September 4, 2024 – Girl Geek X: ELEVATE Conference and Career Fair for mid-to-senior women in tech hosted over a thousand women & allies globally, with 89% attendees interested in hearing about jobs, over two dozen speakers, 2 resume workshops & recruiting at virtual 18C Booth. Help a girl geek land her next job in tech!
About Our Partner: 18C is a boutique engineering search firm specializing in connecting exceptional technical women leaders with transformational opportunities. By blending strategic executive recruitment with passionate advocacy, we’re creating more equitable environments at the top companies in tech. Watch 18C’s Intro for insights on product, teams, hiring process, open remote & hybrid jobs!
We also partner monthly with companies on Girl Geek Dinners in the greater San Francisco Bay Area, booking now for 2024 and 2025. Please email us sponsors@girlgeek.io and we’ll be in touch!
Voxel51 is a fully-remote Series B startup building a platform that empowers machine learning teams to create more accurate, less biased AI across a number of exciting fields (healthcare, security, self-driving cars).
From an open source project to an enterprise product, Voxel51’s visual AI is used worldwide in academic research labs, startups, and Fortune 10 companies. The engineering team is growing, and looking to hire skilled engineering managers to help us continue to build out the organization and culture. Please consider applying! If you have any questions, please feel free to shoot Josh an email (josh@voxel51.com) or connect with him on LinkedIn. You can also meet Voxel51’s hiring managers at ELEVATE!
Attentive® is the AI marketing platform for leading brands, designed to optimize message performance through 1:1 SMS and email interactions. Infusing intelligence at every stage of the consumer’s purchasing journey. Watch Attentive’s 10-min intro at ELEVATE!
18C Partners is a boutique engineering search firm specializing in connecting exceptional technical women leaders with transformational opportunities. By blending strategic executive recruitment with passionate advocacy, we’re creating more equitable environments at the top companies in tech. Check out 18partners.com and tune in to the 18C employer intro at ELEVATE!
Rippling is the first way for businesses to manage all of their HR, IT, and Finance — payroll, benefits, expenses, corporate cards, computers, apps, and more — in one unified workforce platform. By connecting every workforce system to a single source of truth for employee data, businesses can automate all of the manual work they normally need to do to make employee changes. Based in San Francisco, CA, Rippling was named one of America’s best startup employers by Forbes (#12 out of 500) and the #1 fastest-growing private company by the San Francisco Business Times.
Over 100 girl geeks attended the SOLDOUT Rippling Girl Geek Dinner featuring networking and panel discussions on February 6, 2024 at Rippling’s San Francisco office. Learn how to sponsor a Girl Geek Dinner!
Our goal began with supporting students at our “adopted” school Coliseum College Prep Academy in Oakland, California teaching grades 6-12 with a computer science pathway. We providing access to volunteers and role models from the professional community for students in partnership with the nonprofit Oakland Education Fund, which coordinates volunteer activities with public schools in Oakland and clears volunteers for entry into the schools.
Girl Geek X Community volunteers helped teachers with classroom projects to prepare their rooms and hallways for students return to campus for the new school year. More photos are on Facebook here.
LATINE/X READ-IN AT THORNHILL ELEMENTARY IN OAKLAND
The nonprofit Oakland Education Fund expanded access to students in Oakland elementary schools, starting with volunteering with Latine/x Read-in (Monday, October 2, 2023, 1pm – 2:30pm). Volunteers read books by Latine/x and Hispanic authors to students at Thornhill Elementary.
Girl Geek X volunteers at Latine/x Read-In (pictured from left: Thornhill Elementary School Librarian Marie Fox, Girl Geek X Founder Angie Chang, Customer Success Leader Haana Rafiq, Playground Global Principal People Operations Sylvia Donohoe, Technical Operations Leader Belisa Mandarano, Flexport Software Engineers Bryanna Valdivia and Rachel Colby, and Syntiant Director of HR Jenny Garcia).
Volunteers read aloud books to 2-3 elementary school classes that celebrate Latine/x culture in the 90-minute volunteer shift. Books and sample questions to guide conversations were provided by the Oakland Education Fund.More photos are on Facebook here. ❤️
FIRST-GEN COLLEGE & CAREER PANELAT CCPAIN OAKLAND
TheGirl Geek X CCPA career panel (Wednesday, October 4, 2pm-4pm), moderated by Vanessa Magaña with An Nguyen, Molly Dubow, Bryanna Valdivia, and Elizabeth Orpina shared advice from first-generation students now working in the technology industry.Read about the takeaways from the panel. ❤️
HELPING STUDENTS WITH CSU AND UC APPLICATIONSIN OAKLAND NOVEMBER 3 AND / OR NOVEMBER 17
Volunteers supported seniors’s college applications, providing crucial feedback on grammar, flow, and clarity of writing during “College Crunch Days” – these are dedicated school days for high school seniors to work on their UC admissions applications.
Note: a writing/comms background is NOT required to participate! Any experience writing in an academic/professional setting will be sufficient to participate in this event.
We are looking for TechLink VOLUNTEERS to meet virtually with CCPA sophomores and juniors during the Spring 2024 semester!
Volunteer Mentors will meet on Fridays for ~11 sessions virtually from February thru April 2024.
While TechLink is a virtual mentorship program, Mentors are welcome to volunteer IRL and have lunch with their Mentees at the East Oakland school.
Thank you so much for supporting Oakland public schools and students!
STUDENT PROJECT FEEDBACK (WINTER EXPO NIGHT IS JANUARY 25, 2024)
Girl Geek X volunteers support public school students and educators at Coliseum College Prep Academy (CCPA) in East Oakland. The school entrance is on the corner of 66th Ave and International Blvd. (map)
On Thursday, January 25, 2024 (5:30pm-7pm), CCPA educators and students will be joined by Girl Geek X community volunteers to receive feedback on Senior Capstone Projects.
Bella Vista Elementary is located by Oakland’s Highland Hospital.
On Wednesday, February 14, 2023 (9:30am-11:00am), Girl Geek X Community Volunteers will read books to 2-3 elementary school classes that celebrate African-American culture in the 90-minute volunteer shift. Books and sample questions to guide conversations are provided by the Oakland Education Fund.
Volunteers do not need to identify as African-American to participate, and those who do identify as such are encouraged to participate and share about their culture with students.
Don’t forget to spread the word and invite your coworkers & friends to join you in volunteering! Volunteering together not only strengthens our impact, but also provides a chance to bond.
This event is organized in partnership with the nonprofit Oakland Public Education Fund, which connects groups with schools to make a positive impact on school culture and student achievement through relevant and meaningful volunteer projects.
We want to understand your firsthand experiences, as well as priorities, so everyone can support organizations in shaping a more positive and productive work environments for all.
We seek to understand where disconnections and misaligned priorities exist between business leadership and employees to better facilitate mutual understanding and bring dignity back to the workplace. Survey results will be anonymously grouped, shared, and themes presented to better showcase employees’ experiences.
Girl Geek X is partnering with She+ Geeks Out with a mission to improve the work experience for everyone. (Here’s where you come in.)
We’re conducting this survey to gather real stories and experiences from people. Your insights are crucial to understanding the challenges we all face and advocating for change.
Whether you’re a recent graduate, a seasoned team contributor, or a business owner, sharing your experience (it’s anonymous!) can help build a movement for better work environments. Your story matters.
Imagine a workplace where you:
Feel valued and appreciated
Have opportunities for growth and development
Can maintain a healthy work-life balance
Taking this quick survey can help make that vision a reality.
After completing the survey, you can enter to win a gift card or sticker prize pack. Thank you for your time and contribution. Together, we can create a brighter future for work!
