Current Date And Time In Tanzania
Friday, 29 May 2026
02:07:22 EAT
Explore the complete directory of 31 states, provinces, regions and administrative divisions within Tanzania. This comprehensive database provides detailed information about regional territories, local governance structures, geographic subdivisions and administrative boundaries essential for business operations, market analysis and strategic planning across Tanzania.
Benefits for Professionals: Regional market segmentation • Location-based business intelligence • Supply chain optimization • Distribution network planning • Demographic analysis by region • Real estate market research • Franchise expansion planning • Territory management • Sales region allocation • Local taxation research for operations in Tanzania, comparative country administrative structures and regional capital cities
| State / Province Name | Capital City | Population | Area (km²) |
|---|---|---|---|
| Arusha (AR) | Arusha | 1,694,310 | 81,263.46 |
| Dar Es Salaam Region (DS) | Dar Es Salaam | 2,791,063 | 4,144.08 |
| Dodoma (DO) | Dodoma | 2,083,588 | 72,166.66 |
| Geita (GE) | Geita | 1,739,530 | 45,174.88 |
| Iringa (IR) | Iringa | 941,238 | 70,373.62 |
| Kagera (KA) | Bukoba | 2,189,850 | 64,640.72 |
| Katavi (KA) | Mpanda | 564,604 | 94,111.75 |
| Kigoma (KI) | Kigoma | 2,127,930 | 104,136.85 |
| Kilimanjaro (KI) | Moshi | 1,640,087 | 32,909.59 |
| Lindi (LI) | Lindi | 864,652 | 107,480.22 |
| Manyara (MA) | Babati | 1,148,070 | 96,694.69 |
| Mara (MA) | Musoma | 1,743,830 | 37,417.17 |
| Mbeya (MB) | Mbeya | 2,707,410 | 72,932.64 |
| Morogoro (MO) | Morogoro | 2,218,492 | 162,120.00 |
| Mtwara (MT) | Mtwara | 1,270,854 | 38,950.74 |
| Mwanza (MW) | Mwanza | 2,772,509 | 40,457.40 |
| Njombe (NJ) | Njombe | 702,097 | 39,559.95 |
| Pemba North (PN) | Wete | 211,732 | 1,043.81 |
| Pemba South (PS) | Chake Chake | 195,116 | 1,186.19 |
| Pwani (PW) | Kibaha | 1,098,668 | 69,587.12 |
| Rukwa (RU) | Sumbawanga | 1,004,539 | 60,526.62 |
| Ruvuma (RU) | Songea | 1,190,348 | 114,022.69 |
| Shinyanga (SH) | Shinyanga | 1,534,808 | 35,486.62 |
| Simiyu (SI) | Not available | 1,584,157 | 42,279.41 |
| Singida (SI) | Singida | 1,370,637 | 86,024.70 |
| Songwe (SO) | Vwawa | 1,173,667 | 55,525.53 |
| Tabora (TA) | Tabora | 2,291,623 | 122,379.67 |
| Tanga (TA) | Tanga | 2,045,205 | 51,827.41 |
| Zanzibar Central/South (ZC) | Koani | 115,588 | 1,751.63 |
| Zanzibar North (ZN) | Mkokotoni | 187,455 | 861.52 |
| Zanzibar Urban/West (ZU) | Zanzibar | 593,678 | 451.07 |
Tanzania's regional administrative structure comprises 31 distinct states, provinces, regions or territorial divisions, each with unique governance frameworks, demographic characteristics and economic profiles. These administrative boundaries serve as crucial reference points for market segmentation analysis, distribution network planning, regional sales territory allocation and location-based business intelligence. Understanding provincial jurisdictions enables effective supply chain optimization, franchise expansion strategies, real estate investment decisions and regulatory compliance management across different regions.
Regional demographic data, population density metrics and geographic coordinates for each state facilitate targeted marketing campaigns, customer segmentation strategies, service area optimization and logistics route planning. Business professionals utilize state-level intelligence for competitive analysis, market entry timing, pricing strategy adaptation and distribution channel selection. Understanding regional economic variations supports revenue forecasting, resource allocation decisions, partnership development and risk mitigation strategies when expanding operations across Tanzania.
State-level population statistics enable precise market sizing calculations, consumer demand estimation, workforce availability assessment and infrastructure capacity planning. Regional demographic trends inform product portfolio decisions, service offering customization, pricing tier development and channel strategy optimization. Analyzing population concentration patterns supports retail location selection, distribution center positioning, service network design and territory management for companies operating across multiple Tanzania regions.
Clearly defined state boundaries facilitate sales territory allocation, quota setting, performance tracking and commission calculation for regional sales teams. Administrative divisions provide standardized frameworks for market coverage analysis, territory balancing, representative assignment and customer relationship management. Understanding state-level commercial regulations, taxation structures and business environments enables compliance planning, legal entity structuring, tax optimization and operational efficiency across Tanzania's diverse regional landscape.
Regional geographic data supports warehouse location optimization, transportation route planning, delivery zone mapping and last-mile logistics design. State-level analysis enables shipping cost estimation, delivery time calculation, service coverage planning and fulfillment center positioning. Understanding inter-regional connectivity, transportation infrastructure and distance metrics facilitates inventory distribution strategies, cross-docking operations, regional hub development and supply chain network optimization for efficient nationwide operations in Tanzania.
State-level economic indicators, infrastructure development metrics and business environment assessments inform market entry sequencing, investment prioritization, resource deployment and expansion roadmap development. Regional competitive landscape analysis supports positioning strategies, partnership identification, acquisition targeting and organic growth planning. Understanding provincial economic trajectories, regulatory environments and market maturity levels enables risk-adjusted return projections, capital allocation optimization and strategic decision-making for companies pursuing growth opportunities across Tanzania's regional markets.
Disclaimer We can not guarantee that the information on this page is 100% correct.