What is the name of this plot that has rows with two connected dots? I've been reading EIA report and this plot captured my attention. I now want to be able to create the same type of plot.

It shows the energy productivity evolution between two years (1990-2015) and adds the change value between this two periods.
What is the name of this type of plot? How can I create the same plot (with different countries) in excel?
 A: That's a dot plot.  It is sometimes called a "Cleveland dot plot" because there is a variant of a histogram made with dots that people sometimes call a dot plot as well.  This particular version plots two dots per country (for the two years) and draws a thicker line between them.  The countries are sorted by the latter value.  The primary reference would be Cleveland's book Visualizing Data.  Googling leads me to this Excel tutorial.  

I scraped the data, in case anyone wants to play with them.  
                       Country  1990  2015
                        Russia  71.5 101.4
                        Canada  74.4 102.9
 Other non-OECD Europe/Eurasia  60.9 135.2
                   South Korea 127.0 136.2
                         China  58.5 137.1
                   Middle East 170.9 158.8
                 United States 106.8 169.0
         Australia/New Zealand 123.6 170.9
                        Brazil 208.5 199.8
                         Japan 181.0 216.7
                        Africa 185.4 222.0
           Other non-OECD Asia 202.7 236.0
                   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: 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 = '#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(0.92, 0.20),
        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.