June, 5, 2024 – Girl Geek X: ELEVATE Conference and Career Fair for mid-to-senior women in tech hosted over a thousand women & allies globally, with 85% attendees interested in hearing about jobs, over two dozen speakers, & recruiting at virtual Employer Booths. Help a girl geek land her next job in tech!
Katie Ledoux (Chief Information Security Officer at Attentive), Neha Srivastava (Staff Software Engineer at Attentive) and Margho Dunnahoo-Kirsch (Director of Recruiting at Attentive) speak about the company, hiring, open roles, and more.
Attentive® is the AI marketing platform for leading brands, designed to optimize message performance through 1:1 SMS and email interactions.
Hi everyone. I’m going to introduce myself first. I’m Katie Ledoux. I am the Chief Information Security Officer at Attentive. Neha. You want to go next?
Neha Srivastava:
Yes. Hi, I’m Nehes Srivastava. I’m a Staff Engineer in the Product Engineering org at Attentive.
Margho Dunnahoo-Kirsch:
And I’m Margo. I’m director of recruiting over here at Attentive. Cool. Katie, kick us off.
Katie Ledoux:
Yes. Little bit about who we are, attentive, really pioneered text message marketing, and let’s give you a little bit of the Attentive experience.
I’d love to invite you to text “Hire me” to the number 2 1 7 1 8 and Neha, you’re going to put that in the comments, right? Thank you. You should be getting a message back from us shortly.
You may have interacted with some of our customers on SMS before, maybe you get texted a coupon code from your favorite brands.
We work with companies like H&M, Wayfair, Reebok, Margot just watched me through the companies I was allowed to name yesterday, Urban Outfitters, I’m allowed to name them.
Margho Dunnahoo-Kirsch:
Chanel.
Katie Ledoux:
Yes, and other funny ones that I can’t name, but just trust me, they’re funny in terms of where we are going as a company.
We’re really moving away from a world slowly, but over time we think marketing is going to move away from a world where our customers are sending massive messages to all of their subscribers or to big chunks of their subscribers and really moving towards one-to-one messaging.
I say slowly some of a lot of our customers are already doing this may be some more legacy customers, it’ll take them a little longer to move in that direction.
We really want to go to a place where we’re sending you as a subscriber exactly the right message from exactly the right brand that you’re interested in, at exactly the time that you want to make this purchase for an item that you are actually interested in buying instead of a link to a page of a billion different things that are on sale.
That’s the journey, and of course that’s powered by AI and ML and Neha. Maybe you can…
Neha Srivastava:
Yeah, absolutely. A little bit more. Yeah, absolutely. As Katie mentioned, Attentive Engineering’s biggest challenge right now is to deliver extremely personalized experiences to subscribers of our clients.
Now this isn’t very interesting problem if you really think about it because unlike others, we’re evolving from being a marketing tool to an active partner to the marketing departments of various companies.
We are doing lots of exciting things, which range from writing AI ML models to generating product recommendations and figuring out the best time to send a marketing text. And this is all driven out of the personalization. This is using AI and ML for the benefit of marketing to drive higher productivity, but also great experience for the end user.
Instead of getting a generic text that says, “Hey, Neha, come buy shoes,” and all the links that you get are all men’s shoes, which don’t even appear in my size, which leads to a frustrating experience, you would actually be directed to, “Hey Neha, you were checking out this great shoe at your favorite brand the other day. We found some other recommendations that you might like, which are in my size and available” and I can buy right now and potentially even in my budget.
Driving this life of type of personalization is a very complex engineering challenge and I’m very excited to be working on this. By the way, that’s my project, so that’s why I can talk too much about it.
The problems we’re looking to solve are ahead of the game, yet complex and challenging so that if you’re like me, someone who gets excited about solving complex problems for the business, you’d absolutely love it here.
Generally speaking, our product engineering orgs sits in a New York platform, is remote and AI ML teams sit in SF.
However, almost all of the projects are extremely cross-functional, so regardless of which location you’re in, you’ll end up working on the same projects and you’ll get a piece of the pie and problems that you would love to solve.
We’re hiring across the board and Margo will tell you all about that.
Margho Dunnahoo-Kirsch:
Awesome. Thanks Neha. Alright, let’s talk recruiting. Our engineering org is about 230 people spread out across the US.
We do have offices in San Francisco and in New York. Our interview process for a standard software engineer is really consistent across all of our teams and locations.
It’s about a 3-week process starting off with a recruiter screen. Then, you move to a 60 minute interview with one of our senior engineers. That conversation is going to be really digging into past experience. What was your role? What was the complexity of the work?
You’ll do a backend coding challenge and then that will be followed up by a reverse architecture conversation.
Once that is complete, we invite you to meet with about four to five more members of the team. This includes coding challenges and architecture interviews, and then discussions with hiring managers.
Don’t worry, a recruiter will prep you for all of that beforehand, then we also do do team assignments at the debrief stage.
We try to really match you with a team that aligns with your experience and interests, and then we’ll get you set up with a few members of those teams so you can learn more about what your impact would be, what you’d be working on, all that kind of stuff.
We have two offices, so we have New York and San Francisco. New York is our headquarters, but the majority of the employees are remotely. I’m actually coming at you from Denver, so this is where I am, home base. My team is primarily in San Francisco, but I do feel super connected to everyone.
The company has a really good job of driving engagement, which brings me to our culture and talking about our employee engagement team, so we do a full company offsite, annually. We do engineering team offsites every year, but then we also do a lot of virtual engagement activities.
Our employee engagement team just hosted a few virtual events. My favorite was the how to make your spring, how to build your own spring roll. We had a floral arrangement class recently and then we also had a good one around understanding the anatomy of our anxiety to honor mental health awareness month.
Just a little bit about us. I know Katie Ledoux’s team is hiring, Neha’s team is hiring, so we would love to have you guys come stop by our booth and meet with us. And then a few members of our attentive Woman Engineering ERG group. Cool. We crushed it.
Katie Ledoux:
We did. Can we use our three minutes for questions?
Someone asked: If we hire entry level engineers, we do have an engineer two role up right now, but that’s the most junior role we have right now.
I can’t speak for every engineering team at Attentive, but it’s going to be important for us on some of these newer teams to make sure that we have the levels of leadership in place before we bring on brand new entry level people so that they have the mentorship that they need to be successful on those teams.
Margho Dunnahoo-Kirsch:
A hundred percent, yes. We just posted, we have three software engineering roles just posted.
One is on our BI team, led by one of our engineering managers, and then we have two engineering twos, one that just got posted for remote employees, and then one that just got posted for San Francisco.
Hybrid – You’d be coming on site three days a week to our San Francisco office in the financial district. And then, Neha has teams mainly looking for some senior level engineers.
Katie Ledoux:
I saw one question. You definitely do not need a background in AI machine learning to apply. If you go on the career site, there’s a breadth of roles across infrastructure security. it it’s definitely not exclusively AI ML roles especially.
Neha Srivastava:
I have no experience in AI. I’m not an AI expert. Just to be clear, I am leading AI ML project and I have no experience on it because the way we think about this is it’s a product, right? A model is developed and then we pipeline it all the way to make it into a product.
I am a backend focused product engineer, so my job is to make sure that the model is delivering value as a product. I’m overseeing the whole thing and helping with the design and the architecture of it, but I’m not doing the modeling myself.
Margho Dunnahoo-Kirsch:
Answering a few questions interested in non-engineering roles. Would you be able to hold a conversation with me? Yes, a hundred percent. We are hiring and go to market g and a, and I also oversee those teams, so a hundred percent can talk to you about that.
