My Journey to Become an Analytics Professional


In this blog I will describe how my MSBA practicum project has strengthened my knowledge of analytics by giving me the opportunity to leverage data and make business decisions. In particular, I will talk about how working for Packsize has taught me some fundamental principles that I will adopt in my business analytics career.

In addition, I will outline the greatest lessons learned throughout my practicum project and how these have helped me build a solid basis to become an analytics professional. Specifically, I will describe three of the most important analytical skills I have learned:

1. Clearly defining a Business Goal

2. Effectively selecting KPIs

3. Storytelling using data

Project Background

Packsize is a packaging machine manufacturing company that aims to reduce material waste and costs by providing right size packaging. Packsize recently acquired Aquifi which is a company that manufactures and builds 3D cameras that can gather product attribute information (e.g. color, shape, size). Packsize tasked me and my team with finding innovative ways to integrate the new camera technology in warehouse operations with the goal of further optimizing packaging efficiency within warehouses.

Business goal

When my team and I first began working on this project we had some trouble understanding exactly what the client (Packsize) was asking us to accomplish. We understood that the broad scope of this project was to apply the newly acquired technology to design a process that would leverage the use of Aquifi cameras to optimize warehouse operations. During our meetings each team member had a slightly different understanding of the project’s goal. After repeatedly scheduling internal meetings and brainstorming ideas to accomplish what we thought Packsize’s project goal was, we decided to pause and come up with a more strategic plan. Eventually, we realized the key was not only understanding how Aquifi could be used, but it was essential to understand how our project could advance and strengthen Packsize’s mission as a whole. As a matter of fact, the company’s mission is to minimize packaging size resulting in a reduction of material waste as well as shipping cost savings. Keeping this greater goal in mind allowed us to define a much clearer path, allowing us to start from the company’s overall mission and working backwards.

The main take away I took is that there are two major components involved when solving a business problem:

1. Clearly understanding the product/project’s technical capabilities and limitations

2. Determine how the product/project ties into the broader company’s mission. During this stage key questions should be asked in order to understand business pain points and generate viable solutions

Finally, after adopting the “start from the company’s mission and work backwards” method, we were able to define our business goal:

Using Aquifi’s 3D cameras to automatically inspect items’ attributes (e.g. liquid, fragile, hazardous etc.) in order to optimize the pre-packing process.

The pre-packing process is defined as the process of using additional material to protect an item from getting damaged during shipping. For example, a fragile item can be prepackaged by using bubble wrap and a liquid item by wrapping it with plastic.

Optimizing the inspection process would allow to reduce labor costs, since the inspection is currently performed manually by an operator, as well as increase the number of throughputs per day (that is, the number of items pre-packaged in a day).


After clearly defining the business goal, the next crucial step was to understand what metrics needed to be tracked to determine whether our solution provided value to the customer. In my experience, I found that the best way to measure success was to work closely with the client to select key performance indicators (KPIs). Part of the confusion in defining a clear business goal, described in the previous section, came from the fact that our team attempted to define KPIs independently from the client. For example, our team’s initial target was to reduce material waste and minimize product damage. However, after presenting these findings to Packsize, they proposed thinking about the key metrics in a different way. They recommended that more savings were actually generated through increasing throughput and decreasing labor costs. Having this perspective allowed our team to revise our choice of KPIs.

KPIs became the main drive in my teams’ creative thinking and allowed us to effectively track how much value the new camera technology would bring to the table. I was fascinated by seeing how our early assumptions led to confusion and delay in delivering a solution. Ultimately, I learned the importance of defining the right metrics in the early project stages, which allows to allocate resources much more efficiently.


Another challenging aspect of our project was to effectively communicate our project progress with Packsize to ensure that we were keeping up with their expectations. That is when I understood how important it is to narrate the project status using a compelling story in order to convey a clear message.

As the “Team Communicator”, I was in charge of communicating progress to the client in our weekly meetings. This was a great opportunity for me to learn how to leverage data to influence an audience. As described in Cole Nussbaumer Knaflic’s book “Storytelling with Data”, narrating a story by effectively leveraging data not only requires having knowledge on the audience’s background, but it also involves presenting ideas and key findings in a “clean” way by showing graphs and spreadsheet with as little cluttering as possible. Starting off my weekly update with a brief overview and summary of the meeting’s agenda was also another great strategy that I learned by reading Knaflic’s book.


This practicum project has given me the opportunity to leverage data to make effective business decisions. Working on this project helped me understand the importance of focusing on three main components whenever solving a business problem using data:

1. Defining a clear business goal by starting from the company’s mission and working backwards

2. Developing KPIs to measure success and track improvement

3. Storytelling with data by understanding the audience’s background and presenting findings in a concise and clean way



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