Human Skills 004 - How Clarity Helps Negotiation
Human Skills 004 - How Clarity Helps Negotiation
with Tim Lu
I wasn't expecting interviewing a data scientist to turn into a master class on negotiation, but that's what happened. Clear, concise, and memorable approaches to think about how you demonstrate the value in your work and ask for what you want.
Perhaps I should not have been surprised. Tim Lu is described by many of his colleagues as the most thoughtful Data Scientist they know. When I have been asking around for good people to talk to on this subject, he has been the first person mentioned again and again.
In this interview, he shares incredibly practical and easy-to-apply approaches to communication, negotiation, and an elegant and systematic approach to learning that blew me away.
How does your nontechnical background help you now in Data Science?
I would point back to when I was twenty three years old and traveling with the CEO of a thirty five year old organization that made tens of millions in revenue every year and that delivered surgery to hundreds of thousands of children in its history.
And you might imagine that this founder of this non profit organization, if I had to sum him up in one word: visionary. Because he knows how to move the heart into action.
And I can remember being along his side speaking with millionaires asking, telling them about the programs that we were rolling out and how they could become strategic partners with us.
And he always said, I know the narrative I need to tell based off of the five fingers on my hand. And he holds his hand up and he says, "What's - in - it - for - me?"
That's all you have to do. You have to think through with empathy. What does your counter part get from what you are saying.
And I just remember thinking that is incredibly simple, but it was the kind of advice that kept coming back to me year after year after year.
And so, translating that now to this transition to data scientist, where there's a lot of things I need to learn from a technical standpoint, but the thing that I kept anchoring to was: "What is in it for the receiver or the beneficiary of my data analysis? What will they care about?"
And if I start there, which maybe, resonates with a lot of how how engineers think about this: reverse engineering, starting with the outcome we desire, and working backwards. It was the same thing. My end point was, "What is the insight or the takeaway that I want my counterpart to understand, and then working backwards there."
How do you approach negotiation in the workplace?
I was in a negotiation class in graduate school, and the teacher on day one asks "who here loves negotiating?" and absolutely no one raised their hands. And these are all like type A people who love getting after what they want.
And then finally one person raises their hand and they've got a little bit of a half smile, And they say "I learned everything I needed to know about negotiating from playing Settlers of Catan"
And there's a lot of truth in this statement, because negotiating in the sense of Catan is really just understanding what are the dynamics of our competitive domain, seeing and seeking to understand what are the needs of your counter part, and trying to find alignment in as quickest, efficient and transparent and trustworthy way as possible.
That's what we're doing. And sometimes there's a little bit of like back stabbing and backdooring involved. We try to avoid that, but sometimes it's necessary. But I think what's counterintuitive intuitive about negotiating as we think that we have to be like stealthy. Like this sly ninja, where we're going to Jedi mind trick our counter part, and that's just not the case.
You just have to say, "I want two wheat for one wood, would anyone be willing to help each other out." And if you scratch my back, I'll scratch your back.
And so it's a matter of surfacing information in a way that builds trust with each other. And so, I suppose when he said that he learned everything from Catan, he actually did really well in the negotiation class.
I think the same thing applies in an external sense. If you're going to a company, you have to say, "Well, here are my expectations for this job, giving the scope and responsibilities that you've defined and the impact that I thing I can have. And here's the range based off of the research that I found. Is this something that that your company can do?"
So again, we are trying to not be stealthy or sly, but provide information to be able to signal trust to our counter part.
In the context of work. Let's talk about a perhaps the most important stakeholder that you're going to have on the day to day, which is, if you're an individual contributor, your manager.
So how do we actually negotiate with our manager? And maybe it's not compensation, but maybe it's a promotion. Maybe it is carving out a fraction of our time to be able to pursue a project that aligns with the ways in which you and I want to grow.
And so I think again, the principles of negotiation are very similar. We have to one, do our preparation. And I think that's what ninety percent of people forget about negotiation. We just go into it sort of haphazardly and say "here's what I want, and if you don't give it to me, I'm going to walk away."
That's the lazy way to approach a negotiation. The way to go into a negotiation is to say "Here is what I anticipate are going to be the objections to what I want from my counterpart, and actually to enumerate them." And then in my preparation I will have my rebuttals for each of those so that I can enter into this conversation proactively, and be able to surface those in a way that is non-confrontational, not guns blazing.
Just saying, from a point of transparency, "I think that I would like to pursue this side project with about twenty percent of my time. And perhaps three of the concerns that you would have would be One: will this detract from my team? Two: will this get in the way of some of the more priority projects? And three: is this actually aligned to the business? For each of those, I've done some pre thought, and I invite your perspective on that, but here are my takes on that"
And so now your preparation has enabled you to go and proactively address these potential objections with your counterpart, all in a way that fortifies trust, provides transparency and allows you to get to a higher third path with your counterpart, which is not just yes or no, bu they're now going to want to find a way to help you, because they know how invested you are and you just gave them the grace of providing you of providing them with information.
How do keep yourself continually learning?
I love this question, and I'll tell you that when I went to go spend on my tuition for graduate school, it was in the hundreds of thousands. And I'll tell you that hundreds of thousands gives you a return, not when you figure out what you learned from that investment, but you when you realize that you learned how to learn from that investment.
And so in graduate school I went to a program where its educational philosophy was based on the Socratic method. Any of your listeners who aren't familiar with the Socratic method - It is a style of learning where we are in this auditorium style room where we're looking at each other, and we are just basically bouncing questions from one to the other.
And so that's really the starting point for my framework for learning. It has to start with a poignant compelling question.
The way I've operationalized this in my life as a data scientist is that, because there are so many things to learn, I have step one which is: consume a piece of content that sparks joy and energy every day.
And it might be for five minutes, or I might go down the rabbit hole, and it is an hour, but spend time consuming a Youtube video, an article, a news letter, a textbook even...
And step two: Once you consume that, inevitably something will make you go "aha". Your eyes will light up. Your brain will start moving its wheels, and you'll say "I did not realize that."
And at that point, that's where question actually comes into reality. I take that insight and I form a question out of it. So I did this the other day. I was reading about machine learning systems and I said "Wow, look at all of these methods." Maybe if I would have formed a question, I would say "What are the most predominant methods used in machine learning today?"
And I'll write that question down on. And I'll write a brief summary, two to four sentences, in the form of an answer. And so I've logged this as basically a Q&A, this new insight.
Step three then is to review it. I save it in a tool... you can write these things down on paper, I like to use software. There's a great tool called ReadWise out there, where I now log this new question and answer insight that I've just created for myself and I'll have it on repeat cycle.
And so every day I go in and I'm repeating things that I've read and learned. And what it allows me to do is it, over time it compounds that knowledge, resurfaces it so that I don't forget it, and gives me a structured way to receive that information in the form of a answer to a question that I've already identified as important.
And that is how I've gone about learning new technical methods, imbibing different philosophies and frameworks that are not necessarily technical, but being able to codify them into a system that I can then repeat and build over time.