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1
Data Visualization for
Management
Consultants
A practical guide on how to show results during
consulting projects
2
In consulting you will spend a lot of time on creating presentations
to show the results of your analyses to the customer.
3
That is why, data visualization is so important. With proper display of data you
have more chances of convincing the customers that your approach makes sense.
4
That is why, data visualization is so important. With proper display of data you
have more chances of convincing the customers that your approach makes sense.
5
In this course I will teach how to use different data visualization techniques
to show the results of your analyses during consulting projects.
6
Target Group What you will learn What you will get
 Management Consultants &
Business Analysts
 Analysts working in PE, VC funds
 Analysts working in PMO or
Strategic Departments
 Controllers working in Financial
Department
 What kind of charts and slides you
can use during consulting projects
 How to read charts
 How to create fast and efficiently
good looking charts in Excel and in
Power Point
 Ready made analyses in Excel
 Templates of slides and charts
 List of Recommended readings
(articles, books)
7
How to read charts &
Which chart type you
should use
Essential Charts in Excel
Types of slides you can use
in presentation
How to create charts in
Power Point
Data Visualization using
Conditional Formatting
PivotCharts
Dynamic Charts in Excel
8
This presentation will teach you how to use
different data visualization techniques on the
level of top management consultants
9
What you will see in this presentation is a part of my online course where you
can find case studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course
10
How the course is
organized
11
In business you have to make a lot of important decisions
In this course I will teach how to use different data visualization techniques
to show the results of your analyses during consulting projects.
12
How to read charts &
Which chart type you
should use
Essential Charts in Excel
Types of slides you can use
in presentation
How to create charts in
Power Point
Data Visualization using
Conditional Formatting
PivotCharts
Dynamic Charts in Excel
13
Types of slides you can use
14
Types of slides you can use –
Introduction
15
In consulting you will be creating presentations to show the results of your
analyses. We will discuss the main types of slides you will be using.
16
I will show you show you not only charts but other types of slides as
well
17
Slides for Management
Consultants & Business Analysts
Examples from consulting projects
presentation
We will go through main examples Check the presentation in Additional
Resources for more than 300 examples of slides
18
How to read charts
19
How to read charts –
Introduction
20
Consulting jobs requires fast reading and understanding of charts. In this
section, we will discuss what you should pay attention to, not to make mistakes.
21
In this section we will talk about the following things
What is a good chart
The process of creating
charts
How to lie with charts
22
How to lie with charts
23
People on purpose or by accident lie quite often with charts. In
this lecture, I will show you the most often used methods.
24
Below some of the ways, in which they may try to influence you with
the charts
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that supports
the hypothesis
Message inconsistent with data
25
Let’s start with the first one
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that supports
the hypothesis
Message inconsistent with data
26
Below an example how you can adjust axes to make difference between
data to look smaller or bigger
Wrong graph Correct graph
100
101
102
99
100
101
102
103
Year 1 Year 2 Year 3
100 101 102
0
20
40
60
80
100
120
Year 1 Year 2 Year 3
Sales of product A in following years
In M USD
Sales of product A in following years
In M USD
27
Below an example how you can adjust axes to make difference between
data to look smaller or bigger
Wrong graph Correct graph
100
101
102
Year 1 Year 2 Year 3
100 101 102
Year 1 Year 2 Year 3
Sales of product A in following years
In M USD
Sales of product A in following years
In M USD
28
Let’s see how we can change the data reception through trendlines
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
29
Below an example of the use of a trendline to data with no correlation
between them
Wrong graph Correct graph
0
2
4
6
8
10
0 2 4 6 8 10
Correlation between 2 data series
0
2
4
6
8
10
0 2 4 6 8 10
Correlation between 2 data series
30
Let’s see how we can change of the units may be confusing to the
recipient
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
31
Below an example of how the use of incorrect units may affect the
readability of the data in the graph
Wrong graph Correct graph
200 000
300 000
400 000
Year 1 Year 2 Year 3
Potential revenues in following years
In thousands of USD
200
300
400
Year 1 Year 2 Year 3
Potential revenues in following years
In M USD
32
Let’s see how we can choice of colors may affect graph interpretation
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
33
Below an example of wrong graph when the incorrect colors of the
graph may be confusing for data interpreting
Qualify Leads Create Demand
Negotiate the
contract
Sign the contract Up-sell
 Retail
Industry
30%
30% 30% 40% 50%
 Health
Industry
80%
60% 40% 20% 50%
 Financial
Industry
10%
70% 40% 25% 30%
 Technology 30%
20% 80% 80% 70%
Sales funnel by cohorts using color coding
In %
0% - 50%
50% - 100%
34
Below an example of correct graph when the colors of the graph
support data interpreting
0% - 30%
35% - 40%
45% - 50%
55% - 70%
More than 80%
Qualify Leads Create Demand
Negotiate the
contract
Sign the contract Up-sell
 Retail
Industry
30%
30% 30% 40% 50%
 Health
Industry
80%
60% 40% 20% 50%
 Financial
Industry
10%
70% 40% 25% 30%
 Technology 30%
20% 80% 80% 70%
Sales funnel by cohorts using color coding
In %
35
Let’s see how we can manipulate data selecting the period that support
our hypothesis
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
36
Below an example of how data manipulation can support our
hypothesis
Revenues by years
In M USD
100
150
90
80
200
300
Year 1 Year 2 Year 3 Year 4 Year 5 Year 6
Revenues by years
In M USD
Wrong graph Correct graph
100
150
90
80
200
300
Year 1 Year 2 Year 3 Year 4 Year 5 Year 6
Message: The revenues have increased in recent years
37
Let’s see how message that is inconsistent with data may be confusing
for data interpreting
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that support
the hypothesis
Message inconsistent with data
38
Below an example of message that is inconsistent with data
320
100
80
300
290 295
Month 1 Month 2 Month 3 Month 4 Month 5 Month 6
Sales by months
In thousands of EUR
Message: A slight decrease in sales in months 2 and 3 was caused by some problems with the
availability of products at the manufacturer
39
Below an example of message that is consistent with data
320
100
80
300
290 295
Month 1 Month 2 Month 3 Month 4 Month 5 Month 6
Sales by months
In thousands of EUR
Message: A large drop in sales in month 2 and 3 was caused by big problems with the
availability of products at the manufacturer
40
Below some of the ways, in which they may try to influence you with
the charts
Adjust axes to make difference
look smaller or bigger
Trendlines
Choice of units
Choice of colors
Select the period that supports
the hypothesis
Message inconsistent with data
41
Check the video on YouTube for more details
Click here to go to the video
42
What is a good chart
43
Now let’s see when can we say that the chart is a good one
Consistent with message
Clear easy to read
The right type
With properly defined color
coding
Adjusted to the audience
Has an Excel to support it
With proper units Don’t manipulate the audience
44
The process of
creating charts
45
Create a structure of
the presentation
Write down the
messages you want to
convey
Sketch the slides
Create a template in
Power Point
For every slide create
the underlying
analysis or gather
needed info
Check for errors,
mistakes and
omissions
Write the beginning
and the end of the
presentation
Create Executive
Summary
Check the flow of the
whole presentation
and modify if needed
slides or the structure
Fill in the slides with
data and charts
Just as a reminder the creation of presentation consists of 10 phases of
46
Create a structure of
the presentation
Write down the
messages you want to
convey
Sketch the slides
Create a template in
Power Point
For every slide create
the underlying
analysis or gather
needed info
Check for errors,
mistakes and
omissions
Write the beginning
and the end of the
presentation
Create Executive
Summary
Check the flow of the
whole presentation
and modify if needed
slides or the structure
Fill in the slides with
data and charts
The choice of slides is done in the Sketch phase. You may modify the
charts later on
47
If we were to take a look only at the process of creating a chart we
would have the following sequence
Write down the
messages you want
to convey
Decide what type of
data you want to
show
Select the type of
chart that suits your
needs
Input data into the
chart
Modify or change
the type of the chart
48
For more details and content check my online course where you can find case
studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course
49
Which chart type you should use
50
Which chart type you should use
– Introduction
51
Before you decide which chart to choose, it's important to understand
why you need one and what story you want to tell your audience.
