to present the framework at workshops on industrial statistics and data governance.
“Everybody in the region is grappling with the same issue: multiple data sources that don’t talk to each other, and everyone blaming everyone else for the discrepancies,” said a West African data consultant who has reviewed the SDIF documentation. “Nigeria’s approach may not be perfect, but it’s a serious attempt to attack the problem at the right point—the ingestion layer.”
“We just wanted the numbers to stop lying”
For his part, Daniel Ihenacho seems uncomfortable with the attention.
“I’m a back-end person,” he laughed. “If my work is on the front page, something has probably gone wrong.”
Asked what motivated him to push through a framework that, at least initially, annoyed almost everyone who had to comply with it, he shrugs.
“At the end of the day, we just wanted the numbers to stop lying,” he said. “If government is going to make hard choices about tariffs, FX allocation or backward integration, the least we can do is give them a dataset that isn’t shouting ‘error’ in the background.”
The dataset is no longer shouting. Whether policy-makers will now listen more carefully to what it says is another question—one that SDIF, by design, leaves to humans.
But for the first time in a long time, Nigeria’s raw-materials import numbers may finally be solid ground rather than quicksand.