We are only hiring in the US for engineering roles. Yes, for a few of our sales positions, we do hire in London as well as Australia. But just for engineering for now, we are primarily just us. We do support visas.
In this ELEVATEsession, Soumya Lakshmi(Director of Engineering at Adobe) speaks about developer experience (DevX): productivity, impact, and satisfaction as keys to quality and collaboration.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!
Thank you Sukrutha. Hi everyone. Happy Women’s Day and thank you Sukrutha Angie and the ELEVATE team for giving me this opportunity on Women’s Day. I’m here today to talk about DevX. DevX is called developer experience. This is going to be a little geeky talk, so bear with me. It’s purely from the engineering side, but I promise I have a story to say, which is what I’m going to start with.
I grew up in India and reflecting on my childhood in India, we did a lot of train journeys. Train journey was sort of the internal part of our family outing. These adventures began long before the train even arrived. It sort of marked the anticipation and the flurry of preparation. And each journey meant packing our bags with care, ensuring that we have everything needed for the trip. Upon reaching the station, our next step would be to find a porter or a coolie, is what we call locally in the Indian language.
Now, watching these skilled porters effortlessly balance their entire family, our entire family luggage, where I’ll show you a picture, I hope it’s pretty clear. I try to get a picture where a porter is carrying a lot of luggages. There’s one couple on his head and there’s two, one on his right shoulder, one on his left shoulder, and then he just carries around. Now it’s a real skill to carry the entire family’s luggage on their heads and arms, and there was nothing short of remarkable. Now they carried our burdens, allowing us to navigate the crowded station with ease, transforming our potential strenuous part of our journey with this seamless experience.
Now, why am I saying this? What has this got to do with the developer experience? Now, this memory serves as a powerful metaphor for a challenge faced by our developers and the engineers today. In many ways, they are like the coolies or the porters of the digital world, just as the porter prepares the physical journey. Let me go to the next slide. There we go.
Just as the porter prepares for the physical journey by strategically balancing the load to carry our developers and engineering teams and engineers geared up to the journey of innovation, excited about the possibilities of deploying really exciting features, but they also weigh into the inefficiencies that accompanies with the role and these inefficiencies being slow build processes, inadequate infrastructure, sparse test automation, nebulous documentation, and ever looming shadow of the tech debt, which never gets over are the suitcases of the software development industry that exists today.
Now, these are necessary parts of the journey containing assets and tools along the road. Yet this is a cumbersome process, slowing the pace down, clouding the excitement, and at the end of it, it seems really tiring.
Why then should our digital porters or coolies, the developers and engineers whose innovation propels us forward, accept the struggle as given, just as an introduction of wheeled luggages, revolutionized travel for many of the load or managing the load because adding wheels to suitcase? It really did not change the functionality of the suitcase, but what it did is made a hard task easier, and that’s really what DevX is. That’s exactly what the crux of the developer experience is.
Let me talk a little bit about the recipe of what I think, and GitHub completely agrees with this, is of what a DevX is.
DevX can be viewed in many different lenses, and this has become a common buzzword in the industry, but a lot of companies have started to put as this is an org and this is a team and we are investing in it, but what exactly is this? And it can be viewed in many different lenses. I think that the formula for DevX incorporates few key eight things.
First, it takes into account how efficiently and productively a developer can do their best work on any given project. The second one, how simple is it to make a code change and how easy is it to move from idea to putting it into production? Today, if I have an idea in mind, how long does it take for me for that idea to be delivered in the hands of our users?
DevX also examines how positively or negatively the work environment, the workflows, the tools, the technologies that affect the engineering satisfaction. By eliminating some of these friction and inefficiencies, we can multiply our operational impact. Now, if we want to move fast, it is easy, but if we want to move fast with quality is when the tricky part comes.
Collaboration and quality is also the integral piece of what a DevX is. If our engineers are productive and if they love what they’re doing, and if collaboration is smooth and quality is the integral part of it, then we have a good DevX and DevX is great. Yes, we want everything. I mean, who doesn’t, right?
Let’s see. Okay, why is this important Now, why are we talking about this? This seems pretty obvious to some extent, but why is it becoming even more important now? Because of the macroeconomic climate in the industry, the economic uncertainty is shaking up the tech industry with increased pressure on infrastructure and engineering teams to optimize cost. At the same time, we also realized that the progress and innovation must be accelerated as it is the key lever to create business value and success for digital initiatives and boost revenue of organizations and with restricted budgets.
That’s the key point. There was a survey or a snapshot that was done February of 2023. It’s called the Forrester Opportunity Snapshot, and what they did is they looked across 500 enterprise companies across United States and they did a survey of what the companies think that they should be focusing on to innovate.
Now, this company who does this survey is their focus is digital transformation, and organizations are recognizing and making sure that the operational excellence is on par with a restricted budget. These were some of the results of the survey. I won’t go into a lot of details because it is a lot of numbers. I’ll still talk about the top four key findings that came out of the survey.
The first key finding is the need to increase efficiency as a key focus. Yes, there is no headcount. There’s no incremental headcount. The companies are not hiring as much as they were and the climate, the microeconomic climate is extremely challenging, but we still need to innovate. To keep up with the pace of the digital transformation, organizations are recognizing that the need for developers to build, deliver software with greater efficiencies before.
Me as an engineer, it’s been a while I wrote code, but as an engineer, if I’m able to write one pull request in one day, then how is my company, how is my company providing the tools and technologies for me to merge two or three per request? That’s where the industry is going, and that’s where the crux of DevX is. Now, according to this research, 87% of the leaders agree that increasing the developer productivity is a priority for the next 12 months, while 85% say that better meeting customer demand will be their focus, and 85% say that shortening the release cycles, but would be the key factors involved.
The second key finding is several obstacles will hinder developer productivity. Now, developer productivity is not as simple as, Hey, you give me a tool and a framework and I can make things happen. There are a lot of different things that go into the combination of uncertain economic outlook, increased competition, shifting, customer demand, and the hybrid work as well as the DevOps methodology. This is all highlighted in the report. If you take a look at these numbers, 41% of the respondents say that developer productivity and experience building difficult to improve because of pandemic related issues like onboarding, training, mentoring. The face value is gone, and I’m sure things are improving eventually, but we need to strike a balance and focus more on not just the user experience but also the engineering or developer experience. The key finding three is having an internal developer platform, or an IDP, to boost developer productivity.
What’s the solution? You just give an IDP and then that’s the solution. Well, according to the snapshot or according to the survey, they said that IDP enabled a self-service for developers, helping them to become less reliant on operations and reducing bottlenecks that caused by ticket ops and whatnot.
This is one of the biggest pain points caused by increasing complexity of cloud architecture. Not only do platforms help alleviate this challenge, but they also have a potential huge impact on developer velocity and satisfaction by optimizing developer workloads and freeing up teams to focus on value adding work.
And the last one is the developer experience impacts overall business. It’s not just that we make strides and we make improvements to the developer experience and only engineering teams is benefited. Let me go forward a little bit. There we go. This talks about the survey also took into account teams who already invested in an org like DevX, and this is what they found. They found that it not just improved the engineering productivity, but it improved app development, time to market, customer attraction and retention. On the delivery side, there was brand recognition reputation, and on the operations side we had revenue growth and developer recruitment, retention and profitability.
Alright, so I think there was a lot of numbers. What is the crux of this conversation and where are we headed? In conclusion, what I do, I have about five minutes and I can take questions after this. In conclusion, what I would really like to add is think about it like adding wheels to your suitcase. 20, 30 years we all traveled, lugging our baggage or somebody else carried it for us instead.