52
There are 7 main reasons for which we can create a graphical
representation of data
What I want to show
How something
has change over
time
Compare across
2-dimensions
different options
Compare across
3-dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
53
There are 7 main reasons for which we can create a graphical
representation of data
What I want to show
How something
has change over
time
Compare across
2-dimensions
different options
Compare across
3-dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Clustered column
chart
Line chart
Stacked area
chart
Scatter Chart /
Bubble chart
Heat map
100 % stacked
column
2 Clustered
column charts
with 1 column
1 Clustered
column charts
with 2 columns
2 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 2 Bars
Combo chart with
– column and line
3 Clustered
column charts
with 1 column
1 Clustered
column chart
with 3 columns
Bubble chart
3 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 3 Bars
Snake graph (Line
graph with
markers)
Radar chart
100 % Stacked
column chart
100 % Stacked
bar chart
Waterfall chart
Pareto chart
Infographic chart
Other
Funnel chart
Clustered column
chart
Clustered Bar
Waterfall chart
Heat map
Map with color
coding
Map + Clustered
column chart
Regular charts
Map + Clustered
bar chart
54
There are 7 main reasons for which we can create a graphical
representation of data
What I want to show
How something
has change over
time
Compare across
2-dimensions
different options
Compare across
3-dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
55
How to show that something
has change over time
56
Let's see how we can present data that changes over time
What I want to show
How something has
change over time
Compare across 2-
dimensions
different options
Compare across 3-
dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Clustered column
chart
Line chart
Stacked area chart
Scatter Chart /
Bubble chart
Heat map
100 % stacked
column
57
Check the video on YouTube for more details
Click here to go to the video
58
Clustered columns
100
150
200
250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
59
Stacked column with absolute values
100 150 200 250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
60
100 % stacked column chart with absolute values
100
150 200 250
400
400
200
300 450
500
80
100
200 250 300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
61
100 % stacked column chart with percentages
17%
33% 29% 26%
33%
69%
44%
43% 47%
42%
14%
22%
29% 26% 25%
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Share of business units in Total Revenues of a chain of clinics by years
In percentage
62
Line chart
100
150
200
250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
63
Bubble chart
Revenues of a chain of clinics by years and business units
In M of EUR
100
400
80
150
200
100
200
300
200
250
450
250
400
500
300
0 1 2 3 4 5 6
Dentists
GP Doctors
Others
Year
64
Scatter chart – same color with labels
Revenues of a chain of clinics by years and business units
In M of EUR
Dentists; 100
GP Doctors; 400
Others; 80
Dentists; 150
GP Doctors; 200
Others; 100
Dentists; 200
GP Doctors; 300
Others; 200
Dentists; 250
GP Doctors; 450
Others; 250
Dentists; 400
GP Doctors; 500
Others; 300
0 1 2 3 4 5 6
Year
65
Scatter chart – different colors with labels
Revenues of a chain of clinics by years and business units
In M of EUR
Dentists; 100
GP Doctors; 400
Others; 80
Dentists; 150
GP Doctors; 200
Others; 100
Dentists; 200
GP Doctors; 300
Others; 200
Dentists; 250
GP Doctors; 450
Others; 250
Destists; 400
GP Doctors; 500
Others; 300
0 1 2 3 4 5 6
Year
Dentists
GP Doctors
Others
66
Scatter chart – different colors no labels
Revenues of a chain of clinics by years and business units
In M of EUR
100
400
80
150
200
100
200
300
200
250
450
250
400
500
300
0 1 2 3 4 5 6
Year
Dentists
GP Doctors
Others
67
Heat map
Revenues of a chain of clinics by years and business units
In M of EUR
Dentists
GP Doctors
Others
Year 1 Year 2 Year 3 Year 4 Year 5
< 100
100 – 199
200 – 299
300 – 399
400 – 499
400 – 499
68
When it comes to me, in most cases I would use the clustered column
chart or the stacked column chart
100 150 200 250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
100
150
200
250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Stacked column in absolute values Clustered column
69
How to compare different
options across 2 dimensions
70
Let's see how we can present data with 2 dimensions
What I want to show
How something has
change over time
Compare across 2-
dimensions different
options
Compare across 3-
dimensions different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
2 Clustered column
charts with 1 column
1 Clustered column
charts with 2
columns
2 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 2 Bars
Combo chart with –
column and line
Scatter chart
71
211
117
200 200
50
Company 1 Company 2 Company 3 Company 4 Company 5
Cost of the project
In thousands of USD
36 33
52 52
16
Company 1 Company 2 Company 3 Company 4 Company 5
Time needed for full implementation
In weeks
2 Clustered column charts with 1 column
72
211
117
200 200
50
36 33 52 52
16
Company 1 Company 2 Company 3 Company 4 Company 5
Cost of the project vs Time needed for full implementation
In thousands of USD & In weeks
1 Clustered column charts with 2 dimensions
Cost of project (in thousands of USD)
Time needed (in weeks)
73
211
117
200 200
50
36
33
52 52
16
0
10
20
30
40
50
60
0
50
100
150
200
250
Company 1 Company 2 Company 3 Company 4 Company 5
Cost of the project vs Time needed for full implementation
Combo chart with – column and line with 2 visible axes
Cost of project (in thousands of USD)
Time needed (in weeks)
In thousand of USD In weeks
74
211
117
200 200
50
36
33
52 52
16
0
10
20
30
40
50
60
0
50
100
150
200
250
Company 1 Company 2 Company 3 Company 4 Company 5
Cost of the project vs Time needed for full implementation
In thousands of USD & In weeks
Combo chart with – column and line with 2 hidden axes
Cost of project (in thousands of USD)
Time needed (in weeks)
75
50
200
200
117
211
Company 5
Company 4
Company 3
Company 2
Company 1
Cost of the project
In thousands of USD
16
52
52
33
36
Company 5
Company 4
Company 3
Company 2
Company 1
Time needed for full implementation
In weeks
2 Clustered bar charts with 1 Bar
76
1 Clustered bar with 2 Bars
50
200
200
117
211
16
52
52
33
36
Company 5
Company 4
Company 3
Company 2
Company 1
Cost of the project & Time needed for full implementation
In thousands of USD & In weeks
Cost of project (in thousands of USD)
Time needed (in weeks)
77
Scatter Chart
Cost of the project
In thousands of USD
Company 1
Company 2
Company 3
Company 4
Company 5
0
50
100
150
200
250
0 10 20 30 40 50 60
Time needed for full
implementation
(In weeks)
78
When it comes to me, in most cases I would use the 2 Clustered column
charts with 1 column or scatter chart
2 Clustered column charts with 1 column Scatter chart
79
How to compare different
options across 3 dimensions
80
Let's see how we can present data with 3 dimensions
What I want to show
How something has
change over time
Compare across 2-
dimension different
options
Compare across 3-
dimension different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
3 Clustered column
charts with 1
column
1 Clustered column
chart with 3
columns
Bubble chart
3 Clustered bar
charts with 1 Bar
1 Clustered bar
chart with 3 Bars
81
4,5
3
4
3
2
1
2
Cottage
cheese
Cheddar Yoghurt Feta Yellow
cheese
Milk
desserts
Ice cream
Attractiveness of product category
(1- Low; 5 – High)
3 Clustered column charts with 1 column
Difficulty of implementation product category
(1-Small; 5-Big)
Potential revenues generated by product category
In M USD
3
4 4 5
2
1
4
Cottage
cheese
Cheddar Yoghurt Feta Yellow
cheese
Milk
desserts
Ice cream
100
30
300
30
150
200
150
Cottage
cheese
Cheddar Yoghurt Feta Yellow
cheese
Milk
desserts
Ice cream
82
1 Clustered column chart with 3 columns
4,5 3 4 3 2 1 2
3 4 4 4,5 2 1 4
100
30
300
30
150
200
150
Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream
Attractiveness, Difficulty of implementation and Potential revenues generated by product category
Attractiveness
Difficulty
Potential revenues
83
Bubble chart
Difficulty level
(1-Small; 5-Big)
Attractiveness
(1- Low; 5 – High)
Cottage cheese; 100
Cheddar; 30
Yoghurt; 300
Feta; 30
Yellow cheese; 150
Milk desserts; 200
Ice cream; 150
0
1
2
3
4
5
0 1 2 3 4 5
Potential Revenues
In M of USD
84
4,5
3
4
3
2
1
2
Cottage cheese
Cheddar
Yoghurt
Feta
Yellow cheese
Milk desserts
Ice cream
Attractiveness of product category
(1- Low; 5 – High)
3 Clustered bar charts with 1 bar
Difficulty of implementation product category
(1-Small; 5-Big)
Potential revenues generated by product category
In M USD
3
4
4
5
2
1
4
