Basic Spreadsheet Formula Skills by Country – 2026
How comfortable are you using basic arithmetic formulas in spreadsheets such as Excel or Google Sheets? Spreadsheet formula skills represent one of the most essential digital competencies in modern workplaces, enabling people to perform calculations, analyze data, and automate routine tasks. This analysis examines spreadsheet formula skills by country across 99 nations, revealing how populations have adopted this fundamental digital skill and the significant disparities in digital literacy that persist globally. Understanding spreadsheet formula proficiency provides insight into broader patterns of digital skill adoption and digital inequality between countries. This analysis is based on the latest available UNESCO ICT skills data, with projections extending to 2026.
Spreadsheet formula skills measure the percentage of people who use basic arithmetic formulas (addition, subtraction, multiplication, division) in spreadsheet applications such as Excel, Google Sheets, or LibreOffice Calc. This includes using simple functions like SUM, AVERAGE, and COUNT to perform calculations and data analysis. A proficiency rate of 60% means 60 out of 100 people can effectively use basic spreadsheet formulas, while 40 cannot or do not use these tools. This metric captures fundamental digital skills that underpin data literacy and represents a key indicator of digital competency across populations. Spreadsheet formulas enable efficient data management and analysis across digital environments. Users can perform calculations within documents, analyze datasets, create financial models, and automate routine computational tasks. These fundamental digital skills are foundational for digital literacy in modern workplaces, enabling people to work with numerical data effectively. Inability to use spreadsheet formulas limits productivity, restricts access to data-related work opportunities, and creates barriers to participation in digital economies that increasingly depend on data analysis capabilities. Several countries show exceptionally high spreadsheet formula proficiency rates, indicating populations with strong data literacy and digital competency. United Arab Emirates leads with 87.5% (2023), followed by Saudi Arabia (81.6%), Brunei (73.2%), and Oman (67.3%). These nations combine excellent digital infrastructure, high device penetration, and populations comfortable with fundamental spreadsheet skills. The high spreadsheet formula proficiency in these countries reflects broader digital skill adoption and investment in digital literacy programs that emphasize data competency. This global comparison of spreadsheet formula skills by country reveals significant disparities in data literacy adoption. Developed nations in Northern Europe and East Asia show particularly high adoption rates of spreadsheet formula skills. Iceland (66.5%), Norway (56.0%), Netherlands (53.7%), and South Korea (57.4%) demonstrate strong spreadsheet proficiency. These countries have invested in digital infrastructure and digital literacy education that ensure populations can perform basic data analysis effectively. The global digital skills gap is evident when comparing these high-performing nations with countries where spreadsheet formula usage remains limited. Many countries show growing spreadsheet formula proficiency, driven by increasing device access and digital literacy initiatives. Countries in Latin America, Southeast Asia, and Eastern Europe demonstrate strong growth trajectories in data literacy adoption as digital infrastructure expands and younger populations with native digital skills become larger shares of the population. Brazil (14.2%), Colombia (23.9%), and Mexico (25.2%) show emerging adoption of spreadsheet formula skills. These emerging markets represent the global digital skill adoption trend toward more universal data literacy. The spreadsheet formula usage across countries shows clear patterns of digital inequality that require targeted intervention. Developing nations increasingly recognize spreadsheet formula skills and data literacy as essential for economic participation and workplace competitiveness. As computer and device access expands, populations gain opportunities to develop fundamental data analysis capabilities. However, significant gaps persist between countries with mature digital ecosystems and those with limited digital infrastructure. The digital inequality between countries remains a critical challenge for global digital skill adoption. Many