I’m currently pursuing a degree in computer science, but I must choose a major soon. I was hoping to obtain some fast advice and thoughts on what major to choose that will be most useful for a future project manager.
The list of majors I can choose from is as follows:
Business Information Systems Management
Artificial Intelligence and Data Analytics
Enterprise Systems Development
Interaction Design
Networking and Cybersecurity
Mathematical Analysis
Operations Research
Statistics
Cybersecurity and Privacy
The business information systems major is where I’d like to concentrate my efforts, but I’m concerned that if I apply to APM programs with well-known technical rigour, like Google, my understanding won’t be technical enough.
Additionally, if you have any examples of courses you took in college that were helpful to you in your role as a project manager, please share them with me. I’ll check to see if there is an elective equivalent.
– Pauline Francis
Discussion
A] Finding a PM position is less about your academic background and more about your creations and improvements. An English major will be a more fascinating candidate than a CS major who knows data analytics but has never launched a product or interacted with customers. The English major’s simple web-based copywriting business will expand to several hundred clients as a result.
PM is not an entry-level position, either. When you really apply, you’ll have reached the point in your work that employers no longer inquire about your educational background.
– Natasha Martin
B] Since you mentioned Google, I’d like to give out some facts about the FAANG:
Facebook has an RPM program… both industries (internal employees, designers, engineers, consultants, investment bankers, etc.) and new grads compete for it and go through the same recruitment process so can be very competitive
Apple – doesn’t hire PMs out of college, they will hire EPM (engineering PMs) out of college but you’ll likely require a technical background
Amazon – only hires MBA new grad PMs
Netflix – doesn’t hire new grads
Google – hires for APM, about ~50 per class, 25 coming from their intern class. Extremely competitive.
As for Uber, Twitter, Lyft, etc. their APM intern classes are about 5-8 new grads.
Compared to the >200 new grad software engineers they hire each every year.
New grad APM recruiting is tough, honestly, there are a lot of very qualified students out there.
If you’re from Australia, Atlassian hires a lot of new grad PMs. Microsoft hires a lot of PMs as well but typically comes from a technical background.
If I were you, I would focus more on completing personal projects and obtaining PM internships while in college and worry less about choosing the correct major. If you’ve completed actual PM internships, you’ll be 100 times more likely to get selected for an APM interview than if you majored in business as opposed to computer science. My involvement in personal projects in college—such as leading teams of engineers and designers to develop an app used by thousands of students—was the reason I was able to secure every PM internship I ever applied for.
Start interacting with PMs in business to determine what abilities you should hone. While you’re still in school, launch a business that fills a need. Attend classes on business and product design (UI/UX).
My recommendation is to pursue a technical major while still making time for extracurricular activities (like starting your own thing and side projects). On-the-job training is available for business skills, agile, metrics, etc. Once you’re employed, you won’t have the time to advance your technical knowledge (take an algorithm class, understand data structures, etc.).
Understanding the technical underpinnings of things will benefit you throughout your career as a PM and open additional options for you (e.g. at places like Google). If you are aware that technology isn’t your strong suit, I wouldn’t worry about it. I wouldn’t stress if you know that technology isn’t your strong suit, but I would focus more on gaining experience and honing your non-technical PM skills (i.e., it will be crucial that you understand product design, comprehend and create UX/UI, have completed your own personal projects, develop your product vision/intuition, etc.).
Make sure you aren’t doing PM because you believe you can’t design or that engineering is too difficult. I believe that a lot of it is occasionally imposter syndrome, and PM can be greatly exalted in the eyes of college students.
Before investing a significant amount of time in pursuing a career in PM, be sure you have a clear understanding of both its advantages and disadvantages. Discuss it with other professionals in the field (not just former interns) to find out what the drawbacks are and whether you’re alright with them.
– Michael Yoffe
C] Wow! I’m so grateful you took the time to write that; it definitely allayed my anxieties. Since I’m still in my first year, I have some time to expand my skill set before I apply for internships or graduate positions. I’ve been attending weekly product networking events, and after doing some internet study and speaking with numerous PMs in person and on LinkedIn, it looks like this would be the perfect profession for me.
I’ll be working as operations and sales intern at a fintech and an EduTech, respectively, starting the next week. Both founders have indicated that there is space to collaborate with the product team, so perhaps this will benefit me when I apply for APM positions in the future. The only organizations that offer APM grad roles locally are Canva and Atlassian, which is why I’m a little hesitant about doing so. It is substantially less technical than their FAANG counterparts, and career advancement and opportunities are also not as strong in comparison, according to some APM/PMs who work at these companies.
However, the issue is that despite searching LinkedIn for months in search of any examples of Australian graduates who had successfully relocated to the US for an APM grad post, I had only found one account, and I was unable to contact that person. As a result, I’m in a bit of a predicament because I’m unsure whether relocation is even an option.
Do I submit an application for the Atlassian APM program, or do I hold off until I can obtain an L-1 Visa to work in the US?
Should I go on an exchange and apply to as many APM programs while I’m there in the hopes of getting a graduate position?
I suppose this all deserves its own conversation, but, yea, I’m currently a little confused.
For our 1200+ analysts, 200+ data scientists, and 300+ machine learning engineers, we built a web app.
It was created for the following reasons and functions effectively as a custom, highly integrated data catalogue:
Using search and browsing features, assist data workers in finding the data they’re looking for fast.
