Data governance gaps threaten economic growth potential

DAR ES SALAAM: DATA has become one of the most valuable assets in the modern economy. Governments depend on it to formulate policies, allocate resources, collect taxes, deliver services and anticipate risks, while businesses use it to understand customers, manage risks, innovate and remain competitive.

As Tanzania accelerates digital transformation, however, a significant gap is emerging: The country is generating more data than ever, but its capacity to govern, integrate, protect and strategically use that data has not kept pace.

The challenge is no longer simply collecting information. It is ensuring that data is accurate, accessible to authorised users, protected from misuse, compatible across institutions and ultimately converted into decisions that improve economic and social outcomes.

Tanzania has made progress through digital government services, statistical systems, financial technology and personal data protection. Yet several governance gaps could leave the country data-rich but economically underutilised.

The first is treating data governance as an IT issue

Data governance extends beyond databases, software, servers and cybersecurity. It involves accountability, standards, ownership, ethics, quality, access and decisionmaking.

A ministry may have an advanced information system but still make poor policy decisions if its data is incomplete, outdated or incompatible with information held by another institution.

Major institutions therefore need clear accountability for the data they collect, including its purpose, access rights, retention and quality controls.

The second challenge is fragmented government data

Agencies often collect information independently according to their mandates, creating data silos.

Information on businesses, taxpayers, workers, land, agriculture, financial transactions and social protection beneficiaries may exist in separate systems that cannot communicate effectively.

Tanzania does not necessarily need one giant database. It needs strong interoperability frameworks, common data formats and secure systems through which authorised institutions can exchange information.

The principle should be simple: Collect once where possible, verify continuously and share responsibly.

The third gap is data quality

Large volumes of poorquality data can be more damaging than smaller, reliable datasets. Duplicate records, inconsistent definitions, missing information, outdated registers and differing methodologies can undermine policy decisions.

National and institutional data-quality frameworks should therefore address accuracy, completeness, timeliness, consistency and validity. Data should be treated as an asset requiring regular audits, controls and accountability.

The fourth challenge is turning data into intelligence

Producing statistics is different from generating insights. A dashboard showing unemployment, inflation or agricultural output provides information, but policymakers also need to understand what drives those trends, where they are heading and which interventions could change them.

Tanzania should strengthen capacity in data analytics, predictive modelling, geospatial analysis, artificial intelligence and evidence-based decisionmaking across ministries and local authorities.

The fifth gap concerns public-private data sharing

Banks, telecom companies, fintech firms, insurers and government agencies generate information with significant economic value.

Yet sharing it raises legitimate concerns about privacy, cybersecurity, competition and commercial confidentiality.

A regulated data-sharing framework could allow responsible use of alternative data, for example, to improve access to credit for small businesses and entrepreneurs without conventional collateral, while protecting personal and commercial information.

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The sixth challenge is privacy and data protection

As digital services expand, protecting personal information is essential to maintaining public trust. Data breaches are not merely technical failures; they can undermine confidence in digital government and financial services.

Institutions should therefore integrate data protection into risk management through privacy assessments, access controls, breach-response plans and staff training.

The seventh gap is the data divide

Digital transformation can deepen inequality when those generating data do not have equal access to the benefits it creates.

Small businesses, rural communities, women, young people and underserved regions may generate valuable economic information while lacking analytical tools, digital services or financing linked to that data.

Data governance should therefore be connected to digital inclusion, ensuring data infrastructure and services extend beyond major cities and large corporations.

The eighth is insufficient data leadership

Effective governance requires senior officials responsible for data oversight in major institutions, supported by multidisciplinary teams of ICT specialists, statisticians, economists, legal advisers, cybersecurity experts and sector professionals.

Data governance should also form part of institutional performance frameworks, with managers assessed on how effectively data improves institutional performance and public outcomes.

Addressing these gaps requires seven priorities: establishing a governmentwide data governance framework; harmonising national data standards; improving secure interoperability; investing in data skills; strengthening dataquality assurance; creating responsible public-private data-sharing mechanisms and integrating data governance into national development planning.

These measures are particularly relevant to Dira 2050, where industrialisation, productivity, financial inclusion and improved public services will increasingly depend on reliable information.

Tanzania’s challenge is therefore not a shortage of data but an abundance of scattered, underused and poorly governed information. The strategic opportunity is to recognise data as a national asset alongside infrastructure, finance, human capital and natural resources.

A data-smart Tanzania would be better positioned to anticipate problems rather than simply react to them, while businesses could use reliable information to innovate, researchers could access appropriate datasets and citizens could exercise greater control over their personal information.

Ultimately, effective data governance is about building the trust, institutions and capabilities required to turn information into economic value while protecting the rights of those who generate it.

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