countries show low spreadsheet formula usage rates, reflecting multiple barriers to data literacy development and digital competency. Limited device access prevents populations from practicing fundamental spreadsheet skills. Low digital literacy creates barriers even when devices are available. Lack of digital education and training means populations never develop basic data analysis capabilities. Language barriers limit access to spreadsheet software and training materials. Older populations show lower proficiency than younger demographics, reflecting generational differences in digital exposure and data literacy adoption. Economic factors significantly influence spreadsheet formula proficiency and broader digital literacy skills. Populations in low-income countries often lack access to computers and software needed to develop data analysis capabilities. Educational systems in developing nations may not prioritize spreadsheet skills training. Limited availability of training materials in local languages restricts learning opportunities for non-English speakers. These factors contribute to the global digital skill gaps observed across countries. Spreadsheet formula proficiency creates fundamental digital inequality. People who can use spreadsheet formulas can analyze data efficiently, access data-related employment opportunities, and participate in digital economies. Those without these data literacy skills face barriers to analytical work, cannot access opportunities that assume basic spreadsheet competency, and become increasingly isolated from digital economic participation. The digital inequality between countries reflects broader patterns of digital skill adoption and access to digital literacy education. Within countries, spreadsheet formula proficiency shows significant urban-rural divides. Urban areas with better device access and digital infrastructure show higher proficiency in data analysis skills. Younger, more educated, and wealthier populations demonstrate higher proficiency than older, less educated, and poorer populations. Gender differences exist in some countries, with women sometimes showing lower proficiency in technical digital skills in societies with strong gender inequalities in technology access. High spreadsheet formula proficiency enables efficient data analysis and workplace productivity. Workers who can effectively use spreadsheet formulas complete analytical tasks faster, reduce errors in data management, and can perform financial analysis and reporting seamlessly. Organizations benefit from workforces with strong data literacy that enable them to adopt more advanced analytical tools and processes. Spreadsheet formula proficiency represents a critical foundation for broader digital literacy skills required in modern workplaces. Low spreadsheet formula proficiency creates productivity barriers and limits data-related work opportunities. Workers without these data analysis skills struggle with fundamental analytical tasks, cannot efficiently manage numerical data, and face barriers to advancement in data-dependent roles. Organizations in countries with low spreadsheet proficiency face challenges adopting data-driven decision making and competing in digital economies. The global digital skill gaps directly impact economic competitiveness and digital skill adoption rates across nations. The 2026 projections show continued growth in spreadsheet formula proficiency across most countries. High-performing nations like UAE, Saudi Arabia, and Brunei are projected to maintain proficiency rates at or near their current levels, representing populations where data literacy is nearly universal. Mid-tier countries show growth potential as digital infrastructure improves and digital literacy programs expand. Low-proficiency countries will likely see accelerating growth in spreadsheet formula usage as device access expands and younger generations with native digital skills become larger population shares. The global digital skill adoption trend points toward more universal data literacy. Emerging technologies including artificial intelligence-assisted data analysis, simplified spreadsheet interfaces, and cloud-based collaboration tools will likely make spreadsheet operations more intuitive and accessible. However, significant gaps will persist between developed and developing nations, and between connected and disconnected populations within countries. Spreadsheet formula proficiency will remain a critical determinant of digital economic participation and digital inequality between