The simple solution of adding wheels really made all our jobs easier. We could just go anywhere in the world lugging our luggage right behind us because the wheels take care of it. The wheels don’t necessarily improve the functionality of the suitcase, but it does do a lot of heavy lifting.
Think of DevX as the heavy lifting of the software development, a thing of the past. And we are not just enhancing the developer experience, but we are also enhancing the growth and innovation in the coming years. Thank you.
Sukrutha Bhadouria:
There are some questions here. There’s one question. How do I get started with using DevX for my company?
Soumya Lakshmi:
That’s a great question. Depending on which stage your company is and at what point there is readiness, there might be a few different things. I can speak from Adobe’s perspective. Adobe, I don’t think a year ago DevX was even a thing we started talking about, like I said in the presentation, we were not there.
We were not hiring and headcount was crucial, but we still had to make improvements. But there were different teams and members of the team who were already doing this kind of work.
One of the things you could do is create a working group across different products within the organization to see what needs to happen and how you can share and reproduce to share and sort of reuse some of the frameworks and toolings that you’re doing. That could be the first step.
Then, meeting often online of course, I mean, and setting up a roadmap of what is important and what are the gaps, and at least starting this conversation in the devs direction might be the first step towards it.
I’ll also add that there are a lot of resources available online because again, all the companies, many companies are realizing that our user experience and customer experience is crucial, but so is our engineering and developer experience. That might be a good starting point.
I’m available and you’re welcome to reach out to me personally and I’m happy to provide guidance on that front as well.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!
In this ELEVATEsession, Poornima Muthukumar (Senior Technical Product Manager at Microsoft) shares how data can help product managers validate their assumptions, test their hypotheses, and measure their outcomes.
Attendees learn to build data-driven products backed by insightful analysis and how to utilize big data, data science and machine learning to inform complex product decisions.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!
Hi everyone. Good morning. Thank you so much for joining today’s presentation. I’m super excited to speak to all of you today on how to unlock product growth with big data, data science, and machine learning. Some of you might be interested in getting into a career either as a data scientist, business analyst, data engineer, technical product manager. so if you’re in any of these careers, I hope that this talk resonates with you and I hope that you can take back something for your job.
I also want to thank the Girl Geek IO for giving me this opportunity to speak to all of you today. And I want to add that I’m not speaking on behalf of Microsoft, but rather sharing the knowledge and experience that I have gained along the way in my journey. So yeah, without further ado, let’s get started. Brief look into today’s agenda so you know what you can expect from this talk.
First, we’ll go over my background so there is context on some of the things that I shared. Next, I will talk about how data is at the center of nearly every product you own and how that data is used to customize product to your needs, allowing companies like Netflix and Uber to build great data-driven products.
Next, we’ll talk about why companies need individuals who can use data from all of that big data, and what are those different data types that you as a product manager can leverage to extract insight to give customers the product that you want. And finally, if we have time, we will take some question and answers. Cool.
A brief background. I grew up in India. I spent a majority of my childhood in Mumbai and Chennai finishing my education in India. Post that I went to Singapore where I got my bachelor’s degree in computer engineering from the National University of Singapore. During my time at Singapore, I also interned at Bank of America and Goldman Sachs as a software engineer. After that, I went to New York where I worked in Goldman Sachs as a software engineer, building software for banking systems and capital market. After that, I went to Ireland where I worked in Microsoft Ireland research center as a software engineer in the office team. During there, I also traveled all across Europe, so that was a lot of fun.
After that, I came to Seattle where I grew in my career as a senior software engineer in the office release and delivery experience team at Microsoft. My team was basically in charge of delivering office updates that you got each month for all of your apps, like Word, Excel, PowerPoint on all platforms like Mac, iOS, windows, and Android. During this time is where I realized the power of big data and decided to pursue my part-time masters in data science from the University of Washington.
I also transitioned into my career as a senior technical product manager for the Microsoft 365 team because I wanted to have an end-to-end breadth of ownership of a product and be able to do that in a data-driven fashion. Today I am a data science volunteer at the Women in Data Science Puget Sound Community. I own patents in AI,ML, and big data at Microsoft. I am also volunteering at the UDub Foster School of Business as a product management accelerator.
Here I have five products that I want to quickly talk about how these companies are using data to drive their product growth. Netflix is something that all of us know how. Netflix uses data to build a recommendation model. They also use data to decide how to invest their money and what kind of producing content that resonates with user. They also use data to decide which movie to store and which CDN location based on where the users are streaming movie from in order to efficiently stream movies so that they can optimize for storage cost of CDN.
We know Tesla uses data for powering their autonomous driving system. They also have these cameras and sensors that’s constantly sending data back to Tesla, which in turn is used to optimize their self-driving car.
Amazon is one such product that uses data throughout their entire product stack. They use it for their search result optimization for price forecasting, warehouse optimization, inventory management. There’s just many, many ways that Amazon uses data because it has such a huge customer base. They have all of that huge amount of data which they can use to build and improve their product constantly.
Instagram, I’m sure all of you are aware that all the reels and all the contents and all the things that you see, there is a machine learning model that is running real time customized for you.
That is taking in all your engagement data, that is taking in all your usage data, which in turn is used to customize the model and send data back to you, which in turn gives you content that resonates with you in order to keep you on the product longer.
Next, we have Microsoft 365. Obviously now we have copilot. We have all of that ChatGPT integration that integrates with all your different Office 365 apps in order to give you in order to optimize your productivity suite experience with Microsoft, so if you see what is common to all of these products is they have a huge customer base that generate a huge amount of data, and today’s storage and compute and processing has become so cheap that you can store all of this data.
You can run data science techniques, you can run machine learning models, you can run algorithms on top of it to extract in site, which in turn can be used to optimize your product, which in turn can be used to build products that delight your customers.
Let’s say you join as a product manager for any of these products. You are constantly getting data from various signals. Could be feedback data, could be usage data, could be finance data, could be sales data engagement, data retention data.
How do you as a product manager organize all of this data in a clever way, in an intelligent way so that you can extract insight, which in turn can be used to drive product growth? How do you leverage those different data science algorithms techniques to optimize your product? Which is why I feel that the future of technical product management involves the melding of data science and product management because there’s so much that you can leverage to drive product optimization.
What you can expect from this talk is how to build data-driven products backed by insightful analysis and how can you utilize big data, data science and machine learning to inform complex product decisions.
Here are list seven techniques that I use in my day-to-day job to drive product growth and use data to drive them. First, I list the seven techniques, but because of the time constraint, I’ll only go in detail into three of them today in the talk. Tthe first one being funnel analysis, funnel analysis, how do you look at your customer journey end to end and see where customers are dropping off in the funnel so you can optimize your customer journey and thereby improve the conversion rate.
Next is retention analysis, right? Retention is a very important metric for any product. It’s great to have customers sign up for your product, but you also want to see of that, how many of them are actually using your product? How many of them are enjoying using your product? Let’s say you have a subscription service. You want to know what percentage of customers are renewing your subscription versus what percentage are canceling your subscription.
Next is segmentation analysis is how do you slice and dice your customers segment based on different things? Could be customer demographics, could be age, income, gender, their preferences, their needs of their purchase characteristics. How do you take all of this different data and slice and dice your customer into different segments, which will help you identify your most profitable segment and in turn cater your products differently to different segments?
Next is engagement analysis. This is how do customers interact with your product? How often do they interact with your product? How deeply do they interact with your product? What is it about your product that they like and what is it that they don’t like? So let’s say you have a website and you notice that majority of your customers have who visit the website, leave the website in a very short duration of time, right?
Let’s say you’re noticing that majority of your customers have a very short session duration. How do you use this data? Once you measure it, you have this data and now that you have that data, how do you use it to understand how you can improve engagement for your product?
