Designing ResearchOps for uncertainty

Today I wanna talk about research operations and how to design your research operations for this uncertain world. Before we begin, in case anyone is not familiar with what research ops is, Just now you heard about Chanel and and Bhavan trying to design a research session for these disabled people. All the planning that comes up to it, she talks about like procurement and she talks about like, oh, became event planners.

That is part of research operations. So research operations are enablers of research user research. It is the engine behind user research, and it removes these administrative friction so researchers can focus on insights. It's the combination of people, processes, tools, systems, strategies, all of these things that support research so that research can scale.

Before I begin, I would like to acknowledge the Garibwal people of the Eora nation as the traditional custodians of the land on which we gather on today. And I pay my respects to the elders past and present. And I extend their respect to any aboriginal and Torres Strait Islander people today. Okay. AI transparency. I use AI to make my slides, but everything else came from me. Alright. A show of hands.

Because we're gonna go talk about AI, it's important to talk about this. A show of hands. Okay? We're gonna give you three four scenarios. Okay? I want you to think about which of these situations do you think will cause the most chaos. Okay? Four scenarios. Right? We'll have a vote after this. First one, layoffs. So half or more of your researchers, gone.

Bye bye. Sorry. Next one, your repo vanishes. Your repository, your research repository disappears overnight. You think it's crazy? It has happened before. Okay? Your research budget is cut because that you know that happens very often. Or another one that you don't think about but has happened before, your company acquires another business, and suddenly your team doubles overnight. It sounds great.

You know, having more researchers, having more designers, it sounds great. But so, okay. Let's go. Let's go. First one, layoffs. Who do you think is the most chaotic? Okay. Next one, repo. Your repository. Okay. Alright. Alright. Budget cut. I'm surprised.

I am very surprised. I thought budget cut would be the most. Alright. The last one. Your team doubles. Team doubles is the most. Okay. Interesting. Trick question. It's not what will cause the most chaos, but it's about how you want to survive through it. Who cares what which one caused the most chaos as long as you have systems in place to survive through this chaos?

Right? So today, I wanna explore how we can design research ops so that no single change brings everything to a halt. But first, why do I want to talk about uncertainty? I feel like the roads in my life very naturally brought me to this place where I thought that, oh, you know, if I'm very nosy and I enjoy science, I can get paid to become a scientist. And then I went into UX research and research operations, And I started to realize that I am no longer a researcher.

Now I'm a research operations practitioner. I'm more of a systems administrator. What I thought I wanted to be, because then I want I have the stability. Right? I don't have to move countries or states every two years. If you are an an academic, you know what I'm talking about. You also, like, as a as a research ops person, you don't jump around product teams.

Researchers, they always tend to jump around product teams. Sometimes you build you help to build a product, and then they are like, go to the other team, and then you're like, but that's my baby. You know? So I I don't have to jump around. It's great. Like, stability. I really want I just need to make sure that research operations is stable and smooth, and then my life will also become stable and smooth. Right? So I was really wrong.

The more I expected it to stay the same, the more chaos it created. So then I asked myself, do I want stability in my life or is it adaptability and flexibility that I want? When I pitched this talk to UX Australia, I was thinking a lot about the change and uncertainty in my life. And it seemed to me that actually I just really want being able to to be very flexible in my life.

And I saw it in the way of how I should design research operations to be. So let's go back to the start. When does change happen? It can be for a variety of reasons, not just including the ones that I I just gave you, but layoffs. We've talked about it. You know, it's like it's at this point, it's like an annual carnival. I feel like we're so numb to it now.

It's just coming like, every year you're like, alright, it's happening again. Right? Cost cutting, they're always asking us to do more with less. Even with AI, it's like with AI, it's like even even crazier. Re orgs is the most common one I've experienced so far. And they always like to like shake things up because some new executive join and like, let's move things people around.

Move. Move. Move. Right? So how do we design for change? When we assume as when we assume certainty, any change can feel like it's a time for panic. So if change is inevitable, then our operations need to be able to absorb that change. It means designing for flexibility by default, not building processes around assumption that the tools, the people, and the team, and organization will stay the same. Design it so that it can absorb the uncertainty.

