15 Minute Read
When a research team finds itself spending too much time fielding 1-off questions, sharing 1-off access to research data, or doing administrative tasks that impede doing research, it could be time to introduce research operations.... and its close cousin research enablement.
If you come from the technology industry or a business background, then you may have already heard of marketing operations, design operations, or sales operations in your organization. With user-centered design becoming more of the standard for great products, research operations has also solidified itself as a growing function in the product org.
But what is research operations? How does it relate to research enablement? How do you know if or when to start thinking about research operations for your product research team?
This post dives deeper into these topics, but first let’s start with a more classic example to build a reference: Sales.
In the business world, sales operations is a company function that refers to the people, tools, and processes of the sales org that are devoted to ensuring a smooth and effective sales motion.
This type of 3-pronged approach might include things like supporting accurate pipeline reports, getting sales reps to track certain types of data in a CRM, and even setting up new integrations or workflows that help make sales peoples' jobs easier.
Sales enablement, while part of operations, is a more focused niche of the sales function that focuses not just on the sales process, but on effectiveness and performance, ie making better sales people. Sales enablement efforts might include things like producing assets like 1-pagers or demo decks, to coaching sales reps on how to ask good questions during discovery or handle objections. At its heart an enablement effort involves investing in teammates to hone their skills and optimize their sales performance.
As a sales team grows, the greater the needs of operations and enablement. The better operational support a sales team has, the greater the potential is for higher productivity and performance.
Sales operations and sales enablement go hand in hand. Let's learn how research operations and research enablement compare to this example.
Research Operations refers to how an organization optimizes the people, tools, and processes involved in research. A research ops program looks at different ways to streamline research activities and maintain budget while spending money on tools, software, people, incentives, and more.
A research operations program aims to make all activities related to research more accessible, consistent, and effective. Research ops also helps organizations leverage research insight for creating better designs and making faster decisions.
A research ops program usually sits across a team of researchers who are embedded across different product teams or pods. Depending on the size and type of organization, research operations could be a centralized but shared function or it could be decentralized or autonomous. Regardless of how research operations fits into a company's hierarchy, there are 6 main focuses of research operations, including:
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Research enablement isn’t just about managing researchers and processes, but rather about creating better researchers. For better or worse, it is increasingly common for people who don't have researcher titles or research training to do research in their roles. For example, designers doing user research or product managers doing market research. For some, researcher is their title and main job function, but for others it might be a skill or a hat they must wear as part of a broader set of responsibilities.
Research enablement might not just be about providing support for a team of researchers, but extending that support out to other members in the company doing research. Instead of setting up the process of research as steps employees must go through, enablement goes a step further by focusing on skills, such as the art of asking good questions, how to recognize bias, ways to analyze data, and more. Research enablement also speaks to the cultural effort of building understanding and appreciation for research across various types of stakeholders.
For research enablement research leaders work closely with members of the greater product team: like managers or designers, as well as their own researchers. Some essential tasks in research enablement may include: establishing standards, advocating for the user, developing research strategies, coordinating training and continued education, and looking for opportunities to bring even more stakeholders into the research fold.
Research enablement is close to an ongoing debate in the research industry: should non-researchers do research?
At the heart of that question is deep issues such as whether poorly conducted research is better or worse than no research at all. It also begs the question whether inviting stakeholders to do research delegitimizes research as a specialized skill. If anyone can do research then why hire trained researchers?
Or, on the flip side, is the more, the merrier true in research? Is an organization where lots of stakeholders feel the contagious need for more research and want to be involved whole-heartedly, actually a net positive for growing the research function with more buy-in and a bigger impact?
Like most complicated questions the answers are: it depends.
From our perspective, yes, anyone can cook. Anyone can do research. However just because it's possible for anyone to do great research, it doesn't mean it's an inherent skill or that all research will be created equal. Sometimes good research will do when the resources for great research aren't available. And yes, bad research can lead to disastrous consequences that can derail companies, hold back industries, and cause great harm.