Next is feedback. Feedback analysis is nothing but how do you collect feedback from various signal sources? Like could be feedback or [inaudible] ratings, reviews, all of that data and use that to understand what are your strengths and weaknesses for your product. And next is AB experimentation. This is where you show two different variations of your product to your customer and see which one resonates with your user and use that data to eventually launch the change to all the users.
And finally, machine learning. Machine learning is a very important tool that as a product manager you can leverage to give user centric and innovative solutions for your customers.
It’s important for you to know and have an awareness of what are the different machine learning models, algorithms so you can partner effectively with your engineering team, with your data science team to build the end-to-end pipeline to deliver the feature. Of these seven techniques, we will first look at funnel analysis. Like I already said, funnel analysis is a method used to analyze the sequence of events leading up to a point of conversion. Let’s say you have an e-commerce website.
Let’s look at one customer journey, right? Let’s say the customer came to your website, they searched for a product that they wanted to purchase, they added the product to cart, they went through checkout, and at which case they finally completed the purchase, right? This is just one customer, but not every customer will follow the same journey. Some maybe will come to your website, at which point they lose interest and they leave.
Some maybe will come to your website, they’ll add the product to cart, at which point they leave only a small section of customer eventually go all the way up till purchase, entering their payment details and completing, which is why it looks like a funnel. The ideal journey is obviously the whole thing. You want every customer to go through every step, but the funnel keeps getting shorter because customers keep dropping off.
Once you have this data, let’s say you measured this data for your journey for whichever feature you own, you measured the data in the form of a funnel, and let’s say you notice that majority of your customers are dropping off at the homepage, maybe you can hypothesize that your page is too slow, which is why customers are losing interest and they’re leaving. And whereas if you notice that majority of customers are leaving at the payment and checkout screen, at which point you can hypothesize, maybe the pricing is too expensive.
Once you have these different hypothesis, you can run experiments and improve the overall conversion rate for your product. Okay, next is AB experimentation. Here I have two different greeting cards for a Christmas, right? Maybe the one on the left resonates with the customers more and they click on it and they open it. Maybe the one on the right is not as appealing. Here, this is a trivial example.
In this case, the customer greetings, it maybe doesn’t matter if customers really open it and see it because it doesn’t translate into business outcome. But that’s not always the case, right? Let’s say you have an open house website, you want customers to click on the website, sign up for the open house so that your house is eventually sold, maybe in this case the color of the button results in different conversion rate and that it really matters what color of the button. That is something you can maybe experiment and see which one results in a higher conversion rate, not just for visual things.
Here I have Nike website, maybe the search algorithm on the left. There’s different from the search algorithm on the search result ranking on the right. Maybe the one on the left is resulting in higher units of shoes sold and higher revenue for the company, in which case you can totally AB experiment this as well.
What I mean to say here is that AB experimentation is not just limited to visual things, UI elements and things like that, but you could totally even AB experiment algorithms, APIs, backend systems or different systems that eventually translate into better user experience for your customer. So what exactly is AB testing? It is called split testing, bucket testing, randomized control experiment. It’s typically used to compare different versions of a webpage, but you can test anything from the color of a button to the backend algorithm to the layout of a page.
The AB groups are typically called control group and test group, and all elements are held constant except for that one thing that you really care about and you measure it. And it’s the best scientific way to establish causality with high probability. What it means really is that you’re not going by gut feeling, you’re not going by instant, but rather you’re running a scientific experiment and saying that based on the results of the experiment, I can conclusively say I can conclude that changing something results in a higher something else.
You can establish that causality in a very scientific way. What are the different stages of AB experiment is the first is you have a problem statement. You define the hypothesis, you design the experiment, you run the experiment, and then you eventually interpret the results based on the problem, based on the business that you’re in, based on the company that you’re running AB experiment. For you problem statements will be very different because you want the experiment to ladder up to the uber goal that the company has set.
Let’s say that I join as a product manager for a travel company like Expedia or booking.com. I will run experiments that eventually impact these metrics because that’s what the company cares about. The company wants to increase number of bookings, they want to increase their loyalty participation program, they want to increase maybe number of searches that people are conducting on their website.
Whereas if you are a media company like Netflix or Amazon Prime, they want to increase engagement, they want to increase subscription rate, they want to increase content consumption time. So your experiments that you run will impact different metrics. And as a product manager, if you’re running AB experimentation, you want to be very clear on the problem statement even before you get started, even before you design the experiment.
That is something you start off your ab experimentation process with. Again, if you’re an e-commerce company, your goal is to increase products viewed, products added to cart, resulting in higher conversion. And finally, if you’re a social media company like Instagram or Facebook, your goal is to increase engagement or maybe increase revenue through advertisement and things like that. Here what I’ve captured is that the problem statement could be very, very different, and that is something you want to be very clear about and define it at the start of the process itself.
Next is defining the hypothesis, right? A hypothesis is nothing but a testable statement that predicts how changing something will affect certain metric or a user behavior. So here these are the three steps that I use to define the hypothesis is you want to be clear on the problem based on evidence, and you want to decide changing something impact certain outcome and how that impacts the problem.
How do you know you have achieved the outcome is when you see the metrics change, right? Here below I have defined an example of how you could do that. So let’s say you are a product manager for an e-commerce website. You’re seeing lesser number of units sold on the website through sales data. That is the problem you have and that is the evidence you have.
Let’s say you believe that incorporating something like a social things like X number of people purchase in the last 24 hours will influence them to purchase and make the purchase. That will result in people actually converting. And that’s your gut feeling and that’s your hypothesis that you start off with. At the end of the experiment, you’re seeing whether indeed doing that change results in higher revenue and higher units sold. So that is what your null hypothesis is, and that is what your alternate hypothesis.
You can also define the significance level and statistics, power, and these are industry standards that you use a level of 0.05 and 0.8 to define the sample size that you want to use for running the hypothesis. Next is designing the experiment. When you design the experiment, you want to be very clear on what the metric is.
The primary metric, and you also want to be clear on the revenue. Maybe you have one primary metric, but maybe in this case it is revenue per user per month. But you could also have secondary metric and other metric that you want to test. You also want to determine the population that you want to test it for. Let’s say whether you want to run the experiments specifically in US in Europe for certain section of the market or all users.
Next is how many people do you want to run the experiment for is determining the sample size here I already talked about using an industry standard of alpha and power to determine how big your sample size should be in order to have statistically significant data to draw conclusion.
And finally, how long do you want to run the experiment? In this case, you could run it for two weeks, you could run it for two months. You can run it for much longer. And you also need to think about seasonality days of the week and holidays. You don’t want to design some email engagement experiment during holiday season when people are on vacation, not really checking their emails. Those are some factors you would decide take into factor when you’re designing the experiment.
Next is once you have all of these things finalized, you randomly assign users to group A and group B, and it’s very important to randomize so you’re not introducing any bias into the process. And you partner with the dev team to instrument logging for any necessary metric, collecting data to make sure you have a dashboard that surfaces the metric that you care about.
As you can see on the right, you are tracking revenue and you’re tracking how does revenue differ between the control group and the treatment group. And that will help you decide how your experiment is doing. And then you want to avoid looking at results before running the experiment for the entire duration of it and avoid peaking and jumping into conclusion. And then finally, once the experiment is run, you want to make sure that the data is reliable.
You want to perform some sanity check. If the data is obviously unreliable, you want to discard it and rerun it and then make some trade offs. Let’s say at the start of the experiment, you decided to measure engagement and revenue. And at the end of the experiment you saw that, okay, based on the changes that you’ve introduced, revenue is looking good, it’s going up, that’s great.