The core philosophy I want to introduce you to is on designing enduring principles. A principle is a high level belief or value that guides your decision making regardless of the circumstance. It overarches the way you create your processes. When this uncertainty arises, you can turn to your principles.

And that becomes your compass that helps you adapt while staying true to what matters most. So regardless of whether you're choosing a new tool, redesigning a process, responding to organizational change, enduring principles ensure that your decisions continue to protect your participants, support your researchers, and reduce risk for the organization even when everything keeps changing over and over again.

So let's talk about some key research operations pillars and what it means to have enduring principles. Starting with research governance. Research gov research needs to be governed because when you have a team of researchers and designers who do research, anyone who does research, people bring in their own experience and expertise in. Some people come from an academic background, some come from really fast moving startups, some from design backgrounds, and they've all been taught to be flexible, be creative.

And when all these different types of people meet, they kind of lose their minds a little bit. They bring in different ways of working, different expertise, different specialties. And our job as research ops is to stop them from constantly trying to reinvent the wheel, standardize the way the research is done so that it can scale with quality.

It improves efficiency, it creates trust, and it allows researchers to focus on research. And it also exists to protect your participants. You protect their safety, and you maintain your ethics as a researcher and the organizational compliance or the rules that's been set up for you. So how do we design for uncertainty? The enduring principle here is to focus on what you want to protect. What is your ethics and what are your priorities?

Is it the out is it is it a research output? Is it the value of research that will help improve the digital experience? Or is it the people that you create these experiences for? Build your operations around key principles to protect what you care about. So for me, my priority will always be on the participant. The the participant, the researcher, and the company.

And that is the order I act and protect. Because at the end of the day, while I am a research operation operations practitioner, I am still a researcher, and my priority will always be on the user and the participants. So, I design processes for people. I design my enduring processes for the people who decide, the people who approve budgets, who govern, and the vendors.

I decide the people who follow, the people who execute the processes. So it could be researchers, could be designers, could be product managers. And I designed the principles for the tools that they use, the systems that enable the work. So whenever you design a process, ask yourself, will this survive a reorganization? Is this tool agnostic?

Am I assuming that the same people will always do the same work? Take participant incentives. Right? Decision makers, they are the ones who approve the budgets. Then the researchers and the research ops people, they issue the incentives. And then the delivery tool is the one that that you use to deliver the the the incentives. Could be a gift card platform.

It could be cash. It could be merch. It could be anything. So, the enduring principle isn't use this tool. Get approval from this person. Do all these things. It's the design of the whole process. It needs to explain why this process exists. What problem is it solving? And why do we let people do it the way we want them to do? And how do we make this process last through any change? But while I talk a lot about depending on people, I mean it as a whole.

Build your research team. Build research team's maturity. It's building your research team's maturity is a team effort. So think about what each person's per specialty is and the knowledge and the skills that they bring with them and how that disappears when they leave. Are you able to continue as well? If it depend on one or a small handful of specialized individuals, your systems will crumble the moment a change is initiated.

The solution is documentation. I've been in organizations that document everything and also organizations that don't. Guess which one bounces back quickly when a major change happens. How how fast does it go back to being productive? And guess which one is more resilient, more agile? This might sound very obvious, but unfortunately, it's a lot said than done. And it's very very very dependent on the team on the organization's culture. Changing a culture is very difficult.

It's very scary as well because the moment you initiate change, any sort of change, people if people don't like it, they will think that, oh, you're not a very agreeable person. You're hard to work with. Right? But documentation will ensure continuity. And it's not simply just about documenting it. It's about managing that knowledge as well. Is it in one place or is it in multiple places?

Not just talking about insights and repository. I'm even I'm talking about the processes, the operation processes that and the initiatives that you create. You need to differentiate front facing research operations, content with back facing works in progress, consolidate in places that make sense and it's easy to get to as well. So it's one of those enduring principles that you need to to fight the uncertainty. Start small, drive the change, ask for documentation, and then put it in the right places.

Provide people with the tools to do all these documentation, and make it as easy as possible. You can also provide them with AI tools. I know what you're thinking. Oh, she just wants us to train AI models. You want you she just wants us to do all these documentation so that the AI models can be trained and then we will all be out of her job.

