A Young Professional’s Guide to Data Presentation

By: Vanda Ametlli, Henry Ford Health System, IIE Great Lakes Regional Vice President

Growing up with a father who was an engineer, I always knew that I wanted to follow in his footsteps. There was no
question. It wasn’t until middle school that my fascination with numbers began, which I carried into high school by taking statistics classes as my “electives”. It would have maybe been handy to take one of those cooking classes now that I look back. My past 3 years of industrial engineering experience in manufacturing, academic research and healthcare have been a great reinforcement that data is a powerful agent that drives decision making and ultimately changes processes for better outcomes.

As young professionals, one of the challenges we are faced with is presenting data to staff and upper management in a way that is meaningful enough to empower them to take action. While, as we advance into our careers, we’ll strengthen our skills and aptitude to present data to our stakeholders, here are some tips that I have learned and use them as my checklist to consider when presenting data.

1. Understanding Data – I recall an undergrad project in my Numerical Methods/Matlab course that focused on Predator-Prey models. The technical outcomes of the project tested our ability to solve non-linear equations and applying differentiation to understand how ecosystems work. The most beneficial outcome out of that project, however, was the ability to use “understanding” of predator-prey-scavenger interactions beyond the equations and
data. You couldn’t just put in random numbers for Newton-Raphson to see outcomes of changing different parameters such as prey rate. No matter if you’re in a strictly data analyst role or industrial engineer, take the time to understand the data you analyze. If geography allows, ask to go to a site visit to see the process in action or seek out individuals that are process experts. If needed, go beyond the scope of your data to understand any interactions that impact results. When dealing with complicated data, draw a framework of all inbound/outbound means in which the data comes from. This not only helps establish a good foundation but allows for someone new to the process to easily analyze the data. Taking measures to understand the data not only adds credibility but gives you the confidence to
present it to stakeholders!

2. Audience – No matter what industry you come from, knowing your audience is crucial. Knowing your audience takes a lot effort. When presenting data, it is so important to dig deep and find out the background of your stakeholders. A lot of this background is tied in within an organization’s culture. Ask yourself questions such as “How does this manager use data in their department”. Some leaders rely heavily on data and some not as much. Finding out why they do not rely on data is just as important. Many times, managers and leaders are provided with so much data that it becomes overwhelming due to poor presented data or misleading data. That organizational culture plays a role since it drives how staff,managers and leaders view and react to data. If you are in a small organization where you are tasked with developing metrics and dashboard use this is an opportunity to develop a data driven culture. The biggest advice to knowing your audience all boils down to not making any assumptions. As IEs, we like to think everyone knows what mean/median but even “simple” descriptive statistics might not have been used by your collagues in a while. While, you might not get it right the first time, it is important that you modify presentation of your data in the future to take into consideration the statistical and technical background of your audience. Going back to point 1, don’t assume that your audience fully understands the process on how your data especially if you’re dealing with high-level leaders that might not be as involved in all the operational details.

3. Method of Presentation – I always have associated the word “creative” with being “artsy” and making pretty floral arrangements, being a really good painter/drawer and creating objects out of recycled materials and etc. Through my young professional journey, I have learned that creative does not necessarily have to be any of those mentioned items. As engineers, we have the opportunity to be creative in our problem solving and presentation of work and especially as IEs, where we are in a role where we need to “sell” stakeholders our ideas. Knowing your audience drives how you present data. While, electronic means such as powerpoint, excel, pdf and etc. are great, don’t be afraid to go outside the box! Use a posterboard or some type of communication type board to convey statistics. Relate to the culture of the department. Make it pretty! This might seem as non-traditional way but what better way to not only make the data of your department/team visible to all staff and leaders but it provides great accountability (My Lean professor should be so proud of my Visual Management application). Take time to think on what the best method to present your data is by taking into account frequency, audience and level of summary that you are presenting.

4. Reporting
a. Summary: Averages – I don’t think, I have ever met someone that doesn’t like averages. Who doesn’t? Averages are easily understood and they always made me feel better on Chemistry grades. I did better than the average! That’s what matters! While averages establish a baseline measure they can be misleading based on your data set. Go beyond the averages. Think in terms of percentiles. Engage your stakeholders early on and establish goals that center around percentiles. If you veer off from a traditional measure such as an average to percentiles make sure that
your audience understands percentiles. Make sure you understand type of statistics you are using! Don’t assume!

b. Times/ Financials – Dealing with dollar amounts (positive/negative) and time (hours/dates/years) can sometimes be tricky when analyzing in Excel. As simple as these sounds make sure your data is presented in a clean manner that there is no confusion on your analysis.

c. Operational Definitions – It is so important that not only you as the data expert understand the operational definitions but your stakeholders also are aware of what is used as the start/time of the process. These are so important especially when you’re measuring/tracking a measure that is to be compared against national benchmarks. When doing literature research or talking to peers in your industry always ask of their operational definitions. Different factors influence the start/end of process.

d. Outliers – We all like our data to be “nice and clean”. Outliers are a fact of life. How we deal with them though makes a huge difference. Early on, when I started doing data analysis, I always felt “guilty” whenever I removed outliers. Do your homework on the outlier! Make sure that it is statically an outlier but find out “causes” why it was an outlier. Was it due to a user error? Simple data entry error? Power outage? And etc. Be prepared if your stakeholders ask you about outliers. Many times they will!

5. Double Check – Sometimes, we are so excited that after working “so hard” on cleaning up the data, analyzing and making it all nice looking that we forget to pause and see if it makes sense! Give yourself a small break and before preparing to submit or present to a group, check that the data logically makes sense!

6. Empowerment – Numbers are so fascinating because they can empower people to take action. Use your data analysis/presentation strategy to empower your stakeholders to take action. Believe in your cause and it will show through. Of course, experience will only make you better at empowering your audience but being proactive and taking small steps can only benefit you.

7. Beyond the numbers – At the end of the day, it is important to remember that number are much more than numbers. The numbers we might deal with might impact people’s futures. Understand not only the local but global impact the data you’re dealing with has. Be prepared to discuss alternatives. After all, data is only a tool that allows us to drive decision making and empower leaders to take change.

What are some of your tips that you have used? Do you have a strategy that you use? What do you see
some challenges when presenting data? What recommendations do you have for young professionals?