But if engagement is going down, you want to make the trade off that. Is it really worth introducing the change? How do you want to look at the result? How do you want to interpret the result and things like that? And then eventually launch the change to everyone. This is one way you take a data-driven approach to introduce changes.
An AB experimentation is widely used within Microsoft is something I’ve used throughout my career. We have these office bills that are released each month to millions of users, so before we introduce a change to such a worldwide population, we launch it to a small segment of population.
We collect telemetry signals, we collect all the signals, crash signals, we make sure that it’s looking good, and then eventually launch the change through a different release pipeline that we have. And that is something that throughout industry, it’s practiced in Instagram everywhere where they test some change with a small section of user, use that data to then eventually launch the change.
Cool. Next one is machine learning. Machine learning is not a magic wand, but it’s an application of AI that provides system the ability to learn and improve from experience without being explicitly programmed. When do you want to use machine learning is when you have lots of data, when you have a complex logic, something that cannot be solved with if statements cannot be solved by classic programming. That’s a good example.
When you want introduce some sort of personalization, like you have the case with Uber, you have the case with DoorDash, Instacart, all of them provide you a very personalized experience. And when you want the system to learn with time, that’s also a classic example where you want to introduce machine learning. Something like Twitter, what’s standing on Twitter today might not be training tomorrow. And that’s where machine learning is a classic example and fits the scenario.
Here I have three different types of machine learning. One is the supervised machine learning where you have machine learns from training data that is labeled where you train the system while it learns to do on its own. Next is you have non labeled training data. And finally is reinforcement learning where the machine learns on its own.
Here I’ve listed quickly different techniques of machine learning that you can use. One is ranking. This is something I already talked about that Amazon uses machine learning for, powering the search result ranking recommendation. Again, Netflix uses it for powering their home screen. Different recommendation, I guard them.
The great thing about recommendation, it doesn’t have to be perfect as long, it’s close to accurate. Customers are happy classification. Facebook uses it for tagging different users on their product. Classic example of classification regression is something we use for seeing, for casting, clustering for Spotify, uses it for clustering songs. And finally, chase uses anomaly detection for flagging fraudulent transaction. Thank you.
Sukrutha Bhadouria:
Thank you so much. This was a wonderful session. Yes, going to hop on to the next one. Thank you so much.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!
In this ELEVATEsession, Dotty Nordberg (Senior DevOps Engineer at Pure Storage) shares strategies ensuring a positive outcome when presenting your ideas. You will learn how to effectively use various forms of communication (e.g. email, slack, zoom), who you should talk to (and what you should talk to them about), and how can you get those key stakeholders to buy-in to your plan.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!
Thanks Angie. Yeah, so happy to be here today. First of all, I’d like to say happy International Women’s Day, everyone. Thank you for joining. This session is going to be hopefully a fun session on effective communication in particular persuasion, getting that yes, that is so critical in our work and our lives. Let’s get started. Again, we have a full agenda today. We have a short amount of time, so hopefully we’ll get through all of this. If there are any questions, I hope to get to them at the end. If not, you can always reach out. I’ll give you my contact information and I’m happy to talk after.
I’ll introduce myself. We’ll define persuasion so that we’re all on the same page. We’ll talk about why persuasion is so important. We’ll talk about some challenges that you may face with being effective in communicating and persuading with others, and then some strategies to overcome that and to increase your persuasion powers.
Then we’ll talk about a success plan for the day of say you have a big idea that you want to present to your management team or maybe even higher ups. We’ll talk about the success plan for that particular day and then hopefully Q and A. Let’s get going. Okay, so me, a little bit about me. I am a technologist. I’ve been a geek all my life. I have an undergraduate degree in math, not computer science.
I’m a little bit of a non-traditional background. I took a bit of a circuitous route here. I started out as a Windows systems administrator. I got some certificates, so those bootcamps and those certificate courses, they can help you get your foot in the door. That’s how I did that, and then I worked on the Linux side of things as a Linux systems administrator. Got some training in that. Again, certification courses, working kind of on my own, highlighting that on my resume and at interviews and things like that.
Now, my focus for the last several years has been more of the cloud platform engineering and systems administration that, so as we mentioned, I’m a DevOps engineer. My current role at Pure Storage, I’ve been there for about five years, really enjoy it a lot. Moved to the San Francisco Bay Area about 13 years ago. I was originally on the east coast of the US, grew up in New York, lived in Atlanta for a while and then moved out to the west coast of the US near San Francisco about 13 years ago. I’m also a speaker.
I’ve really enjoyed speaking at events like Grease Hopper / Anita B, and ACM-W, and then of course Girl Geek X. I’ve been a mentor to probably hundreds of techies at this point. Mostly people new to tech. And they’re so talented, so inspirational. I cannot wait to see what they do next. And it is one of my favorite ways to give back to this community. I mean it’s small, but I think every little bit helps, so it’s one of my all time favorite things to do. Other miscellaneous things about me. Little fun facts.
I like to run and hike. I’ve trained in martial arts. I like to read. I’m in a couple of book clubs, travel, and right now I’m learning Spanish just for fun. I am a lifelong geek because I mentioned I love science and sci-fi. I dreamed of being an astronaut. And one quick little story about that here out where I live is, right down the street is one of the NASA research centers. A couple of years ago, one of my friends said, “Hey, I’ve been volunteering at the NASA Center there. They have an educational program for 12 year olds and 13 year olds. Do you want to to do this with me? I hear you want to be an astronaut. “And I’m like, “yes, please sign me up right away.”
It was so fun as a temporary volunteer, I got a temporary badge to just go right through the gates. The guards just kind of wave you right through the gates, which was so fun. And then at the educational center working with the kids, they had four or five different stations that were teaching the kids all about space, space, travel, it makes it possible, flight, all of that stuff. Release principle for flight and orbital mechanics and all that stuff like that. One of the displays is a mock space shuttle mission with a mock little space shuttle. And then I got to be Houston. I got to be ground control and be like, “Hey, ground control, mission control to space shuttle, please come in, space shuttle.” I was like a twelve year old kid at that thing. It was great. I think I had more fun than the kids did that day, so a lot of fun.
Okay, so let’s get to our topic today. Persuasion. Looking up on our friend dictionary.com, it says that persuasion is the act of persuading or seeking to persuade. The power of persuading and persuasive force – which really doesn’t tell us what persuade or persuading means, so what does persuade mean?
Persuade is to prevail on a person to do something by advising or urging to induce to believe by appealing to reason or understanding, convince. If you combine the two, it looks like persuasion is convincing the act of convincing someone to do something or one of the things that while I was doing this research on persuasion is it kind of seems similar to negotiation, but there is a difference in negotiation looking at the definition of that there’s a mutual discussion and arrangement of the terms of a transaction or agreement.
The difference for me is that persuasion is kind of a one side is trying to convince all the other sides of something, of the value, of their idea, of the reason why we should do this In a negotiation, it’s all parties. They’re trying to benefit in some way. For example, in a job offer, the company is trying to convince you that they’re a great company to work for, they have great benefits, they have great tech that you’ll be working on amazing products, things like that.
And you, for your part of that negotiation of the job offer, you’re trying to convince them to pay you as much as possible to pay you what you’re worth, say a million dollars a year, something like that. If you figure out how to do that, please, please let me know because I still have not done been able to do that yet. I would love to. Then contrasting that with a persuasion. Say it’s a company crisis. Things are on fire, it’s a P one, it’s outage. Services are down, customers are complaining. You really need to kind of maybe push your idea and say, Hey, this is the right way to go. You don’t really have time to negotiate per se.