The company wants to replace all of us with with AI. And, as we've heard this morning, it's not happening soon. So, I get it. I I I get so many like AI job offers nowadays on LinkedIn asking me to train AI models. Like, I don't like it as well. But it has brought us so much uncertainty to the way we do research now.

But again, lean into the enduring principles that you set out for yourself and your operations. It's your research rigor. It's your research skills. Your human judgment. These are the enduring principles that nobody can take from you. Use AI to accelerate your skills and operations, but keep your ethics and your judgment. Differentiate yourself from a machine.

We're still in the business of people. And what makes you different from an AI researcher is your ability to connect with empathy to another human. Be a rigor, improve your skills, learn to identify nonsense, all the slop that's been drip that's been created, and be the one to refine these methods as well. Use AI as a tool to showcase your humanity and your irreplaceable skill set. It's just a tool.

Tools are not very flexible. But your approach to tools can be flexible. Focus on the people who use the tool. Design for enduring principles in a way that you use the tool, for the people who use the tool, and for the people who create the tool. It's not always going to be experienced senior researchers you work with. It's not gonna be these people who use the tools, because tomorrow, reorg, suddenly product managers are doing research.

Suddenly, the c suite people are doing research. I don't know. Design for all levels of expertise because even if your team has experienced researchers, it will benefit everyone. Like, when you design for edge cases, it benefit everyone. It's the same thing with these sort of tools as well. So, it forms an enduring principle because the people and the teams using the tools will change tomorrow, six months, one year.

Who knows? Right? Choose the tool that gives the team room to move. When it comes to tool changes from my experience is that the best way to deal with tool changes to move from one to another is to lean very heavily on the tool's customer success managers. I find that they are the best. They are going to be our best friend when it comes to navigating tool changes, data migration, change management.

They have gone through it all. They have worked with so many of their clients to change tools. So if you need to change a tool, lean very heavily on them. They will support through it. Make it make it clear from the start that when you are going if you are going to get their tool, if you're going to buy their tool, they need to firstly take that change.

They need to expect you need to they they need to expect that you will lean on them. And a good customer success manager will make a world of difference. So, your operating model won't collapse the moment you say, hey, let's go for this other tool. It's cheaper, it's better, let's go. Right? So, I talk a lot. How much time do I have a lot of time?

How much how much I talk so much about changes and uncertainty. Right? But, what should be permanent? Ethics, privacy, consent, legal, the sustainability of your operations and the efficiency. Your principles as a person and as a as a researcher should stay the same. So, which means always prioritizing the participants' rights and comfort and their experience.

That's the basic ethics of research. Treating your participants like a decent human being regardless of what company you work for, what your boss wants you to do. Don't waver in your ethics. It makes you human. And, when you find yourself in a situation, if you find yourself in a situation where you have to, every good company has a speak up hotline, they have ombudsman, they have ethics and compliance teams.

So, work closely as a research ops person, I do work very closely with research and ethics teams Or if they don't have that, usually it's a legal or privacy team. So when you're and during when designing for these sort of processes and all these principles, a lot of times they will set the rules on how you should operate.

So it's very important to work very closely with them, whether you're a researcher, research ops, or anybody who does research. Ah, I finished early. Okay. So, research will always be chaotic. Alright. The we've talked about, you know, making sure that your ethics stay the same. Have having research rigor.

All these budget and tools, they will shift continuously. But research ethics, participant care, human critical thinking, keep it the same, keep it there, keep the standard high, build the systems that will outlast individuals, avoid reliance on single heroes by creating clear governance, Create shared tools and explicit shared principles for decision makers and for the people who do research.

Design for uncertainty by default. Don't fight the change. Structure it such that when something changes, you can sort of move. Have you seen one of those like in Japan, like when they have like those buildings that move with the earthquake? And then they have those things? Yeah. Oh, I should put a git I should put a little video there of that, of the building just shaking.

So, structure your your your research ops like that. Making sure that like, if the the ground moves, you sort of move together with it. So that you can go back to doing the really good research that everybody has been doing, and then you can go back to being business as usual. Thank you. I I I'm early. Yay.