library(dplyr) # for data manipulation library(tidyr) # for reshaping the data frame library(stringr) # string manipulation library(ggplot2) # graphing # create the data frame # (in wide format, as needed for the line segments): dat_wide = tibble::tribble( ~Country, ~Y1990, ~Y2015, 'Russia', 71.5, 101.4, 'Canada', 74.4, 102.9, 'Other non-OECD Europe/Eurasia', 60.9, 135.2, 'South Korea', 127, 136.2, 'China', 58.5, 137.1, 'Middle East', 170.9, 158.8, 'United States', 106.8, 169, 'Australia/New Zealand', 123.6, 170.9, 'Brazil', 208.5, 199.8, 'Japan', 181, 216.7, 'Africa', 185.4, 222, 'Other non-OECD Asia', 202.7, 236, 'OECD Europe', 173.8, 239.9, 'Other non-OECD Americas', 193.1, 242.3, 'India', 173.8, 260.6, 'Mexico/Chile', 221.1, 269.8 ) # a version reshaped to long format (for the points): dat_long = dat_wide %>% gather(key = 'Year', value = 'Energy_productivity', Y1990:Y2015) %>% mutate(Year = str_replace(Year, 'Y', '')) # create the graph: ggplot() + geom_segment(data = dat_wide, aes(x = Y1990, xend = Y2015, y = reorder(Country, Y2015), yend = reorder(Country, Y2015)), size = 3, colour = 'darkgrey''#D0D0D0') + geom_point(data = dat_long, aes(x = Energy_productivity, y = Country, colour = Year), size = 4) + labs(title = 'Energy productivity in selected countries \nand regions', subtitle = 'Billion dollars GDP per quadrillion BTU', caption = 'Source: EIA, 2016', x = NULL, y = NULL) + scale_colour_manual(values = c('#1082CD', '#042B41')) + theme_bw() + theme(legend.position = c(0.8592, 0.1520), legend.title = element_blank(), legend.box.background = element_rect(colour = 'black'), panel.border = element_blank(), axis.ticks = element_line(colour = '#E6E6E6')) ggsave('energy.png', width = 20, height = 10, units = 'cm') The answer by @gung is correct in identifying the chart type and providing a link to how to implement in Excel, as requested by the OP. But for others wanting to know how to do this in R/tidyverse/ggplot, below is complete code:
library(dplyr) # for data manipulation library(tidyr) # for reshaping the data frame library(stringr) # string manipulation library(ggplot2) # graphing # create the data frame # (in wide format, as needed for the line segments): dat_wide = tibble::tribble( ~Country, ~Y1990, ~Y2015, 'Russia', 71.5, 101.4, 'Canada', 74.4, 102.9, 'Other non-OECD Europe/Eurasia', 60.9, 135.2, 'South Korea', 127, 136.2, 'China', 58.5, 137.1, 'Middle East', 170.9, 158.8, 'United States', 106.8, 169, 'Australia/New Zealand', 123.6, 170.9, 'Brazil', 208.5, 199.8, 'Japan', 181, 216.7, 'Africa', 185.4, 222, 'Other non-OECD Asia', 202.7, 236, 'OECD Europe', 173.8, 239.9, 'Other non-OECD Americas', 193.1, 242.3, 'India', 173.8, 260.6, 'Mexico/Chile', 221.1, 269.8 ) # a version reshaped to long format (for the points): dat_long = dat_wide %>% gather(key = 'Year', value = 'Energy_productivity', Y1990:Y2015) %>% mutate(Year = str_replace(Year, 'Y', '')) # create the graph: ggplot() + geom_segment(data = dat_wide, aes(x = Y1990, xend = Y2015, y = reorder(Country, Y2015), yend = reorder(Country, Y2015)), size = 3, colour = 'darkgrey') + geom_point(data = dat_long, aes(x = Energy_productivity, y = Country, colour = Year), size = 4) + labs(title = 'Energy productivity in selected countries \nand regions', subtitle = 'Billion dollars GDP per quadrillion BTU', x = NULL, y = NULL) + scale_colour_manual(values = c('#1082CD', '#042B41')) + theme_bw() + theme(legend.position = c(0.85, 0.15), legend.title = element_blank(), legend.box.background = element_rect(colour = 'black'), panel.border = element_blank(), axis.ticks = element_line(colour = '#E6E6E6')) ggsave('energy.png', width = 20, height = 10, units = 'cm') 
This could be extended to add value labels and to highlight the colour of the one case where the values swap order, as in the original.