countries. This analysis uses UNESCO Institute for Statistics (UIS) data from ICT skills surveys across 99 countries (2011-2024). The data measures self-reported behavior among individuals aged 15-74 who use basic arithmetic formulas in spreadsheet applications including addition, subtraction, multiplication, and division. This UNESCO digital skills data provides comprehensive coverage of data literacy adoption globally. Spreadsheet formula proficiency rate represents: (Number of people who use basic spreadsheet formulas ÷ Total surveyed population aged 15-74) × 100. For example, 65% means 65 out of 100 people use basic spreadsheet formulas for calculations and data analysis. This metric captures fundamental data literacy skills that indicate broader digital competency adoption. Our dataset includes 81 countries (82%) with current data from 2020-2024, while 18 countries (18%) have older data from 2011-2019. Of the 99 countries in the dataset, 82 had multiple historical data points suitable for linear regression analysis, while 17 countries had single data points. For 2026 projections, we applied linear regression analysis using all available historical data points for each country. Countries with single data points received projections based on growth patterns adjusted for economic development and digital infrastructure. This approach provides insight into global data literacy adoption rates and digital inequality between countries. Projections include growth dampening for high-performing countries (>70% current rate) to reflect saturation effects in data literacy adoption. Countries with older data (>5 years) received additional dampening (50% growth reduction) to account for data uncertainty. All estimates are capped at each country's historical maximum observed value to prevent unrealistic projections. For example, if a country's highest recorded spreadsheet formula proficiency was 73.2%, the 2026 projection cannot exceed 73.2%. This approach ensures projections remain grounded in observed data literacy adoption patterns while allowing for modest growth in countries with lower current rates. Survey methodologies follow UNESCO's standardized ICT skills measurement framework, though self-reported proficiency may not capture actual skill depth or application in real-world data analysis. The UNESCO digital skills data provides valuable insight into global patterns of data literacy and digital inequality between countries.Understanding Spreadsheet Formula Skills
Basic Spreadsheet Formula Skills by Country – 2026
1
87.5%
2
81.6%
3
73.2%
4
67.3%
5
66.5%
6
57.4%
7
56%
8
55%
9
54.4%
10
53.7%
11
52.9%
12
51%
13
48.9%
14
48.7%
15
47%
16
46.7%
17
46.5%
18
46.1%
19
45.8%
20
45.5%
21
45.3%
22
44.5%
23
42.8%
24
42.5%
25
41.8%
26
41.5%
27
41.3%
28
40.6%
29
40.5%
30
38.9%
31
38.3%
32
38.3%
33
38%
34
38%
35
37.5%
36
37.4%
37
36%
38
35.5%
39
34.7%
40
34.6%
41
34.6%
42
34.4%
43
33.9%
44
32.9%
45
32.1%
46
31.2%
47
30.6%
48
27.9%
49
27.1%
50
25.5%
51
25.2%
52
25.2%
53
24.7%
54
23.9%
55
23.6%
56
23.2%
57
21.5%
58
21.4%
59
21.2%
60
20.4%
61
19.7%
62
19.5%
63
18.7%
64
18.6%
65
18.2%
66
18%
67
17.3%
68
17.3%
69
17%
70
16.3%
71
16.2%
72
16.2%
73
15.2%
74
14.4%
75
14.2%
76
13.7%
77
12.9%
78
12.3%
79
12.2%
80
11.8%
81
11.2%
82
10.4%
83
9.4%
84
9.1%
85
8.9%
86
7.1%
87
6.5%
88
6.2%
89
6%
90
5.5%
91
4.9%
92
4.8%
93
3.6%
94
2%
95
2%
96
1.8%
97
1.7%
98
1.5%
99
1.4%
Global Leaders in Spreadsheet Formula Proficiency
Emerging Data Literacy Development
Barriers to Spreadsheet Formula Proficiency
Spreadsheet Skills and Digital Inequality
The Impact of Spreadsheet Skills on Digital Work
Future Trends in Data Literacy Development
Basic Spreadsheet Formula Skills by Country – 2026
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1
87.5 (2023)
87.5%
2
81.6 (2023)
81.6%
3
73.2 (2022)
73.2%
4
67.3 (2023)
67.3%
5
66.5 (2021)
66.5%
6
57.4 (2023)
57.4%
7
56.0 (2023)
56%
8
55.0 (2023)
55%
9
54.4 (2023)
54.4%
10
53.7 (2019)
53.7%
11
52.9 (2023)
52.9%
12
51.0 (2022)
51%
13
48.9 (2023)
48.9%
14
48.7 (2023)
48.7%
15
47.0 (2022)
47%
16
46.7 (2023)
46.7%
17
46.5 (2019)
46.5%
18
46.1 (2023)
46.1%
19
45.8 (2023)
45.8%
20
45.5 (2015)
45.5%
21
45.3 (2023)
45.3%
22
44.5 (2023)
44.5%
23
42.8 (2023)
42.8%
24
42.5 (2023)
42.5%
25
41.8 (2023)
41.8%
26
41.5 (2021)
41.5%
27
41.3 (2023)
41.3%
28
40.6 (2023)
40.6%
29
40.5 (2023)
40.5%
30
38.9 (2023)
38.9%
31
38.3 (2019)
38.3%
32
38.3 (2023)
38.3%
33
38.0 (2023)
38%
34
38.0 (2022)
38%
35
37.5 (2023)
37.5%
36
37.4 (2023)
37.4%
37
36.0 (2020)
36%
38
35.5 (2022)
35.5%
39
34.7 (2023)
34.7%
40