Cottage cheese
Cheddar
Yoghurt
Feta
Yellow cheese
Milk desserts
Ice cream
100
30
300
30
150
200
150
Cottage cheese
Cheddar
Yoghurt
Feta
Yellow cheese
Milk desserts
Ice cream
85
When it comes to me, in most cases I would use the 2 bar charts or 3
Clustered bar charts with 1 bar
Bubble Charts 3 Clustered bar charts with 1 bar
86
How to compare different options
across more than 3 dimensions
87
Let's see how we can present data that change their composition over time
What I want to show
How something has
change over time
Compare across 2-
dimensions different
options
Compare across 3-
dimensions different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Snake graph (Line
graph with markers)
Radar chart
88
Snake graph (Line graph with markers)
Price image for 2 firms
In USD
0
20
40
60
80
100
Regular price level Promotions /
Discounts
Price emotional
impact
Assortment Image Price Fairness Value for money
level
Consitency of price
strategy
Price Transparency
Firm A Firm B
Importance of specific criteria
% of people that thought that criteria is the most important
25%
19%
12% 10% 10% 10% 9%
5%
Regular price level Promotions /
Discounts
Price emotional
impact
Assortment Image Price Fairness Value for money level Consitency of price
strategy
Price Transparency
89
Radar Chart
0
20
40
60
80
100
Regular price level
Promotions / Discounts
Price emotional impact
Assortment Image
Price Fairness
Value for money level
Consitency of price strategy
Price Transparency
Firm A Firm B
Price image for 2 firms
In USD
90
How to show composition /
structure
91
Let's see how we can present data that change their composition over time
What I want to show
How something has
change over time
Compare across 2-
dimension different
options
Compare across 3-
dimension different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
100 % Stacked
column chart
100 % Stacked bar
chart
100 % Stacked area
chart
Waterfall chart
Pareto chart
Infographic chart
Doughnut chart
Tree Map
92
100 % stacked column chart with absolute values
100
150 200 250
400
400
200
300 450
500
80
100
200 250 300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
93
100 % stacked column chart with percentages
17%
33% 29% 26%
33%
69%
44%
43% 47%
42%
14%
22%
29% 26% 25%
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Share of business units in Total Revenues of a chain of clinics by years
In percentage
94
Stacked column chart with absolute values
100 150 200 250
400
400
200
300
450
500
80
100
200
250
300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
95
100 % stacked bar chart with absolute values
100
150
200
250
400
400
200
300
450
500
80
100
200
250
300
Year 1
Year 2
Year 3
Year 4
Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
96
100 % stacked bar chart with percentages
17%
33%
29%
26%
33%
69%
44%
43%
47%
42%
14%
22%
29%
26%
25%
Year 1
Year 2
Year 3
Year 4
Year 5
Dentists GP Doctors Others
Share of business units in Total Revenues of a chain of clinics by years
In percentage
97
100% Stacked area chart with absolute values
100
150 200 250
400
400
200
300 450
500
80
100
200 250 300
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
98
100% Stacked area chart with percentages
17%
33% 29% 26%
33%
69%
44%
43% 47%
42%
14%
22%
29% 26% 25%
Year 1 Year 2 Year 3 Year 4 Year 5
Dentists GP Doctors Others
Revenues of a chain of clinics by years and business units
In M of EUR
99
Waterfall chart
100
400
80
580
Dentists GP Doctors Others Total
Revenues of a chain of clinics and business units in Year 1
In M of EUR
100
Infographic chart
Share of business units in Total Revenues of a chain of clinics in Year 1
In percentage
17%
Dentists
69 %
GP Doctors
14 %
Others
101
Infographic chart
Share of business units in Total Revenues of a chain of clinics in Year 1
In percentage
17%
Dentists
69 %
GP Doctors
14 %
Others
102
Infographic chart
Share of business units in Total Revenues of a chain of clinics in Year 1
In percentage
Dentists – 17%
GP Doctors – 69%
Others – 14%
103
Pareto chart
200 190 180 170 166 150 140 135 120 120 110 90 95 80 70 60 50 40 30 10
9%
18%
26%
34%
41%
48%
54%
60%
66%
71%
76%
80%
85%
88%
91%
94% 96% 98% 100% 100%
0%
20%
40%
60%
80%
100%
120%
0
50
100
150
200
250
Client 1 Client 2 Client 3 Client 4 Client 5 Client 6 Client 7 Client 8 Client 9 Client 10Client 11Client 12Client 13Client 14Client 15Client 16Client 17Client 18Client 19Client 20
Average value of annual sales by individual clients
In thousands of EUR
104
Doughnut chart
Share of Product sales in Total Revenues of a retail company in Year 1 vs Year 2
In percentage
10%
12%
24%
6%
18%
19%
11%
12%
14%
28%
7%
19%
15%
5%
Product 1
Product 2
Product 3
Product 4
Product 5
Product 6
Product 7
Year 1
Year 2
105
Doughnut chart
Sales and Margin of the following products
In percentage
10%
12%
24%
6%
18%
19%
11%
5%
11%
43%
10%
12%
12%
7%
Product 1
Product 2
Product 3
Product 4
Product 5
Product 6
Product 7
Margin
Sales
106
When it comes to me, in most cases I would use the 100 % stacked
column chart or waterfall chart
100 % stacked column chart Waterfall chart
107
How to show funnels
108
Let's see how we can present funnel analysis
What I want to show
How something has
change over time
Compare across 2-
dimensions
different options
Compare across 3-
dimensions
different options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local differences
Funnel chart
Clustered column
chart
Clustered Bar
Waterfall chart
Heat map
109
Conversion rate
100%
85%
73%
87%
70%
64%
Number of customers who, after clicking on an advertisement of the app, became its users
In %
Funnel chart
110
Funnel chart using shapes
Click to the add
Visit app store website
Run the app
Download and install app
Fill in registration data
Complete registration
100%
85%
62%
54%
38%
24%
% of initial
Group
Conversion
rate
100%
85%
73%
87%
70%
64%
Number of customers who, after clicking on an advertisement of the app, became its users
In %
111
Clustered column chart
20
18
14
7
3
Start session Product viewed Add to cart Registered Purchase
Funnel Analysis of customers who decided to book a hotel online
In millions
112
Clustered bart chart
Funnel Analysis of customers who decided to book a hotel online
In millions
3
7
14
18
20
Purchase
Register
Add to cart
Product viewed
Start session
113
Waterfall chart
Funnel Analysis of customers who decided to book a hotel online
In millions
20
2
18
4
14
7
7
3
3
Start session End session Product
viewed
Product
abandoned
Add to cart Product not
added
Registered Not registered Purchase
114
Qualify Leads Create Demand Negotiate the contract Sign the contract Up-sell
Heat map
 Retail Industry 30%
30% 30% 40% 50%
 Health
Industry
80%
60% 40% 20% 50%
 Financial
Industry
10%
70% 40% 25% 30%
 Technology 30%
20% 80% 80% 70%
Sales funnel by cohorts using color coding
In %
115
When it comes to me, in most cases I would use the 100 % stacked
column chart or waterfall chart
Clustered bar chart Waterfall charts Heat map charts
116
How to show local differences
117
Let's see how we can present local differences
What I want to show
How something has
change over time
Compare across 2-
dimension different
options
Compare across 3-
dimension different
options
Compare across
more than 3
dimensions
Composition Funnel Analysis Local difference
Map with color
coding
Map + Clustered
column chart
Regular charts
Map + Clustered
bar chart
118
Map with color coding – PowerPoint map
Shares of sales of cosmetics products in following countries
In %
100%
Shares of sales :
74%
31%
26%
85%
14%
119
100%
Shares of sales :
Map with color coding – map made out of shapes
74%
31%
26%
Shares of sales of cosmetics products in following countries
In %
85%
14%
120
PowerPoint Map + Clustered column chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland United
Kingdom
Germany France Spain Italy
121
Map made out of shapes + Clustered column chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland United
Kingdom
Germany France Spain Italy
122
PowerPoint Map + Clustered bar chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland
United Kingdom
Germany
France
Spain
Italy
123
Map made out of shapes + Clustered bart chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland
United Kingdom
Germany
France
Spain
Italy
124
Clustered bar chart
Shares of sales of cosmetics products in following countries
In %
100%
85%
74%
31%
26%
14%
Poland
United Kingdom
Germany
France
Spain
Italy
125
For more details and content check my online course where you can find case
studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course
126
Essential Charts in Excel
127
Essential Charts in Excel –
Introduction
128
Let’s see how you can create fast and efficiently charts in Excel. In
this section we will concentrate on some technical tips.
