How to write a data-driven resume
As business professionals, we know the increasing importance of data-driven decision making in our projects and operations.
This article will explain why we need to bring that same approach to resume writing, and how to level up your Project Manager/Business Analyst resume writing skills.
The importance of data
In the business world today, it is hard to come by important decisions that are made in the absence of data to support them. Managers are, understandably, loath to not have evidence stacked up to support a claim or decision that exposes their organization to opportunity, but also risk.
This same perspective can be applied to hiring decisions as well. Are not employees a huge opportunity, albeit potential risk, for any business? A star employee can transform an organization for the better, resulting in a strong bottom line and happier customers. In a competitive job market, candidates need to sell their attributes and accomplishments to hiring managers, who increasingly need to base their hiring decisions on strong evidence, not unlike other operational or project decisions. Show me the data!
What does this mean for your resume?
For one, your resume needs to be quantitative. Most resumes list work experience and education in a neat table, sorted by date and organization. This is a good start. However, when you drill down into the details (the bullet points) underlying each previous job, the descriptions often leave something to be desired. For example;
- “Compiled project analysis for company executives”
- “Managed an organization-wide ERP solution implementation”
- “Trained support teams on use of new software tool”
What these examples demonstrate is a lack of volume, scale, or size. How is a hiring manager to know if you managed the roll out of an ERP system for a staff of 10, or 2000? What does improved service delivery really mean? That each agent more consistently said thank you at the end of each call? Or were turnaround times reduced by 30%? Look for your ‘wins’ and highlight them with data.
What this can look like:
- “Comprehensively analyzed and compiled dozens of address, routing, and fuel data points on a weekly cadence, to draft executive reports that could be quickly understood and acted upon”
- “Managed a 1 year ERP implementation affecting 900 staff, resulting in time savings of 5 FTEs”
- “Facilitated dozens of training sessions of 5‐25 participants each, achieving an average instructor rating of 4.5/5 from feedback forms”
There are 2 important take-aways from the above examples:
- Fully use the real estate provided to you on the page. Your resume should only be 1-2 pages, so use up that white space as efficiently as possible.
- The examples use specifics that are quantified.
Examples of other metrics you can use:
- $’s spent, saved or earned
- Time taken or time saved
- Cadence or turnaround time of process or task
- # of people impacted, trained or involved
- # of computers/machines updated or provisioned
- Volume or quantity of materials
[widget id=”custom_html-68″]
Is the data impressive enough?
What if the numbers aren’t impressive, you may ask? When providing feedback on resumes, mentees often state they don’t think their accomplishments sound big or important enough if too much detail is given, as if keeping it vague somehow augments their work. If you don’t think an accomplishment is worth quantifying, remember that hiring managers can also revert to the lowest common denominator, if quantities aren’t provided. You may have concurrently managed 10 accounts worth an average of $10,000. In the absence of concrete numbers, a hiring manager may theoretically guess that maybe it was 4 accounts worth $5000 each.
Sometimes, exploring different ways of telling your data story can make your work history sound more effective too. Maybe you successfully negotiated a $100 savings on a monthly vendor contract. That’s great, but maybe you can re-word it as, “Negotiated a 10% savings on a recurring monthly expense, saving $1000s per year”. Explore absolute versus percent versus ratio metrics for each claim, as sometimes one will sound better than the other.
Internal- and external-facing data points
You may notice 2 distinct metrics types, that we can call internal, vs. external. Often, when we are stuck in the weeds of our projects, we only think of our internal metrics. These could include things like # of stakeholders managed, dollars spent, or groups involved. What are often more impactful, in terms of convincing employers of the significance of your work, are metrics that speak to what your project ultimately accomplished; the downstream outcomes. Sometimes, these data points may not be known for months or years. These could include things like # of new clients, # of people trained, or incremental dollars earned or saved, directly due to actions you took while deep in the weeds of your project. Have a think about your last few projects. What were their downstream outcomes?
Quantify your interests
People differ on the utility of a personal interests or extracurricular section of your resume. I’m personally a fan, because hiring managers are hiring people, not robots, and want to know who the person is that they are hiring. Also, hiring managers, like all humans, are subject to nervousness around meeting new people in a formal interview setting. The personal interests section provide great small chat talking points to fill otherwise awkward pauses that can occur before and after the formal questioning part of an interview.
Just like with the other sections of your resume, be specific, and quantified, with your personal life! Instead of;
- “Organizer of musical festivals”, or
- “Love travelling and photography”
you could say
- “Have organized 3 musical festivals with 1000s of participants each”, or
- “Have traveled in 23 countries, and photographed the Taj Mahal to the fish & corals of the Great Barrier Reef”
Final thoughts
Lastly, quantifying your resume is an exercise to perform not only once you are looking for your next contract or job, but on an ongoing basis, so that you can leverage the metrics you have formulated for yourself in conversations and informal networking chats.
Good luck on your next application!
LSM99 กีฬาออนไลน์ แทงบอลออนไลน์
… [Trackback]
[…] Find More here on that Topic: projecttimes.com/articles/how-to-write-a-data-driven-resume/ […]
https://www.dallasnews.com/marketplace/2023/09/29/phenq-reviews-legit-diet-pills-or-fat-burner-scam/
… [Trackback]
[…] Find More on that Topic: projecttimes.com/articles/how-to-write-a-data-driven-resume/ […]
ทางเข้า lsm99
… [Trackback]
[…] Info to that Topic: projecttimes.com/articles/how-to-write-a-data-driven-resume/ […]
Bk8
… [Trackback]
[…] Find More on that Topic: projecttimes.com/articles/how-to-write-a-data-driven-resume/ […]
sites
… [Trackback]
[…] Here you will find 82078 more Information on that Topic: projecttimes.com/articles/how-to-write-a-data-driven-resume/ […]
faceless niches
… [Trackback]
[…] Info to that Topic: projecttimes.com/articles/how-to-write-a-data-driven-resume/ […]
micro mini step
… [Trackback]
[…] Read More Info here on that Topic: projecttimes.com/articles/how-to-write-a-data-driven-resume/ […]