Interesting insights about LEGO® across 53 years (1970 - 2022)

Tools used in this project
Interesting insights about LEGO® across 53 years (1970 - 2022)

LEGO dashboard

About this project

  • Objective: The dashboard is designed for general audiences who are keen on LEGO and want to discover the transformation of LEGO’s product segmentation for over 53 years (1970 - 2022), or for those who are simply interested in history or games (or both). In the dashboard, every chart, every text and every button matters. Choose/hover over each one to explore. Leg Godt (Play well)!

  • What the dashboard covers: The dashboard carries three main parts, equivalent to three colours (red, green and blue):

    • Red: In red, we discover the most general information about LEGO across 53 years (or you can filter for the period you want to dive into):
      • A summary to cover the information of the dashboard as a whole
      • The 4 most holistic numbers of LEGO in the 53-year-journey of transformation
    • Green: In green, we discover the changes in the number of products released and some other products’ details such as the number of pieces, price per one set, and age limit adoption, throughout the chosen period. In each chart, there are dynamic and descriptive titles, subtitles, and texts added to the chart.
    • Blue: In blue, we discover LEGO more vertically by analyzing top categories, top theme groups and top sub-themes. I grouped the years into three bins for better comparison. The bins group logic was based on a significant event of LEGO launching its “Shared Vision” strategy in Oct 2004. Audiences aka customers might also be interested in identifying which products are most suitable and most economically efficient so I put all products on a scale of # of pieces and price. After exploring the interesting insights about LEGO, it’s time for the audiences to surf for their best sets based on their preference of age, price, and theme. I placed the image and link to the website for further product details.
  • Key insights:

    • Most prominent trends:
      • Over 53 years of development, total annual sets released showed an upward trend, most remarkably from 2005 onwards. Total sets increased 2259% in 2022 after 53 years. The significant growth was achieved by the combined efforts of:
        • LEGO sets were designed to be more challenging with more pieces per common set, together with a higher standard price per set. It also indicated that LEGO offered great variety with remarkable gaps between the highest and lowest number of pieces per set and price per set
        • A customer-centric approach by offering different products to different target groups of audiences. The first set with age limit adoption was in 1975 and 2006-2012 was the period LEGO adopted this strategy most aggressively. The most common age limit in the last 20 years is 6-year-old and the first adult sets (applied for 18-year-old and above customers) were released in 2020
    • Dive into LEGO products more vertically:
      • From 2005 onwards, LEGO transformed its product categories and themes:
        • (1) Categories: from focusing solely 89% on the “Normal” category in 1970-2004, LEGO diversified its portfolio to “Normal” (59%) and “Gear” (27%) in 2005-2010, then to other categories from 2011 onwards
        • (2) Theme Groups: the “Modern day” & “Preschool” theme groups became much less focused over time, while “Miscellaneous” and “Licensed” groups climbed to the top 1 & 2
        • (3) Theme: Across the period, “Gear”, “Duplo” and “Star Wars” were the most popular themes among LEGO sets
      • In case some audiences are curious about which LEGO set is the most economically efficient based on its number of pieces and price, it’s World Map. You can get 47 pieces for just $1. World Map is also the set with the highest price of LEGO ever.
  • Methods: I consider myself a beginner when it comes to making a real dashboard project. I also find myself a bit of a perfectionist. Oftentimes, I spend a lot of time thinking, planning, researching (esp. when you’re a beginner), and trying to make a perfect out of something. That is why this time, I decided to take a different approach, better get things done first. Then polish them.

    1. Objective: I narrow down the key audiences of the report and try to be in their shoes to think about what I would like to see in a dashboard with the information provided. I designed a story flow with key indicators and their corresponding visuals with sketches on paper. The sketch is important for me to direct my focus when building the dashboard.
    2. View data and process data where necessary: I took a quick scan on Excel, then decided if any data required cleaning. Also, I viewed each element in the individual column to understand the meaning of each field and its corresponding numbers. As a data analyst, it’s best if you have domain knowledge so that the dashboard built could have valuable insights. For this dataset, I did not do much cleaning and mostly just went with the original.
    3. Place visuals on the dashboard - Better get things done: I worked on two tabs: one is for the official dashboard presentation, and the other is for the testing environment, in case I want to test any DAX measures or any visuals before making it official. As a beginner, there were a lot of things that I would love to deliver to the dashboard, however, I could not due to my limited knowledge and experience. To solve this, I just went with the so-called “ok” version first to have a quick result. Based on this raw version, I added comments to the areas I wanted to work on to make the dashboard more insightful. I googled or asked ChatGPT for the solution to clear each comment, and then to come up with the final version.undefined
  • Opportunity for Improvements:

    • It is best if the data analyst has the domain knowledge so it will assist him/her to 1) clean data more efficiently and 2) drill the most valuable insights. In this dataset, when I viewed the data details, what I observed was the inconsistency of grouping data into theme groups and sub-theme groups. Also, if there were resources to understand the meaning behind that grouping, it would help to effectively present the visuals.
    • The dashboard presents some very intriguing trends, such as the unusual spikes in the number of pieces per set in 2004, and two dips in price per set in 1993 and 2001, which will be elaborated with the help of in-depth qualitative analysis. Taking the financial data of LEGO into account might explain the effectiveness of the “Shared Vision” strategy of LEGO in 2004 and other strategies of LEGO.

Additional project images

Discussion and feedback(3 comments)
Gia Khanh Dao
Gia Khanh Dao
about 1 month ago
Interesting insights Andie! Especially the one on age group distribution. Keep up the good work!

Przemyslaw Grynagiel
Przemyslaw Grynagiel
19 days ago
Great work and really insightful description.
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