129
In this section we will talk about the following things
How to format the chart
How to have a one chart
with 2 axes
Basics of creating a chart in
Excel
How to reverse the order
of data in the chart
How to reuse formatting
from previous charts
Bar chart with different
colors
How to add total for
stacked column charts
How to highlight specific
periods on the chart
How to create more
complicated charts
130
Check the video on YouTube showing how to create a waterfall chart
Click here to go to the video
131
How to create more
complicated charts
132
Sometimes you will want to create more complicated charts that you
cannot do directly in Excel. I will show how to find a way around
133
In the next lectures we will have a look at 2 case studies
Waterfall Charts showing
potential stores
Scatter Charts with labels
showing new products
134
Check the video on YouTube showing how to create a waterfall chart
Click here to go to the video
135
Check the video on YouTube showing how to create scatter plot with labels
Click here to go to the video
136
Data Visualization using
Conditional Formatting
137
Data Visualization using CF
– Introduction
138
For data visualization you don’t have to use charts. In some cases conditional
formatting does a great job. In this section we will discuss it in practices
139
In this section we will talk about the following things
Charts using conditional
formatting
Heat Maps using
conditional formatting
Basics of Conditional
Formatting
Sparklines
140
How to create charts in Power
Point
141
How to create charts in Power
Point – Introduction
142
Let’s see how you can create fast and efficiently charts in Power
Point. In this section we will concentrate on some technical tips.
143
In this section we will talk about the following things
How to make the chart look
nice in Power Point
Library of formatted charts
Basics of creating a chart in
Power Point
Chart Animation
144
Check the video on YouTube for more details
Click here to go to the video
145
Pivot Charts
146
Pivot Charts –
Introduction
147
Pivot Charts are great tools that will help you with data visualization.
In this section we will have a look how to use them in practice.
148
In this section we will talk about the following things
Combining slicers with
Pivot Charts
Building a Dashboard
Pivot Charts Example
Online store-checks – Case
study using Pivots
Look & Feel of Pivot Chart
Using Customer reviews –
Case study using Pivots
149
Online store-checks –
Introduction
150
In many cases you will have to do not only store checks in physical stores
but also in online stores. We will discuss this subject in this lecture.
151
Before going deeper into this lecture I would recommend revising the
lecture on offline store-checks
Offline store-check
152
In the online store checks you can compare different types of stores
Compare different
online stores
Compare offline to
online for the same
brand
Compare offline to
online for different
brands
 For example H&M online to
Zara online
 For example H&M online to
H&M offline
 For example H&M online to
Zara offline
 Understand difference in
product range and pricing
used in the online world
 Understand difference in
product range and pricing
policy used by the same
brand in offline and online
worlds.
 Do they have the same policy
or they use different sets of
rules for the online and
offline world
 You want to compare 2
brands
 For one of them you don’t
have the offline data i.e.
from another country. In this
case you can use the online
data as a proxy to make the
comparison.
 This will require adjustments
so you can trulely ompare
the 2 brands
Compare different
offline stores
 For example H&M offline to
Zara offline
 Understand difference in
product range and pricing
used in the offline world
Example
Purpose
153
Below the main methods you can use to do the online store-check
Create a script to
automate the
process
Use data scraping
tools
Do the store-check
manually
Buy data from the
3rd party
Use the API or ask
for data the
provider
154
Online store-checks – What
information you gather
155
During online store-check you most likely will be gathering the following
information
Name, photos of the product &
assigned categories
Prices of specific products
Available quantity
# of reviews
Rules for organizing data on the
webpage
Rules for presenting data
Additional information on the
availability in offline stores
Discounts on the product
156
Online store-checks – Case
Introduction
157
Let’s see how you can use the online store-checks to analyze the market.
This time around we will do a store-check for cosmetics
158
A few information about what you have to do
You will concentrate only on
cosmetics for the face
You have data on 200 SKUs
You have information on the
brand, price, group, size
Analyze the data from the online
store-check
159
Using customer reviews –
Introduction
160
The information from customers is extremely important. Nowadays we have plenty of sites
that gather customers reviews. We will discuss how you can use them in market research
161
Below a short summary of what you can learn from sites with review
What customers pay attention
to
Customer Segments
What current players are good
at
What current players don’t do
too well
You can estimate NPS (Net
Promoter Score)
You can check how popular
certain brands / solutions are
In some cases you can contact
the reviewer
You learn the language used by
the customers
162
Using customer reviews –
Source
163
Below some examples where you can find customer reviews
SaaS Products Restaurants / Hotels Local Services
 G2
 Trust Radius
 Software Advice
 GetApp
 Founder Kit
 AppBot
 Yelp
 TripAdvisor
 Airbnb
 Booking.com
 DoorDash
 Yelp
 Google Reviews
 Facebook Reviews
 Task Rabbit
Consumer Goods
 Amazon
 Walmart
 Best Buy
164
Using Customer reviews – Case
Introduction
165
Imagine that you were hired by a firm to analyze the emailing software market and to tell
them whether there is a niche for them to create a new product. Use the customer reviews
166
A few information about what you have and what are your goals
You decided to concentrate on the
Mailchimp customers
Your boss proposed to concentrate
only on the users that have 3 stars
You have gathered data from 900
users by data scraping
Propose on which aspect they
should concentrate
167
Sites for comparing products
– Introduction
168
One of the ways to understand the market and competitors is to try and compare products
especially from different firms. You can do that using comparison tools / sites
169
Below a short summary of what you can learn from comparison sites
How popular specific product is
To what extent products differ in
terms of features / characteristics
What customer segments do they
target
Pros and Cons of each and every
solution
How widely specific products are
used
Pricing and sales strategy
Customer support offered
Links to other products / Product
Ecosystem
170
Below some examples where you can find product comparison
Some Review Sites
Sites dedicated to
comparisons
Other
 G2
 Trust Radius
 Software Advice
 GetApp
 Comparison done by
influencers
 Product Rankings
Reddit
 Quora
E-commerce /
Marketplaces
 Amazon
 Best Buy
171
Dynamic Charts in Excel
172
Dynamic Charts in Excel –
Introduction
173
In some cases you will want to make your charts more dynamic so it can readjust to
changes in parameters or questions asked. I will show you how you can achieve it in Excel.
174
In this section we will talk about the following things
Dynamic Charts using
VLOOKUP & MATCH
Dynamic Charts using
SUMIFS
Dynamic Charts using Pivot
Charts
How to add new data to
the chart automatically
175
Advanced Charts in Excel
176
Advanced Charts in Excel –
Introduction
177
In 80% of the time you will be using simple charts similar to what we have shown
so far. Now we will have a look at some interesting charts that are less frequently.
178
In this section we will talk about the following things
Maps Tree Maps
Pareto Chart
Doughnut Charts
Funnel Charts Box & Whisker Chart
179
For more details and content check my online course where you can find case
studies showing analyses along with detailed calculations in Excel
Data Visualization for Management
Consultants & Analysts
$190
$19
Click here to check my course
180
Badass
Consultants
Blog
Subscribe to our channels:
181
Essential Excel for Business
Analysts and Consultants
A practical guide
presentation
Check also my other presentations
182
Retail for Business Analysts and
Management Consultants
A practical guide
presentation
Check also my other presentations
183
Strategy for Management
Consultants & Business Analysts
Practical Guide
presentation
For more information on Strategy check also my other presentation
184
How to solve problems like
Management Consultants
Practical Guide
presentation
Check also my other presentations
185
KPIs for Management
Consultants & Business Analysts
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presentation
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Data Visualization for Management Consultants & Analyst

  • 1. 1 Data Visualization for Management Consultants A practical guide on how to show results during consulting projects
  • 2. 2 In consulting you will spend a lot of time on creating presentations to show the results of your analyses to the customer.
