VIZLOCK HOLMES INITIATIVE

Empowering communities with data and analytics skills is a multifactorial pursuit.

The needs and expectations vary widely within the same community, with some users showing more interest in technical skills, whilst others are just initiating their journey into the world of data and analytics.

Yet, the ability to question ideas and assumptions rather than accepting them at face value, it’s something that ought to be nurtured in any data and analytics community.

But how can we promote critical thinking whilst driving technical upskill?

Can we marry the two activities into a single initiative?

Yes and Yes; This is where the Vizlock Holmes initiative comes into play. Vizlock is an initiative that not only encourages team work, but also the discovery of the ‘So what?!’ behind the analysis whilst the users increase their technical skills.

How does Vizlock Holmes initiative work?

The initiative consists in one event where users work into small teams and use data to create visualisations according to instructions provided, collating all into an analytics story. This story/ analysis can then be presented as a dashboard, infographic or even a Tableau story.

The instructions, consist in specific asks, leading to the creation of visualisations. By the end of each chart/ visualization, the team should find one insight that will be their clue to be able to formulate what would be the initial question driving all the analysis developed.

In summary, each team is reverse engineering the analysis and insights to get the initial ‘business question/ ask’.

The idea is to heighten the ability to question the data, to look for insights and ultimately understand how to drive the analysis in order to answer each question that evolves from the initial business ask or hypothesis. It is an opportunity to practice storytelling, critical thinking and technical know-how.

Working through an example:

Data - Travel data with the following fields: passengers ; flights details; airport; airline; booking agency; vendor; price; discount; destination; origin

Instructions for Visualisation clues:

1. Please create a visual that shows the sales and profit trend through the years of data

a. Clue: year with more sales is the least profitable

2. Visualise the most popular destination

a. Clue: destination country or city with the majority of flights / sales

3. Show the % sales for the most popular destination in comparison with overall sales

a. Clue: how much of the sales to the most popular destination contribute to the overall sales

4. What is the departure airport with more flights to the most popular destination

a. Clue: specific location that is driving the most sales

5. Show the profits for popular destination vs total profit

a. Clue: most popular destination driving the lowest profit

6. Which airline fly the most to the most popular destination

a. Clue: Is the sales driven by different airlines or a single airline

7. Who are the ‘most loyal/ best’ customers

a. Clue: Identification of people that bought the most tickets/ flights

8. What are the sales and profit for the ‘most loyal/ best’ customers

a. Clue: Comparison with other customers; more sales but less profit

9. Please add discount to the previous visual

a. Clue: discount driving the poor profit

10. Visualise the agency where the ‘most loyal/ best’ customers purchased their flights

a. Clue: identifies if they use only one agency or more

11. Which vendor did the ‘most loyal/ best’ customers used

a. Clue: identifies if several vendors or just one is driving the loss of profit

12. What is the surname of the vendor/s and respective customers for the ‘most loyal/ best’ customers

a. Clue: vendor and top customers with same surname

Clues summary: The year with most sales is the least profitable. For that year, the most popular destination was x that drove a x% of sales. At the same time, this destination was the one with least profit, with x amount of airlines flying there, but only one agency supplying flights to that destination.

The best customers were x, y and z and all those sales drove really low profit, due to high discounts, applied by the same vendor in all the sales. Coincidentally this vendor has the same surname as the majority of the ‘most loyal/ best’ customers.