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Data Visualization for Management Consultants & Analyst

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Data Visualization for
Management
Consultants
A practical guide on how to show results during
consulting projects

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2
In consulting you will spend a lot of time on creating presentations
to show the results of your analyses to the custome...

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3
That is why, data visualization is so important. With proper display of data you
have more chances of convincing the cus...

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How to show composition /
structure

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Data Visualization for Management Consultants & Analyst

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What is the aim of this course?
In consulting you will spend a lot of time on creating presentations to show the results of your analyses to the customer. 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. In this course I will teach how to use different data visualization techniques to show the results of your analyses during consulting projects.
In the course you will learn the following things:
1. What types of slides you should use to present your thoughts
2. What types of charts you should use for data visualization
3. How to read the charts
4. How to create charts in Excel
5. How to create charts in PowerPoint
6. How to create dynamic charts in Excel

For more check the following course
https://bit.ly/DataVisualizationMC

What is the aim of this course?
In consulting you will spend a lot of time on creating presentations to show the results of your analyses to the customer. 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. In this course I will teach how to use different data visualization techniques to show the results of your analyses during consulting projects.
In the course you will learn the following things:
1. What types of slides you should use to present your thoughts
2. What types of charts you should use for data visualization
3. How to read the charts
4. How to create charts in Excel
5. How to create charts in PowerPoint
6. How to create dynamic charts in Excel

For more check the following course
https://bit.ly/DataVisualizationMC

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Data Visualization for Management Consultants & Analyst

  1. 1. 1 Data Visualization for Management Consultants A practical guide on how to show results during consulting projects
  2. 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. 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. 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. 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. 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. 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. 8 This presentation will teach you how to use different data visualization techniques on the level of top management consultants
  9. 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. 10 How the course is organized
  11. 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. 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. 13 Types of slides you can use
  14. 14. 14 Types of slides you can use – Introduction
  15. 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. 16 I will show you show you not only charts but other types of slides as well
  17. 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. 18 How to read charts
  19. 19. 19 How to read charts – Introduction
  20. 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. 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. 22 How to lie with charts
  23. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 41 Check the video on YouTube for more details Click here to go to the video
  42. 42. 42 What is a good chart
  43. 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
  44. 44. 44 The process of creating charts
  45. 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. 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. 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. 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. 49 Which chart type you should use
  50. 50. 50 Which chart type you should use – Introduction
  51. 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. 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. 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. 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. 55 How to show that something has change over time
  56. 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. 57 Check the video on YouTube for more details Click here to go to the video
  58. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 69 How to compare different options across 2 dimensions
  70. 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. 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. 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. 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. 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. 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. 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. 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. 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. 79 How to compare different options across 3 dimensions
  80. 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. 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. 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. 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. 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. 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. 86 How to compare different options across more than 3 dimensions
  87. 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. 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. 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. 90 How to show composition / structure
  91. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 107 How to show funnels
  108. 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. 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. 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. 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. 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. 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. 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. 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. 116 How to show local differences
  117. 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. 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. 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. 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. 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. 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. 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. 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. 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. 126. 126 Essential Charts in Excel
  127. 127. 127 Essential Charts in Excel – Introduction
  128. 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. 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. 130 Check the video on YouTube showing how to create a waterfall chart Click here to go to the video
  131. 131. 131 How to create more complicated charts
  132. 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. 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. 134 Check the video on YouTube showing how to create a waterfall chart Click here to go to the video
  135. 135. 135 Check the video on YouTube showing how to create scatter plot with labels Click here to go to the video
  136. 136. 136 Data Visualization using Conditional Formatting
  137. 137. 137 Data Visualization using CF – Introduction
  138. 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. 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. 140 How to create charts in Power Point
  141. 141. 141 How to create charts in Power Point – Introduction
  142. 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. 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. 144 Check the video on YouTube for more details Click here to go to the video
  145. 145. 145 Pivot Charts
  146. 146. 146 Pivot Charts – Introduction
  147. 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. 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. 149. 149 Online store-checks – Introduction
  150. 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. 151 Before going deeper into this lecture I would recommend revising the lecture on offline store-checks Offline store-check
  152. 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. 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. 154 Online store-checks – What information you gather
  155. 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. 156 Online store-checks – Case Introduction
  157. 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. 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. 159 Using customer reviews – Introduction
  160. 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. 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. 162. 162 Using customer reviews – Source
  163. 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. 164 Using Customer reviews – Case Introduction
  165. 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. 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. 167 Sites for comparing products – Introduction
  168. 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. 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. 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. 171. 171 Dynamic Charts in Excel
  172. 172. 172 Dynamic Charts in Excel – Introduction
  173. 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. 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. 175. 175 Advanced Charts in Excel
  176. 176. 176 Advanced Charts in Excel – Introduction
  177. 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. 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. 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
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  182. 182. 182 Retail for Business Analysts and Management Consultants A practical guide presentation Check also my other presentations
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