Data Story-Telling: Telling Your Story Through Data Analytics

1 year ago SETHA THAY 1793

In this blog post, we are going to introduce you to an example of data story-telling. Data Story-Telling is a methodology to present a story by analyzing data as proof to support your story. The proof of story can be a dashboard, graph, or any visual to easily for judgment.

HYPOTHESIS

Imagine that you are an IT manager. Your team receives tickets, or technical issues, from employees. In May last year, there were two people quitting your team. You have heard complaints from the remaining employees about doing more work.

You are wondering if you should hire more people. First, you want to understand what impact the departure of employees has had on your team's overall productivity. You plot the monthly trend of incoming tickets and those processed over the past year. You see that there is some evidence your team's productivity is suffering from being short-staffed and now want to turn the quick-and-dirty visual you created into the basis for your hiring request.

1. Revise your IT-ticket visual to meet the objective in the above-mentioned scenario.
2. Construct your story's target and storyline.
3. Present your result in a storytelling manner.

Dataset

Ticket Type	Month	Number
Received	January	160
Received	February	184
Received	March	241
Received	April	149
Received	May	180
Received	June	161
Received	July	132
Received	August	202
Received	September	160
Received	October	139
Received	November	149
Received	December	177
Processed	January	160
Processed	February	184
Processed	March	237
Processed	April	148
Processed	May	181
Processed	June	150
Processed	July	123
Processed	August	156
Processed	September	126
Processed	October	104
Processed	November	124
Processed	December	140

EXPERIMENT

We can do an experiment on the above hypothesis which will describe below:

TARGET

Audience: IT Director, HR Executive, Board of Directors
Objective: Request to hire more staff to boost the work productivity
Evidence: Demonstrate the proof of the monthly trend of received and processed tickets with a chart

STORYLINE

Step	Outlines
Context	We at the IT department observed a pessimistic effect of employee resignation (2 staff) and complaints from other employees due to task overload in May last year We literally want to deliver tasks on time to meet the deadline and obtain achievement
Obstacles (Challenges)	Staff feel unsatisfied and lack motivation toward their career Impact overall work productivity, tasks overdue, no achievement
Struggle (Conflict)	We were delighted trying to solve this issue to encourage staff to gain more work productivity We thought about recruiting more employees in order to support daily task operations We want to understand the impact of departure staff on the overall productivity To test whether we could identify the issue or not, we decided to plot the monthly trend of received and processed tickets over the past year
Resolution	The result showed that there was a discrepancy starting from June (June to July displays a small discrepancy, Aug and Dec shows a big discrepancy) As per observation from Jan to May, we could be able to process 910 out of 914 tickets which is equivalent to 99.56% (Processed), 0.44% (Remaining) However, from Jun to Dec, we could only process 923 out of 1120 tickets which is equivalent to 82.41% (Processed), 17.59% (Remaining)
Lessons / Recommendation Actions	The chart illustrates the actual amount of processed tickets compared to received tickets. Provide benefits/rewards and certificate of appreciation Please kindly approve the request to recruit more staff to enhance the overall work productivity, support daily operations, and meet the expected deadline for all related tasks

MONTHLY TREND OF RECEIVED & PROCESSED TICKETS

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About author

SETHA THAY

Software Engineer & Project Manager. I am willing to share IT knowledge, technical experiences and investment to financial freedom. Feel free to ask and contact me.