34.6 (2023)
34.6%
41
34.6 (2021)
34.6%
42
34.4 (2023)
34.4%
43
33.9 (2023)
33.9%
44
32.9 (2023)
32.9%
45
32.1 (2022)
32.1%
46
31.2 (2023)
31.2%
47
30.6 (2023)
30.6%
48
27.9 (2020)
27.9%
49
27.1 (2023)
27.1%
50
25.5 (2023)
25.5%
51
25.2 (2017)
25.2%
52
25.2 (2023)
25.2%
53
24.7 (2020)
24.7%
54
23.9 (2023)
23.9%
55
23.6 (2021)
23.6%
56
23.2 (2020)
23.2%
57
21.5 (2023)
21.5%
58
21.4 (2016)
21.4%
59
21.2 (2017)
21.2%
60
20.4 (2021)
20.4%
61
19.7 (2014)
19.7%
62
19.5 (2023)
19.5%
63
18.7 (2023)
18.7%
64
18.6 (2023)
18.6%
65
18.2 (2019)
18.2%
66
18.0 (2021)
18%
67
17.3 (2023)
17.3%
68
17.3 (2023)
17.3%
69
17.0 (2023)
17%
70
16.3 (2020)
16.3%
71
16.2 (2023)
16.2%
72
16.2 (2023)
16.2%
73
15.2 (2022)
15.2%
74
14.4 (2023)
14.4%
75
14.2 (2023)
14.2%
76
13.7 (2023)
13.7%
77
12.9 (2024)
12.9%
78
12.3 (2017)
12.3%
79
12.2 (2022)
12.2%
80
11.8 (2021)
11.8%
81
11.2 (2023)
11.2%
82
10.4 (2019)
10.4%
83
9.4 (2018)
9.4%
84
9.1 (2017)
9.1%
85
8.9 (2023)
8.9%
86
7.1 (2021)
7.1%
87
6.5 (2023)
6.5%
88
6.2 (2022)
6.2%
89
6.0 (2019)
6%
90
5.5 (2021)
5.5%
91
4.9 (2019)
4.9%
92
4.8 (2020)
4.8%
93
3.6 (2021)
3.6%
94
2.0 (2020)
2%
95
2.0 (2019)
2%
96
1.8 (2016)
1.8%
97
1.7 (2022)
1.7%
98
1.5 (2023)
1.5%
99
1.4 (2017)
1.4%
📊 About the Data Data years vary by country (2011–2024). Where recent data is unavailable, projections are applied using historical trends. Year labels in the data table reflect projection targets, not survey years. This approach ensures comprehensive coverage while maintaining methodological transparency.
Methodology and Data Sources
Frequently Asked Questions
Q: What does spreadsheet formula proficiency mean and why is it important for modern work?
A: Spreadsheet formula proficiency measures the percentage of people who can use basic arithmetic formulas (addition, subtraction, multiplication, division) in spreadsheet applications like Excel or Google Sheets. If your country has 65%, it means 65 out of 100 people can effectively use basic spreadsheet formulas while 35 cannot. This matters because spreadsheet formulas are fundamental data literacy skills that enable efficient data analysis, financial calculations, and automated reporting. People with spreadsheet formula proficiency can analyze datasets, create financial models, and access data-related employment opportunities. Countries with high proficiency like UAE (87.5%), Saudi Arabia (81.6%), and Brunei (73.2%) have populations capable of performing data analysis essential for modern work. Low-proficiency countries face barriers where populations cannot efficiently analyze numerical data, limiting access to analytical work opportunities and economic participation. Spreadsheet formula skills represent a key indicator of broader data literacy adoption.
Q: Why do some countries have high spreadsheet formula proficiency while others lag significantly behind?
A: Spreadsheet formula proficiency depends on multiple interconnected factors that determine data literacy adoption rates across countries. Device access is fundamental—countries with high computer penetration see higher proficiency in data analysis skills. Software availability matters greatly since spreadsheet applications such as Excel must be accessible and affordable. Digital literacy education and training programs significantly influence proficiency. Younger populations demonstrate higher proficiency than older demographics due to greater digital exposure. Economic development generally correlates with higher proficiency. Educational systems that prioritize data literacy training produce populations with stronger spreadsheet competency. Developed nations like UAE, Saudi Arabia, and Brunei combine excellent device access, strong digital infrastructure, and comprehensive digital literacy programs that ensure populations develop fundamental data analysis skills. Developing countries often show lower proficiency due to limited device access, lower digital infrastructure investment, and fewer digital literacy training opportunities, though proficiency is growing as digital access expands and younger generations become larger population shares. The global digital skill gaps reflect broader patterns of digital inequality between countries.
Data Disclaimer: Projected data (future years) are estimates based on mathematical models. Actual values may differ. Learn about our methodology →
Sources
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Updated: 26.01.2026https://databrowser.uis.unesco.org/browser/EDUCATION/UIS-SDG4Monitoring/t4.4/i4.4.1
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