  • 3. 3 That is why, data visualization is so important. With proper display of data you have more chances of convincing the customers that your approach makes sense.
  • 4. 4 That is why, data visualization is so important. With proper display of data you have more chances of convincing the customers that your approach makes sense.
  • 5. 5 In this course I will teach how to use different data visualization techniques to show the results of your analyses during consulting projects.
  • 6. 6 Target Group What you will learn What you will get  Management Consultants & Business Analysts  Analysts working in PE, VC funds  Analysts working in PMO or Strategic Departments  Controllers working in Financial Department  What kind of charts and slides you can use during consulting projects  How to read charts  How to create fast and efficiently good looking charts in Excel and in Power Point  Ready made analyses in Excel  Templates of slides and charts  List of Recommended readings (articles, books)
  • 7. 7 How to read charts & Which chart type you should use Essential Charts in Excel Types of slides you can use in presentation How to create charts in Power Point Data Visualization using Conditional Formatting PivotCharts Dynamic Charts in Excel
  • 8. 8 This presentation will teach you how to use different data visualization techniques on the level of top management consultants
  • 9. 9 What you will see in this presentation is a part of my online course where you can find case studies showing analyses along with detailed calculations in Excel Data Visualization for Management Consultants & Analysts $190 $19 Click here to check my course
  • 10. 10 How the course is organized
  • 11. 11 In business you have to make a lot of important decisions In this course I will teach how to use different data visualization techniques to show the results of your analyses during consulting projects.
  • 12. 12 How to read charts & Which chart type you should use Essential Charts in Excel Types of slides you can use in presentation How to create charts in Power Point Data Visualization using Conditional Formatting PivotCharts Dynamic Charts in Excel
  • 13. 13 Types of slides you can use
  • 14. 14 Types of slides you can use – Introduction
  • 15. 15 In consulting you will be creating presentations to show the results of your analyses. We will discuss the main types of slides you will be using.
  • 16. 16 I will show you show you not only charts but other types of slides as well
  • 17. 17 Slides for Management Consultants & Business Analysts Examples from consulting projects presentation We will go through main examples Check the presentation in Additional Resources for more than 300 examples of slides
  • 18. 18 How to read charts
  • 19. 19 How to read charts – Introduction
  • 20. 20 Consulting jobs requires fast reading and understanding of charts. In this section, we will discuss what you should pay attention to, not to make mistakes.
  • 21. 21 In this section we will talk about the following things What is a good chart The process of creating charts How to lie with charts
  • 22. 22 How to lie with charts
  • 23. 23 People on purpose or by accident lie quite often with charts. In this lecture, I will show you the most often used methods.
  • 24. 24 Below some of the ways, in which they may try to influence you with the charts Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that supports the hypothesis Message inconsistent with data
  • 25. 25 Let’s start with the first one Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that supports the hypothesis Message inconsistent with data
  • 26. 26 Below an example how you can adjust axes to make difference between data to look smaller or bigger Wrong graph Correct graph 100 101 102 99 100 101 102 103 Year 1 Year 2 Year 3 100 101 102 0 20 40 60 80 100 120 Year 1 Year 2 Year 3 Sales of product A in following years In M USD Sales of product A in following years In M USD
  • 27. 27 Below an example how you can adjust axes to make difference between data to look smaller or bigger Wrong graph Correct graph 100 101 102 Year 1 Year 2 Year 3 100 101 102 Year 1 Year 2 Year 3 Sales of product A in following years In M USD Sales of product A in following years In M USD
  • 28. 28 Let’s see how we can change the data reception through trendlines Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that support the hypothesis Message inconsistent with data
  • 29. 29 Below an example of the use of a trendline to data with no correlation between them Wrong graph Correct graph 0 2 4 6 8 10 0 2 4 6 8 10 Correlation between 2 data series 0 2 4 6 8 10 0 2 4 6 8 10 Correlation between 2 data series
  • 30. 30 Let’s see how we can change of the units may be confusing to the recipient Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that support the hypothesis Message inconsistent with data
  • 31. 31 Below an example of how the use of incorrect units may affect the readability of the data in the graph Wrong graph Correct graph 200 000 300 000 400 000 Year 1 Year 2 Year 3 Potential revenues in following years In thousands of USD 200 300 400 Year 1 Year 2 Year 3 Potential revenues in following years In M USD
  • 32. 32 Let’s see how we can choice of colors may affect graph interpretation Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that support the hypothesis Message inconsistent with data
  • 33. 33 Below an example of wrong graph when the incorrect colors of the graph may be confusing for data interpreting Qualify Leads Create Demand Negotiate the contract Sign the contract Up-sell  Retail Industry 30% 30% 30% 40% 50%  Health Industry 80% 60% 40% 20% 50%  Financial Industry 10% 70% 40% 25% 30%  Technology 30% 20% 80% 80% 70% Sales funnel by cohorts using color coding In % 0% - 50% 50% - 100%
  • 34. 34 Below an example of correct graph when the colors of the graph support data interpreting 0% - 30% 35% - 40% 45% - 50% 55% - 70% More than 80% Qualify Leads Create Demand Negotiate the contract Sign the contract Up-sell  Retail Industry 30% 30% 30% 40% 50%  Health Industry 80% 60% 40% 20% 50%  Financial Industry 10% 70% 40% 25% 30%  Technology 30% 20% 80% 80% 70% Sales funnel by cohorts using color coding In %
  • 35. 35 Let’s see how we can manipulate data selecting the period that support our hypothesis Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that support the hypothesis Message inconsistent with data
  • 36. 36 Below an example of how data manipulation can support our hypothesis Revenues by years In M USD 100 150 90 80 200 300 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Revenues by years In M USD Wrong graph Correct graph 100 150 90 80 200 300 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Message: The revenues have increased in recent years
  • 37. 37 Let’s see how message that is inconsistent with data may be confusing for data interpreting Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that support the hypothesis Message inconsistent with data
  • 38. 38 Below an example of message that is inconsistent with data 320 100 80 300 290 295 Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Sales by months In thousands of EUR Message: A slight decrease in sales in months 2 and 3 was caused by some problems with the availability of products at the manufacturer
  • 39. 39 Below an example of message that is consistent with data 320 100 80 300 290 295 Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Sales by months In thousands of EUR Message: A large drop in sales in month 2 and 3 was caused by big problems with the availability of products at the manufacturer
  • 40. 40 Below some of the ways, in which they may try to influence you with the charts Adjust axes to make difference look smaller or bigger Trendlines Choice of units Choice of colors Select the period that supports the hypothesis Message inconsistent with data
  • 41. 41 Check the video on YouTube for more details Click here to go to the video
  • 42. 42 What is a good chart
  • 43. 43 Now let’s see when can we say that the chart is a good one Consistent with message Clear easy to read The right type With properly defined color coding Adjusted to the audience Has an Excel to support it With proper units Don’t manipulate the audience
  • 45. 45 Create a structure of the presentation Write down the messages you want to convey Sketch the slides Create a template in Power Point For every slide create the underlying analysis or gather needed info Check for errors, mistakes and omissions Write the beginning and the end of the presentation Create Executive Summary Check the flow of the whole presentation and modify if needed slides or the structure Fill in the slides with data and charts Just as a reminder the creation of presentation consists of 10 phases of
  • 46. 46 Create a structure of the presentation Write down the messages you want to convey Sketch the slides Create a template in Power Point For every slide create the underlying analysis or gather needed info Check for errors, mistakes and omissions Write the beginning and the end of the presentation Create Executive Summary Check the flow of the whole presentation and modify if needed slides or the structure Fill in the slides with data and charts The choice of slides is done in the Sketch phase. You may modify the charts later on
  • 47. 47 If we were to take a look only at the process of creating a chart we would have the following sequence Write down the messages you want to convey Decide what type of data you want to show Select the type of chart that suits your needs Input data into the chart Modify or change the type of the chart
  • 48. 48 For more details and content check my online course where you can find case studies showing analyses along with detailed calculations in Excel Data Visualization for Management Consultants & Analysts $190 $19 Click here to check my course
  • 49. 49 Which chart type you should use
  • 50. 50 Which chart type you should use – Introduction
  • 51. 51 Before you decide which chart to choose, it's important to understand why you need one and what story you want to tell your audience.