And why is this important? It is a soft skill, meaning that it’s not a technical skill. It’s not like learning Python or Java or something like that, but it’s not typically taught in schools or in life in general.
Soft skills are very, very important tools to have for your career or even in your life. We use this a lot. I would say we use it in the workplace as well as in our regular lives. When we’re talking to, say maybe we’re on a board of a city council or something, and you’re speaking to legislators, you need to be able to persuade them like, this is the way to go, or this is not the way to go. Even parent teacher meetings, maybe your child needs a little extra help in class or you are the student and you’re working with your professors, asking for more time on a project, things like that. And for those of us with kids, I’m sure we use persuasion pretty much every night trying to convince our kids to go to bed at the appropriate time.
Persuasion is needed when you have a new idea, when you have a different opinion than others. When you’re working on those key assignments and you need to get a direction on which way to go, it could be the wrong direction to start, but sometimes you just need to get going, especially when you’re asking for a raise or a promotion. Definitely need to figure out a way to persuade your manager that, yes, I’ve done X, Y, Z, here’s the market rate for what I’ve been doing and things like that. And I highly recommend you do that as at least once a year, every one year or two years, something like that.
How do we use persuasion? We use it in meetings, we use it in presentations. We even use it in email over Slack. And especially as we discussed in a crisis situation, some possible personal challenges might face or I think you have, we hear a lot about imposter syndrome that when you feel like you don’t belong because you don’t have the skills, why am I here? They’re going to find out I’m a fake, I’m a fraud. I shouldn’t be doing this.
Maybe you feel like you’re the only person in your group of you’re the only woman say, or the only person of color, the only LGBQ, whatever that is for you. Or maybe you’re cross section of a couple of those that might be intimidating for you to try and put your ideas forward. Bro, culture is a thing and that might intimidate you as well, especially even cultural differences and societal norms.
Say you’re from a different country than most of the folks on your team. You have different cultural expectations and things that might hold you back a little bit. There is good news.
If you feel any of these things in particular, imposter syndrome, you are not alone. I’ve talked to many, many folks in all levels of companies, directors of engineering for 5,000 person company, and all the way down to individual contributors and affect men, women, all genders.
Everybody feels imposter syndrome at some point, especially if you’re the new person or if you’re new to the industry. If you’re new to the company or new to the industry, you are going to feel this way. Keep in mind that it’s pretty comforting to know that that’s normal to feel that way. Nobody expects you to know everything right away, especially if you’re new. And yeah, like I said, we’ve all been there, so take comfort in that and know that you’ll be fine.
You do deserve to be here and we want you here. You’ve earned your place and you do deserve to be here. More good news is that more companies are recognizing the importance of diversity, equality, and inclusion programs. And some have sensitivity trainings that are required of their employees.
Overall, I would say these challenges are diminishing, and I’ve been in this industry for many, many, many years and I’ve seen for me personally, these challenges going away, which is good news.
Here are our strategies for increasing our persuasion. Tailor your message for the different situations that you’re in. Is it a crisis or is it a non-emergency? It’s a crisis. It’s going to be a very different conversation than if you, it’s a non-emergency and you have the time to think and maybe plan out the project and things like that. Are you talking to a teammate?
Are you talking to your manager? Are you talking to the CEO of your company? Very different conversations because just for the view of that person, the executives are going to get the 10,000 foot view versus your teammate who’s right by your side every day. They know the lingo, they know everything that you’re doing. That’s going to be a very different conversation. Even your manager, they’re looking at it from a different point of view than you are. They know the tech, but then they also are a little bit higher in the hierarchy of the company, and so they have a little bit different view of things.
The words that you use and the message would be a little bit different. Is it going to be in person or video conference? Is it going to be over email or chat? Is this person a tech geek or are they not a tech geek? Meaning, are they in your industry? I mean every industry, its own geek speak, I would say. Is this person part of that community or not? It’s going to be a different conversation if say, I as a DevOps engineer, I’m talking to a finance person or hr, something like that, so you tailor your message to all these different situations, try to get into the other person’s head and understand their point of view.
Anticipate any objections to your idea, try and see the issue from all angles. This will foster better communication with those people that you’re presenting to, assuming that you have time to put together a presentation and it’ll form a more comprehensive case for your idea as well. Master the art of storytelling, so try to share your ideas through compelling stories and then interesting narratives, capture the audience’s attention and do a time check.
Right now we only have a couple of minutes, so I’m going to zip through these last few slides pretty quick. If your first effort, first your audience is not persuaded, keep an open mind. Ask questions to decipher their point of view and restate your idea in a different way.
Use your logic and reasoning. That’s super important. If there’s time, practice, practice, practice, research and rehearse your key points. Pets, make a great practice. Partners, dogs, maybe more than cats. Start small.
Use one-on-ones with coworkers or teammates and build support before the big presentation day. And then at the end of the discussion, even if it’s a crisis, make sure that everybody understands the idea and the decision makers have enough information to proceed with their decision. And if there’s follow-ups, make sure that you address those and do the work needed for those.
Okay, so it’s the big day of the presentation. Remain calm. Use your appropriate body language. Like, if you’re presenting to a room, stand up straight. Try and keep your hands from moving around too much. And these are reminders for myself as well. Use your compelling stories with your logic, your reasoning, and your credible sources.
Make sure that the decision makers hear you and you address any concerns that they have. Ask questions if you need to.
Try and understand their point of view, especially if they don’t agree with you right away. And keep a positive and curious attitude after the presentation. Take a deep breath and congratulate yourself even if your idea isn’t implemented. I feel that it’s a win for you because you’ve shown that you’re passionate and you’re creative.
And the next time you present an idea, the folks that have heard you the first time, it’d probably be similar folks. They’ll understand and they’ll say, “Hey, Dotty, she has pretty good ideas. She’s really excited about what she does and she’s creative. Let’s hear her out this time.” I think that that is a positive for you and a win. And plus, you’ll have experience as well and be able to get your feedback from there and tweak your presentation for the next time.
And then with that, I would like to thank you for attending. If you have any questions, please reach out to me over LinkedIn and I think we’re going to be cut off soon, but thanks so much everybody. I hope you’re having a great time at the conference.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!
In this ELEVATEsession,D’Janae Robinson (Chief of Staff at RHJ Consulting) defines what being the first means as a framework, helping identify how it shows up in lived experiences. She shares how the challenges impacting lived experienced (e.g. workplace, family, society), and helps you conduct an inspiring self-analysis of ways to conquer challenges.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!
Good afternoon everyone, and thank you so much, Angie, for that introduction. Happy International Women’s Day. Let’s engage in the chat and tell me one word that describes how you’re feeling today on this Friday. Maybe even three words just to describe how you’re feeling on this amazing day, being a first generation and conquering the unforeseen challenges that arise when breaking generational curses.
For this topic, I want to not just focus on being a first gen in the aspect of academia. I also want to bring in those who are trailblazers. You are the first in your family to navigate a specific occupational space.
Maybe you’re the first entrepreneur, maybe you’re the first in your family to navigate a tech space, or based off of how you choose to identify in all your intersections, you’re the first in your family to say, you know what? I’m picking my career first.
I made the decision. I don’t want children. And that is such a foreign concept, right? As the woman is how I identify, and especially in my community to pick career. Why would you want to do that? Why would you not want to have kids? It’s just a personal choice.
As I navigate through this presentation, I want you to also consider, I am talking about yourself as well. Even though the focus will come from my lived experience, from the small perspective of being a first generation, a two-time, first generation college graduate, before I move forward, I want us to ensure as a diversity equity inclusion specialist that we create a psychologically safe space.
