The First Deputy Governor of the Bank of Ghana (BoG), Dr Zakari Mumuni, has called for stronger data quality and closer collaboration between researchers and policymakers to improve decision-making and policy outcomes.
He said the growing availability of data was no longer the major challenge confronting policymakers, but rather the ability to transform the abundance of information into timely, reliable and actionable intelligence.
Dr Mumuni made the remarks on Wednesday, August 26, 2026, in Tamale when he delivered the keynote address at the 4th Annual Statistics and Data Science Conference of the Ghana Statistical Association (GSA).
The conference was held on the theme: “Innovations in Statistics and Data Science: Research, Practice and Policy Impact.”
According to Dr Mumuni, while statistics and data science were essential tools for evidence-based policymaking, data alone could not determine policy decisions.
“The greatest challenge facing policymakers today is no longer a shortage of data. It is turning an abundance of data into timely, reliable and actionable intelligence,” he said.
He added: “A forecast does not make policy. An algorithm does not make policy. People make policy.”
Dr Mumuni said the BoG’s experience demonstrated the importance of quality data to effective economic management, stressing that statistics were central to the work of a central bank.
He identified data collection, quality and continued relevance as three critical pillars of reliable data.
He noted that BoG researchers regularly collected information from markets across the country, including Tamale, while conducting price tracking and business and consumer confidence surveys.
“Long before a survey appears in a published report, our Research Department staff are in markets across the country—including here in Tamale—tracking prices and conducting business and consumer confidence surveys,” he said.
Dr Mumuni also warned that the growing use of artificial intelligence could not compensate for weaknesses in underlying data.
“AI can process enormous volumes of data, but it cannot turn bad data into good data,” he said, adding that unclear definitions, inconsistent classifications and weak validation could result in misleading outputs regardless of the sophistication of the technology involved.
He therefore urged statisticians and data professionals to continue paying attention to sampling, measurement, classification, validation, metadata and revisions.
He also stressed the need for data to remain relevant as economies and consumption patterns evolve, citing the rebasing of Gross Domestic Product (GDP) and the Consumer Price Index (CPI) as important exercises.
According to him, emerging data sources, including payment systems, tax records and telecommunications data, offered significant opportunities but also required strong confidentiality and governance safeguards.
On the use of technology in policymaking, Dr Mumuni said the BoG had deployed artificial intelligence and Big Data technologies in its electronic inflation nowcasting methodology, known as e-Inflation.
He said the Bank also used machine-learning models to complement conventional econometric models in GDP forecasting and text-mining analytics.
“These technologies can help policymakers identify risks earlier and improve the speed with which intelligence is generated,” he said.
He, however, cautioned against allowing technology to replace human judgment.
“Technology can strengthen our intelligence, but it does not remove the need for human judgment,” Dr Mumuni said.
He said the Bank’s forward-looking inflation-targeting framework required policymakers to assess where the economy currently stood, where it was heading, factors that could alter its trajectory and the appropriate policy response.
Dr Mumuni said answering these questions required analysis of prices, output, credit, exchange rates, fiscal conditions and financial markets, as well as the interaction among those indicators.
He further called for stronger collaboration among statisticians, economists, data scientists, technologists and policymakers, arguing that no single discipline could independently address the increasingly complex demands of modern policymaking.
“The statistician asks whether a measure is valid. The economist asks what it means for behaviour. The data scientist asks what pattern it reveals. The technologist asks how to operationalise it. The policymaker asks what decision should follow,” he said.
He urged universities and public institutions to deepen collaboration to ensure that academic research responds more directly to practical policy challenges.
“Research should not only be about policy. It should increasingly be conducted with policy,” he said.
Dr Mumuni outlined three priorities for the statistics and data science community: investing in data quality, embracing high-frequency and alternative data while maintaining statistical standards, and strengthening the link between research and the practical questions confronting institutions.
He cautioned that new forms of data should complement, rather than replace, properly weighted and nationally representative measures.
He said researchers should understand the challenges facing policymakers, while policymakers should remain open to research that challenges assumptions and interrogates available evidence.
“Research achieves its greatest value when it moves beyond publication—into practice, into policy, and into impact,” he said.
Dr Mumuni concluded that the objective of innovation in statistics and data science should ultimately be to improve the quality of decisions and their impact on society.
“Statistics helps us measure reality. Data science helps us interrogate it. When these come together, data becomes intelligence,” he said.
He described intelligence combined with sound judgment as a strategic national asset and called for a future in which better data guides better policymaking, research translates into practice and innovation produces meaningful impact.