  • 52. 52 There are 7 main reasons for which we can create a graphical representation of data What I want to show How something has change over time Compare across 2-dimensions different options Compare across 3-dimensions different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference
  • 53. 53 There are 7 main reasons for which we can create a graphical representation of data What I want to show How something has change over time Compare across 2-dimensions different options Compare across 3-dimensions different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference Clustered column chart Line chart Stacked area chart Scatter Chart / Bubble chart Heat map 100 % stacked column 2 Clustered column charts with 1 column 1 Clustered column charts with 2 columns 2 Clustered bar charts with 1 Bar 1 Clustered bar chart with 2 Bars Combo chart with – column and line 3 Clustered column charts with 1 column 1 Clustered column chart with 3 columns Bubble chart 3 Clustered bar charts with 1 Bar 1 Clustered bar chart with 3 Bars Snake graph (Line graph with markers) Radar chart 100 % Stacked column chart 100 % Stacked bar chart Waterfall chart Pareto chart Infographic chart Other Funnel chart Clustered column chart Clustered Bar Waterfall chart Heat map Map with color coding Map + Clustered column chart Regular charts Map + Clustered bar chart
  • 54. 54 There are 7 main reasons for which we can create a graphical representation of data What I want to show How something has change over time Compare across 2-dimensions different options Compare across 3-dimensions different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference
  • 55. 55 How to show that something has change over time
  • 56. 56 Let's see how we can present data that changes over time What I want to show How something has change over time Compare across 2- dimensions different options Compare across 3- dimensions different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference Clustered column chart Line chart Stacked area chart Scatter Chart / Bubble chart Heat map 100 % stacked column
  • 57. 57 Check the video on YouTube for more details Click here to go to the video
  • 58. 58 Clustered columns 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 59. 59 Stacked column with absolute values 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 60. 60 100 % stacked column chart with absolute values 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 61. 61 100 % stacked column chart with percentages 17% 33% 29% 26% 33% 69% 44% 43% 47% 42% 14% 22% 29% 26% 25% Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Share of business units in Total Revenues of a chain of clinics by years In percentage
  • 62. 62 Line chart 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 63. 63 Bubble chart Revenues of a chain of clinics by years and business units In M of EUR 100 400 80 150 200 100 200 300 200 250 450 250 400 500 300 0 1 2 3 4 5 6 Dentists GP Doctors Others Year
  • 64. 64 Scatter chart – same color with labels Revenues of a chain of clinics by years and business units In M of EUR Dentists; 100 GP Doctors; 400 Others; 80 Dentists; 150 GP Doctors; 200 Others; 100 Dentists; 200 GP Doctors; 300 Others; 200 Dentists; 250 GP Doctors; 450 Others; 250 Dentists; 400 GP Doctors; 500 Others; 300 0 1 2 3 4 5 6 Year
  • 65. 65 Scatter chart – different colors with labels Revenues of a chain of clinics by years and business units In M of EUR Dentists; 100 GP Doctors; 400 Others; 80 Dentists; 150 GP Doctors; 200 Others; 100 Dentists; 200 GP Doctors; 300 Others; 200 Dentists; 250 GP Doctors; 450 Others; 250 Destists; 400 GP Doctors; 500 Others; 300 0 1 2 3 4 5 6 Year Dentists GP Doctors Others
  • 66. 66 Scatter chart – different colors no labels Revenues of a chain of clinics by years and business units In M of EUR 100 400 80 150 200 100 200 300 200 250 450 250 400 500 300 0 1 2 3 4 5 6 Year Dentists GP Doctors Others
  • 67. 67 Heat map Revenues of a chain of clinics by years and business units In M of EUR Dentists GP Doctors Others Year 1 Year 2 Year 3 Year 4 Year 5 < 100 100 – 199 200 – 299 300 – 399 400 – 499 400 – 499
  • 68. 68 When it comes to me, in most cases I would use the clustered column chart or the stacked column chart 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Stacked column in absolute values Clustered column
  • 69. 69 How to compare different options across 2 dimensions
  • 70. 70 Let's see how we can present data with 2 dimensions What I want to show How something has change over time Compare across 2- dimensions different options Compare across 3- dimensions different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference 2 Clustered column charts with 1 column 1 Clustered column charts with 2 columns 2 Clustered bar charts with 1 Bar 1 Clustered bar chart with 2 Bars Combo chart with – column and line Scatter chart
  • 71. 71 211 117 200 200 50 Company 1 Company 2 Company 3 Company 4 Company 5 Cost of the project In thousands of USD 36 33 52 52 16 Company 1 Company 2 Company 3 Company 4 Company 5 Time needed for full implementation In weeks 2 Clustered column charts with 1 column
  • 72. 72 211 117 200 200 50 36 33 52 52 16 Company 1 Company 2 Company 3 Company 4 Company 5 Cost of the project vs Time needed for full implementation In thousands of USD & In weeks 1 Clustered column charts with 2 dimensions Cost of project (in thousands of USD) Time needed (in weeks)
  • 73. 73 211 117 200 200 50 36 33 52 52 16 0 10 20 30 40 50 60 0 50 100 150 200 250 Company 1 Company 2 Company 3 Company 4 Company 5 Cost of the project vs Time needed for full implementation Combo chart with – column and line with 2 visible axes Cost of project (in thousands of USD) Time needed (in weeks) In thousand of USD In weeks
  • 74. 74 211 117 200 200 50 36 33 52 52 16 0 10 20 30 40 50 60 0 50 100 150 200 250 Company 1 Company 2 Company 3 Company 4 Company 5 Cost of the project vs Time needed for full implementation In thousands of USD & In weeks Combo chart with – column and line with 2 hidden axes Cost of project (in thousands of USD) Time needed (in weeks)
  • 75. 75 50 200 200 117 211 Company 5 Company 4 Company 3 Company 2 Company 1 Cost of the project In thousands of USD 16 52 52 33 36 Company 5 Company 4 Company 3 Company 2 Company 1 Time needed for full implementation In weeks 2 Clustered bar charts with 1 Bar
  • 76. 76 1 Clustered bar with 2 Bars 50 200 200 117 211 16 52 52 33 36 Company 5 Company 4 Company 3 Company 2 Company 1 Cost of the project & Time needed for full implementation In thousands of USD & In weeks Cost of project (in thousands of USD) Time needed (in weeks)
  • 77. 77 Scatter Chart Cost of the project In thousands of USD Company 1 Company 2 Company 3 Company 4 Company 5 0 50 100 150 200 250 0 10 20 30 40 50 60 Time needed for full implementation (In weeks)
  • 78. 78 When it comes to me, in most cases I would use the 2 Clustered column charts with 1 column or scatter chart 2 Clustered column charts with 1 column Scatter chart
  • 79. 79 How to compare different options across 3 dimensions
  • 80. 80 Let's see how we can present data with 3 dimensions What I want to show How something has change over time Compare across 2- dimension different options Compare across 3- dimension different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference 3 Clustered column charts with 1 column 1 Clustered column chart with 3 columns Bubble chart 3 Clustered bar charts with 1 Bar 1 Clustered bar chart with 3 Bars
  • 81. 81 4,5 3 4 3 2 1 2 Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream Attractiveness of product category (1- Low; 5 – High) 3 Clustered column charts with 1 column Difficulty of implementation product category (1-Small; 5-Big) Potential revenues generated by product category In M USD 3 4 4 5 2 1 4 Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream 100 30 300 30 150 200 150 Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream
  • 82. 82 1 Clustered column chart with 3 columns 4,5 3 4 3 2 1 2 3 4 4 4,5 2 1 4 100 30 300 30 150 200 150 Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream Attractiveness, Difficulty of implementation and Potential revenues generated by product category Attractiveness Difficulty Potential revenues
  • 83. 83 Bubble chart Difficulty level (1-Small; 5-Big) Attractiveness (1- Low; 5 – High) Cottage cheese; 100 Cheddar; 30 Yoghurt; 300 Feta; 30 Yellow cheese; 150 Milk desserts; 200 Ice cream; 150 0 1 2 3 4 5 0 1 2 3 4 5 Potential Revenues In M of USD
  • 84. 84 4,5 3 4 3 2 1 2 Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream Attractiveness of product category (1- Low; 5 – High) 3 Clustered bar charts with 1 bar Difficulty of implementation product category (1-Small; 5-Big) Potential revenues generated by product category In M USD 3 4 4 5 2 1 4 Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream 100 30 300 30 150 200 150 Cottage cheese Cheddar Yoghurt Feta Yellow cheese Milk desserts Ice cream