I am here not to change how you were raised, not to change how you believe or not to change your lived experience, but I encourage you to approach this conversation from a different lens and perspective and understand that everyone that’s sitting at this equitable table that we keep talking about has a different lived experience than you.
As I navigate through this conversation and we’re all engaging in the chat to understand that your perspective is valid and so is someone else’s, here are three ways that I conquered and navigated my challenges. We glorify and glamorize being the first. Being a trailblazer. We glorify and glamorize promotions.
Whether you’re the first woman in a specific role, the first non-binary in a specific role, the first outwardly, whatever the case may be, we praise them, we cheer you on. You even have cake sometimes, or a nice fancy plaque.
We do not talk about what comes with the weight, the baggage, the expectations that come with creating this pathway, being the first, being the trailblazer. You are the blueprint.
For me, as a two-time, first generation graduate, my mental health was impacted. I don’t know what it is about getting a secondary degree or being the first, but here I was in a university in a school after already experienced corporate America and came back and I felt inadequate.
I felt like I wasn’t qualified because when I looked around this table, I was the only one who looked like me. I was the blueprint, but yet I was looking for my mentor. I couldn’t call my big mama. In my family, being the first, I couldn’t call my auntie. I couldn’t call my uncle and say, big mama. When you were 25 navigating your secondary degree, what did it do? What did it feel like? What steps did you take and how did you take care of your mental health?
This is what I was able to do. I was able to get monthly massages. One, getting massages, eliminates stress within the body. I was so tense. I was also dealing with weight fluctuation. My hair also was falling out. I did this on purpose. But way back then, in 2020, I believe my hair started falling out.
That is how stress attacked my body. Engage in the chat. How does stress attack your body? How have you navigated your challenges in the endeavor that you embarked in? Monthly massages was one, an accountability partner. I needed a safe space to go to. I needed a friend. I needed a person to call and say the things we ought not dare to say, we should be proud to be the first.
We should be proud for that promotion. But they don’t talk about what comes with being the first. And I was calling her and saying, friend, I want to quit. Today’s the day I want to give up. I can’t do this anymore because I’m searching and I’m searching and I’m looking for someone to tell me I’ve been there. D, just keep pushing.
An accountability partner, they weren’t there to problem solve. They were just there to say, close your laptop, go take a walk, go get your massage, schedule another massage. I love the good cry out method, so just cry it out the other way that it impacts me. Being a first generation of trailblazer, imposter syndrome and me were like, peanut butter and jelly, salt and pepper, green eggs and ham imposter showed up in the work.
Working in two of the top tech companies and being the only one, sometimes that looks like me on my team, I felt inadequate because when you don’t see people who look like you in spaces that you aspire to be in, it can be hard to believe that you’re qualified and equipped to be in a specific role, to be in a specific academia space, as well as my family being the first, I was looking around at my family and saying, nobody else has navigated this path. So maybe I’m weird, maybe I’m different. Maybe I shouldn’t pursue a different path because I’ve never seen anybody else done it.
What did I do internally in the corporate space, I found support groups. I found internal ERGs, employee research groups that I can relate to with other first generation graduates who I was able to identify with and ask them how did they navigate their path as well as therapy. Within the family space, I don’t know about your family, I just can talk about mine.
Going to therapy was still foreign, it’s still taboo. And I’m 30 years old now, going to therapy to seek psychological help, to help me remove whatever that imposter syndrome was in my body. I had to go back to my childhood. Why did I feel inadequate? Why did I feel like I had to work so hard to obtain something to where I was still the only one in the room? And last but not least, my faith as a unapologetic God-fearing woman.
Let me tell y’all what, my faith was tested in a way that had never been tested before. Why? Because I no longer had the environment to look at folks that I wanted to be like. This was all self, this was all about me. I was the blueprint.
I had to call capital GOD, and I said, look, man, this is crazy. You want to pick me? But it’s never been done before. So my prayer life had to increase. Now, if you are not a believer of capital GOD, that is absolutely okay. If you are a believer in energy, in crystals, a higher power, a higher source, I encourage you to tap into that in the moments where you want to give up and the moments where you feel like you shouldn’t be here. And the last thing that I was able to do was I had to trust.
I had to trust that God put me in this place for a reason to be a light in rooms full of darkness. I was called and I had to trust him that I was here to help other women, other non-binary individuals, and to look back and to be the representation I never had. When the younger version of myself comes and says, DJ, I need your help. How did you do it? I can help them.
I understand the power of visual representation and seeing yourself in spaces that you’ve never been in is the motivator. If you look at the top left on my screen in the blue chair, that was the first photo of me working at a Fortune 500 company and being the first in my family to work at a tech company, the photo right below it with me crying in my graduation camp, hugging my aunt, the first of my family to graduate with a bachelor’s degree, the top center photo.
I am chief of staff of RHJ, consulting industry, excuse me, consulting company, and I got this position at the age of 29, so I’m also navigating ageism. I am the youngest person in this role, leading a team of folks who are older than me, but the first in my family to hold such a C-suite level position. The middle bottom one is HBCU. I’m a proud HBCU graduate. Shout out to the HBCU graduates that are on the call. Drop what school you’re representing. I’m representing Houston Tillison University based in Austin, Texas. It is the oldest institution of higher learning in Austin, Texas, and the only HBCU in Austin, Texas. Last but not least, the last picture on my right hand side with President Collette. She was the first black female president of the illustrious Houston Tillison University, and I took a picture along with her as I was the first in my family to obtain my master’s degree.
Now you can see that you’ve become the blueprint. Find people in your community, people not in your community, to be allies. To let you know I’ve done it too. I’ve been a trailblazer. I’ve been the blueprint. And in closing, key takeaways be the representation.
You are the mother you never had. You are the auntie, the brother, the sister, the niece, the nephew. You are the representation you never had. And then instead of thinking, why me, I encourage you to change that perspective and say, why not me?
Thank you so much for the opportunity to share a little bit of my story, my testimony, my lived experience on breaking generational curses and navigating the challenges that occur when you are operating a new path and you’ve become the new stigma, the new representation of your unapologetic self.
Lastly, please connect with me on LinkedIn. If you take your phone and scan the QR code, I would love to connect with everybody. Happy Women’s History Month and Happy International Women’s Day.
What opportunities and challenges have you seen hiring a tenured woman leader where Gen X candidates compete with a younger pool, millennials or Generation Z that might not understand their first, how to align differences?
Yeah, I’m going to share my lived experience as being the youngest in leadership roles. The opportunities that come with that. One is experience and finding allies, an ally.
An ally also doesn’t mean someone that looks like you, but it also could mean someone within your community, so I encourage you, Anna, and please let me know if I’m answering this correctly – Find folks who are willing to drop your name in rooms in which you otherwise wouldn’t have been in.
The reason why also along with my faith that I’m able to be a chief of staff in this position is because myself and a male ally shout out to male allies, he saw that I had a large amount of transferable skills.
I was just missing key variables that I otherwise wouldn’t have access to unless I was at the table, so those are the opportunities, the challenges, and I’m going to be so blunt and transparent, the challenges that occur by being the youngest is people not taking you seriously.
People thinking that you are inadequate or you do not have the knowledge because of your age. Ageism is a spectrum. Whether you are on the, I call ’em wisdom, folks of wisdom, or you are growing in your career, you may have different experiences.
For me, the challenges were I wasn’t taken seriously and I received questioning of my knowledge and expertise in a way that I haven’t seen other individuals on my same team who align in the same age experience.
Angie Chang:
Thank you so much for that talk. That was very inspiring.
Like what you see here? Our mission-aligned Girl Geek X partners are hiring!