Due to our detailed documentation, which includes other statistics and linkages between data, they are able to not only access the tables and other information but also understand it.
Before they begin requesting or utilizing the data, provide data workers with all the information they want.
Historically, the team has only ever measured:
monthly active users
net promoter score (which is calculated by a monthly survey that goes out to see who’s happy with our app)
I feel like we could get granular into the metrics we report and collect, any ideas?
– Natasha Martin
Discussion
A] Happy to share my thoughts but first what do you feel success would look like for each of the 3 bullets you highlighted? If you asked your users who did each of the tasks above, what would they say if asked did the tool do its job? How do they know it did or did not?
That should be the basis for your core metrics.
You could throw in additional satisfaction tracking similar to how search engines or Ecommerce does it with “did you find what you were looking for?” or “how satisfied are you with your results?”
And MAUs make sense but are users only expected to use them 1x a month? If more often, then you should be tracking that at that granularity: if they should be using it a few times a week, then WAUs, daily DAUs etc.
– Mario Romero
B] Working in a similar space, a SaaS solution provider. We started with simple metrics like “number of searches” but this tends to be “too few are bad, too many are bad”. So, we dug a bit deeper and started to define “positive actions” like clicking a link, exporting data or forwarding an email. These often happen off our platform, but we have used them to define some new features, and map some more granular user journeys in our analytics and some clearer KPIs.
For example, in our research product, we are aiming for an average search-to-click ratio, per session of between 1-5 (every login has a search, and every search has 1-5 results clicked). In our analysis product, we want an average session to data export of 1 within 30mins. In our monitoring tool, we want an average open rate of opened alerts of >2 and a click ratio of 1 (of people who opened an alert, they come back to it at least once, every open leads to a click).
The KPIs above are early hypotheses, so we expect them to be BS. We just like to start with something and prove ourselves wrong. Hope it helps!
– Jesus Rojas
C]
Adoption: monthly or weekly new users, traffic from Confluence links or direct traffic
Activation: time to first search since session start
Engagement: I also liked a suggestion from one of our users, about the search-to-click ratio per session, queries saved via positive actions
Retention: cohort retention in the first week, first 30 days, 60 days, 3 months out – what’s the natural usage pattern of the tool? do you expect to decrease over time because people got access to the data they needed or got familiar with? does it correlate with the number of active projects and new employees?
High-level business impact:
Scale knowledge and cut down onboarding time for new tech employees or new projects.
Or time for insights and discovery and reduce erroneous queries or server costs indirectly and make it easy to migrate?
It could save developer hours and enable data-centric AI… would be more useful if also integrated with data quality or monitoring tool?
Although I am not a technical or data scientist PM, I get the impression that in order to excel in the position, I need to brush up on my math abilities.
I’d prefer to self-train and prepare for processing huge user datasets, but I’m curious if there’s anything else on this topic that others may comment on.
I studied statistics in college and did calculus back in high school, but I don’t recall much of it.
Any recommendations?
– Pouya Taaghol
Discussion
A] I’m only doing math for financial purposes. If something sophisticated is required, there is generally someone else whose duty is to perform certain kinds of math.
Statistics—like the kind used to examine user sentiment and behaviour—have always felt like a missing component in the three PM positions I’ve held. However, management never thought it wise to have that level of consumer understanding in my responsibilities. It was nearly always what I refer to as “product management by ego” in this sense.
– Maria Wilson
B] @PouyaTaaghol, I’ve read Data Smart, it’s ok and probably more advanced than you’ll need unless your shop is ridiculously lean.
You’re ahead of the game if you know how to handle strings, write nested if statements, and count, sum, and sum products.
Nowadays, I prefer using sheets over older versions of Excel because it’s simpler to collaborate with others and some of the “magic” capabilities operate much faster.
– Priya Verma
C] Why do you think you need to improve your math abilities?
Are there particular requests that you get into trouble answering?
For what kinds of goods do you work as a PM?
Which types of datasets are you able to analyze?
I mostly use accounting-related math for business cases on a daily basis, such as GTM revenue ramps, cost analyses, ROI calculations, and pricing calculations.
In the past, I examined sizable datasets that documented user behaviour to learn more about their routines and usage patterns. Basic statistics like mean, median, mode, and standard deviation were helpful in this, as well as research statistics like ANOVA, f-tests, and z-tests.
Erlang equations were helpful for capacity planning in an application I worked on for contact centres.
In the era of AI and ML, it may also be helpful to comprehend more intricate ideas. According to my assessment, it differs depending on your sector, product, and PM role focus.
I might be able to offer more specific suggestions if you give me some responses to the aforementioned questions.
Confusion increases when people start talking about strategy and tactics. Due to rising uncertainty, some businesses have rejected strategy entirely as they equate strategies with plans and they know plans don’t survive first contact with reality. Therefore they focus rigorously on tacticsinstead, which they usually understand to mean ‘doing things quicker’.
I’ve used this mapping technique in government right since the beginning of my government work in early 2013, helping many programmes to identify better goals and generate better options for achieving those goals. Impact Mapping always delivers something of value.
There are several ways to eliminate fire fighting, but as with any other problem, the first step is to recognize that you have it. Therefore, the first significant step towards progress is the moment the management of the company acknowledges it and decides to make it a priority. This might sound obvious, but actually, most of the firefighting is precisely caused by management and their own obsession with urgency over importance. That is why it’s paramount that somebody speaks up either from within or from outside.
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