  • 85. 85 When it comes to me, in most cases I would use the 2 bar charts or 3 Clustered bar charts with 1 bar Bubble Charts 3 Clustered bar charts with 1 bar
  • 86. 86 How to compare different options across more than 3 dimensions
  • 87. 87 Let's see how we can present data that change their composition over time What I want to show How something has change over time Compare across 2- dimensions different options Compare across 3- dimensions different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference Snake graph (Line graph with markers) Radar chart
  • 88. 88 Snake graph (Line graph with markers) Price image for 2 firms In USD 0 20 40 60 80 100 Regular price level Promotions / Discounts Price emotional impact Assortment Image Price Fairness Value for money level Consitency of price strategy Price Transparency Firm A Firm B Importance of specific criteria % of people that thought that criteria is the most important 25% 19% 12% 10% 10% 10% 9% 5% Regular price level Promotions / Discounts Price emotional impact Assortment Image Price Fairness Value for money level Consitency of price strategy Price Transparency
  • 89. 89 Radar Chart 0 20 40 60 80 100 Regular price level Promotions / Discounts Price emotional impact Assortment Image Price Fairness Value for money level Consitency of price strategy Price Transparency Firm A Firm B Price image for 2 firms In USD
  • 90. 90 How to show composition / structure
  • 91. 91 Let's see how we can present data that change their composition over time What I want to show How something has change over time Compare across 2- dimension different options Compare across 3- dimension different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference 100 % Stacked column chart 100 % Stacked bar chart 100 % Stacked area chart Waterfall chart Pareto chart Infographic chart Doughnut chart Tree Map
  • 92. 92 100 % stacked column chart with absolute values 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 93. 93 100 % stacked column chart with percentages 17% 33% 29% 26% 33% 69% 44% 43% 47% 42% 14% 22% 29% 26% 25% Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Share of business units in Total Revenues of a chain of clinics by years In percentage
  • 94. 94 Stacked column chart with absolute values 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 95. 95 100 % stacked bar chart with absolute values 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 96. 96 100 % stacked bar chart with percentages 17% 33% 29% 26% 33% 69% 44% 43% 47% 42% 14% 22% 29% 26% 25% Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Share of business units in Total Revenues of a chain of clinics by years In percentage
  • 97. 97 100% Stacked area chart with absolute values 100 150 200 250 400 400 200 300 450 500 80 100 200 250 300 Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 98. 98 100% Stacked area chart with percentages 17% 33% 29% 26% 33% 69% 44% 43% 47% 42% 14% 22% 29% 26% 25% Year 1 Year 2 Year 3 Year 4 Year 5 Dentists GP Doctors Others Revenues of a chain of clinics by years and business units In M of EUR
  • 99. 99 Waterfall chart 100 400 80 580 Dentists GP Doctors Others Total Revenues of a chain of clinics and business units in Year 1 In M of EUR
  • 100. 100 Infographic chart Share of business units in Total Revenues of a chain of clinics in Year 1 In percentage 17% Dentists 69 % GP Doctors 14 % Others
  • 101. 101 Infographic chart Share of business units in Total Revenues of a chain of clinics in Year 1 In percentage 17% Dentists 69 % GP Doctors 14 % Others
  • 102. 102 Infographic chart Share of business units in Total Revenues of a chain of clinics in Year 1 In percentage Dentists – 17% GP Doctors – 69% Others – 14%
  • 103. 103 Pareto chart 200 190 180 170 166 150 140 135 120 120 110 90 95 80 70 60 50 40 30 10 9% 18% 26% 34% 41% 48% 54% 60% 66% 71% 76% 80% 85% 88% 91% 94% 96% 98% 100% 100% 0% 20% 40% 60% 80% 100% 120% 0 50 100 150 200 250 Client 1 Client 2 Client 3 Client 4 Client 5 Client 6 Client 7 Client 8 Client 9 Client 10Client 11Client 12Client 13Client 14Client 15Client 16Client 17Client 18Client 19Client 20 Average value of annual sales by individual clients In thousands of EUR
  • 104. 104 Doughnut chart Share of Product sales in Total Revenues of a retail company in Year 1 vs Year 2 In percentage 10% 12% 24% 6% 18% 19% 11% 12% 14% 28% 7% 19% 15% 5% Product 1 Product 2 Product 3 Product 4 Product 5 Product 6 Product 7 Year 1 Year 2
  • 105. 105 Doughnut chart Sales and Margin of the following products In percentage 10% 12% 24% 6% 18% 19% 11% 5% 11% 43% 10% 12% 12% 7% Product 1 Product 2 Product 3 Product 4 Product 5 Product 6 Product 7 Margin Sales
  • 106. 106 When it comes to me, in most cases I would use the 100 % stacked column chart or waterfall chart 100 % stacked column chart Waterfall chart
  • 107. 107 How to show funnels
  • 108. 108 Let's see how we can present funnel analysis What I want to show How something has change over time Compare across 2- dimensions different options Compare across 3- dimensions different options Compare across more than 3 dimensions Composition Funnel Analysis Local differences Funnel chart Clustered column chart Clustered Bar Waterfall chart Heat map
  • 109. 109 Conversion rate 100% 85% 73% 87% 70% 64% Number of customers who, after clicking on an advertisement of the app, became its users In % Funnel chart
  • 110. 110 Funnel chart using shapes Click to the add Visit app store website Run the app Download and install app Fill in registration data Complete registration 100% 85% 62% 54% 38% 24% % of initial Group Conversion rate 100% 85% 73% 87% 70% 64% Number of customers who, after clicking on an advertisement of the app, became its users In %
  • 111. 111 Clustered column chart 20 18 14 7 3 Start session Product viewed Add to cart Registered Purchase Funnel Analysis of customers who decided to book a hotel online In millions
  • 112. 112 Clustered bart chart Funnel Analysis of customers who decided to book a hotel online In millions 3 7 14 18 20 Purchase Register Add to cart Product viewed Start session
  • 113. 113 Waterfall chart Funnel Analysis of customers who decided to book a hotel online In millions 20 2 18 4 14 7 7 3 3 Start session End session Product viewed Product abandoned Add to cart Product not added Registered Not registered Purchase
  • 114. 114 Qualify Leads Create Demand Negotiate the contract Sign the contract Up-sell Heat map  Retail Industry 30% 30% 30% 40% 50%  Health Industry 80% 60% 40% 20% 50%  Financial Industry 10% 70% 40% 25% 30%  Technology 30% 20% 80% 80% 70% Sales funnel by cohorts using color coding In %
  • 115. 115 When it comes to me, in most cases I would use the 100 % stacked column chart or waterfall chart Clustered bar chart Waterfall charts Heat map charts
  • 116. 116 How to show local differences
  • 117. 117 Let's see how we can present local differences What I want to show How something has change over time Compare across 2- dimension different options Compare across 3- dimension different options Compare across more than 3 dimensions Composition Funnel Analysis Local difference Map with color coding Map + Clustered column chart Regular charts Map + Clustered bar chart
  • 118. 118 Map with color coding – PowerPoint map Shares of sales of cosmetics products in following countries In % 100% Shares of sales : 74% 31% 26% 85% 14%
  • 119. 119 100% Shares of sales : Map with color coding – map made out of shapes 74% 31% 26% Shares of sales of cosmetics products in following countries In % 85% 14%
  • 120. 120 PowerPoint Map + Clustered column chart Shares of sales of cosmetics products in following countries In % 100% 85% 74% 31% 26% 14% Poland United Kingdom Germany France Spain Italy
  • 121. 121 Map made out of shapes + Clustered column chart Shares of sales of cosmetics products in following countries In % 100% 85% 74% 31% 26% 14% Poland United Kingdom Germany France Spain Italy
  • 122. 122 PowerPoint Map + Clustered bar chart Shares of sales of cosmetics products in following countries In % 100% 85% 74% 31% 26% 14% Poland United Kingdom Germany France Spain Italy
  • 123. 123 Map made out of shapes + Clustered bart chart Shares of sales of cosmetics products in following countries In % 100% 85% 74% 31% 26% 14% Poland United Kingdom Germany France Spain Italy
  • 124. 124 Clustered bar chart Shares of sales of cosmetics products in following countries In % 100% 85% 74% 31% 26% 14% Poland United Kingdom Germany France Spain Italy
  • 125. 125 For more details and content check my online course where you can find case studies showing analyses along with detailed calculations in Excel Data Visualization for Management Consultants & Analysts $190 $19 Click here to check my course
  • 127. 127 Essential Charts in Excel – Introduction
  • 128. 128 Let’s see how you can create fast and efficiently charts in Excel. In this section we will concentrate on some technical tips.
  • 129. 129 In this section we will talk about the following things How to format the chart How to have a one chart with 2 axes Basics of creating a chart in Excel How to reverse the order of data in the chart How to reuse formatting from previous charts Bar chart with different colors How to add total for stacked column charts How to highlight specific periods on the chart How to create more complicated charts
  • 130. 130 Check the video on YouTube showing how to create a waterfall chart Click here to go to the video
  • 131. 131 How to create more complicated charts
  • 132. 132 Sometimes you will want to create more complicated charts that you cannot do directly in Excel. I will show how to find a way around
  • 133. 133 In the next lectures we will have a look at 2 case studies Waterfall Charts showing potential stores Scatter Charts with labels showing new products
  • 134. 134 Check the video on YouTube showing how to create a waterfall chart Click here to go to the video
  • 135. 135 Check the video on YouTube showing how to create scatter plot with labels Click here to go to the video
  • 137. 137 Data Visualization using CF – Introduction
  • 138. 138 For data visualization you don’t have to use charts. In some cases conditional formatting does a great job. In this section we will discuss it in practices
  • 139. 139 In this section we will talk about the following things Charts using conditional formatting Heat Maps using conditional formatting Basics of Conditional Formatting Sparklines
  • 140. 140 How to create charts in Power Point
  • 141. 141 How to create charts in Power Point – Introduction
  • 142. 142 Let’s see how you can create fast and efficiently charts in Power Point. In this section we will concentrate on some technical tips.
  • 143. 143 In this section we will talk about the following things How to make the chart look nice in Power Point Library of formatted charts Basics of creating a chart in Power Point Chart Animation
  • 144. 144 Check the video on YouTube for more details Click here to go to the video
  • 147. 147 Pivot Charts are great tools that will help you with data visualization. In this section we will have a look how to use them in practice.
  • 148. 148 In this section we will talk about the following things Combining slicers with Pivot Charts Building a Dashboard Pivot Charts Example Online store-checks – Case study using Pivots Look & Feel of Pivot Chart Using Customer reviews – Case study using Pivots
  • 150. 150 In many cases you will have to do not only store checks in physical stores but also in online stores. We will discuss this subject in this lecture.
  • 151. 151 Before going deeper into this lecture I would recommend revising the lecture on offline store-checks Offline store-check
  • 152. 152 In the online store checks you can compare different types of stores Compare different online stores Compare offline to online for the same brand Compare offline to online for different brands  For example H&M online to Zara online  For example H&M online to H&M offline  For example H&M online to Zara offline  Understand difference in product range and pricing used in the online world  Understand difference in product range and pricing policy used by the same brand in offline and online worlds.  Do they have the same policy or they use different sets of rules for the online and offline world  You want to compare 2 brands  For one of them you don’t have the offline data i.e. from another country. In this case you can use the online data as a proxy to make the comparison.  This will require adjustments so you can trulely ompare the 2 brands Compare different offline stores  For example H&M offline to Zara offline  Understand difference in product range and pricing used in the offline world Example Purpose
  • 153. 153 Below the main methods you can use to do the online store-check Create a script to automate the process Use data scraping tools Do the store-check manually Buy data from the 3rd party Use the API or ask for data the provider
  • 154. 154 Online store-checks – What information you gather
  • 155. 155 During online store-check you most likely will be gathering the following information Name, photos of the product & assigned categories Prices of specific products Available quantity # of reviews Rules for organizing data on the webpage Rules for presenting data Additional information on the availability in offline stores Discounts on the product
  • 156. 156 Online store-checks – Case Introduction
  • 157. 157 Let’s see how you can use the online store-checks to analyze the market. This time around we will do a store-check for cosmetics
  • 158. 158 A few information about what you have to do You will concentrate only on cosmetics for the face You have data on 200 SKUs You have information on the brand, price, group, size Analyze the data from the online store-check
  • 159. 159 Using customer reviews – Introduction
  • 160. 160 The information from customers is extremely important. Nowadays we have plenty of sites that gather customers reviews. We will discuss how you can use them in market research
  • 161. 161 Below a short summary of what you can learn from sites with review What customers pay attention to Customer Segments What current players are good at What current players don’t do too well You can estimate NPS (Net Promoter Score) You can check how popular certain brands / solutions are In some cases you can contact the reviewer You learn the language used by the customers
  • 163. 163 Below some examples where you can find customer reviews SaaS Products Restaurants / Hotels Local Services  G2  Trust Radius  Software Advice  GetApp  Founder Kit  AppBot  Yelp  TripAdvisor  Airbnb  Booking.com  DoorDash  Yelp  Google Reviews  Facebook Reviews  Task Rabbit Consumer Goods  Amazon  Walmart  Best Buy
  • 164. 164 Using Customer reviews – Case Introduction
  • 165. 165 Imagine that you were hired by a firm to analyze the emailing software market and to tell them whether there is a niche for them to create a new product. Use the customer reviews
  • 166. 166 A few information about what you have and what are your goals You decided to concentrate on the Mailchimp customers Your boss proposed to concentrate only on the users that have 3 stars You have gathered data from 900 users by data scraping Propose on which aspect they should concentrate
  • 167. 167 Sites for comparing products – Introduction
  • 168. 168 One of the ways to understand the market and competitors is to try and compare products especially from different firms. You can do that using comparison tools / sites
  • 169. 169 Below a short summary of what you can learn from comparison sites How popular specific product is To what extent products differ in terms of features / characteristics What customer segments do they target Pros and Cons of each and every solution How widely specific products are used Pricing and sales strategy Customer support offered Links to other products / Product Ecosystem
  • 170. 170 Below some examples where you can find product comparison Some Review Sites Sites dedicated to comparisons Other  G2  Trust Radius  Software Advice  GetApp  Comparison done by influencers  Product Rankings Reddit  Quora E-commerce / Marketplaces  Amazon  Best Buy
  • 172. 172 Dynamic Charts in Excel – Introduction
  • 173. 173 In some cases you will want to make your charts more dynamic so it can readjust to changes in parameters or questions asked. I will show you how you can achieve it in Excel.
  • 174. 174 In this section we will talk about the following things Dynamic Charts using VLOOKUP & MATCH Dynamic Charts using SUMIFS Dynamic Charts using Pivot Charts How to add new data to the chart automatically
  • 176. 176 Advanced Charts in Excel – Introduction
  • 177. 177 In 80% of the time you will be using simple charts similar to what we have shown so far. Now we will have a look at some interesting charts that are less frequently.
  • 178. 178 In this section we will talk about the following things Maps Tree Maps Pareto Chart Doughnut Charts Funnel Charts Box & Whisker Chart
  • 179. 179 For more details and content check my online course where you can find case studies showing analyses along with detailed calculations in Excel Data Visualization for Management Consultants & Analysts $190 $19 Click here to check my course
  • 181. 181 Essential Excel for Business Analysts and Consultants A practical guide presentation Check also my other presentations
  • 182. 182 Retail for Business Analysts and Management Consultants A practical guide presentation Check also my other presentations
  • 183. 183 Strategy for Management Consultants & Business Analysts Practical Guide presentation For more information on Strategy check also my other presentation
  • 184. 184 How to solve problems like Management Consultants Practical Guide presentation Check also my other presentations
  • 185. 185 KPIs for Management Consultants & Business Analysts Practical Guide presentation Check also my other presentations