A role of research enablement is to empower highly trained researchers and research leaders to enable organizations to better navigate these scenarios and tradeoffs, to strike the balance unique to their organizations, and keep standards high in the process.
Check out this conversation we hosted about research democratization to take a deeper look at the ongoing debate around who should (and shouldn't) do research.
Now that we've covered research operations and enablement, let's explore some of the primary benefits of implementing these functions in an organization, including:
Every research team faces resource scarcity. Increasing productivity and speed isn't just for the sake of capitalist efficiency. Allocating research resources most effectively increases the impact of research, which in turn improves credibility and influence. This ultimately cycles back to making a stronger case for more research and increasing research budgets. This case always starts with being good stewards of resources, especially time.
Time spent fumbling on repetitive and administrative tasks without support or process is time that could be better spent doing research or, our personal favorite, marinating in data. The more structured and repeatable administrative motions are, the easier it is to kick off research and focus energy on the work that matters most.
If a tree falls in the forest and no one is around to hear it... did it really fall at all? If research insights aren't accessible, then the impact of research is stifled right out of the gate. A goal of research enablement is making sure that relevant stakeholders have access to research data and insights, when and where they need it. A focus of this work usually involves setting up a self-serve workflow where stakeholders can search or access information as-needed, rather than relying on 1:1 questions or random calls for aid in group chats.
Equalizing access to knowledge levels the playing field for new researchers or teammates and makes it easier for tribal knowledge to freely flow through an organization.
A huge value of research operations or enablement is the ability to draw what we call "macro" conclusions or patterns across research knowledge over time. To do that requires a small amount of consistency and structure, which usually doesn't evolve organically but is rather designed intentionally.
Data ownership and governance, brought on through research operations, not only helps researchers work with data consistently and effectively, but also helps researchers confidently work with and store data in a way that complies with ethics and legal policies.
Finally, a research operations department is responsible for managing the research budget. There are many components of a research budget from employee salaries, software, recruiting, and participant incentives. Having a bird's eye view of the research budget and various allocations is needed to understand how the demand for research is growing and for measuring the impact of research or ROI (return on investment).
A dialed-in research budget with granular expenses can be a big help when you're looking to cut costs, advocate for more hires, bring on new tooling, and more.
Research Ops has many advantages, but there are also challenges and hangups to avoid. For instance, in theory research operations aims to create consistency in workflows and structure around the process of research. In practice getting an entire team or teams to adopt processes and guidelines is another story.
Below are practical tips to introduce and scale research operations.
If you're just starting a research practice from scratch, the weight of a research operations function can feel overwhelming. Don't go at it alone. Recruit believers and work with allies to invest toward making research accessible to a broader group. Teach. Share. Demystify. Motivate. Inspire.
One of the biggest reasons organizations struggle to adopt a healthy research function is that stakeholders feel intimidated or confused by the work of researchers. Focus on small, simple research skills and habits that build a foundation for learning. The less you tell or teach, and the more you show and do, the faster mutual trust and respect for the practice of research is gained. Help yourself and your team build a sustainable practice by focusing on small, attainable research habits. Aristotle once said that we are what we repeatedly do. He also noted that excellence is not an act, but is in fact a habit. It's the same with research. Excellence is not achieved in one single study. Rather, it's about analyzing habitual acts of research and using those findings to improve the experience over time.
At first it can be tough to convince people to shift from their workflows and practices to a new approach... or tweak tools or process to make accommodations. And sometimes, maybe as you're just getting things dialed in, the landscape shifts or the team evolves and even the new approach no longer fits. This constant tweaking and nurturing is par for the course. It's not necessarily a flaw of the system as much as it may be a signal that the system is being used and evolving.
Research operations, even with a dedicated leader, is still a team sport. For that reason it will always be a work in progress and the work is never done.
The role of effective research operations isn't just about creating and maintaining order, it's also creative and political. There are many business objectives to grow the research function: to reduce risk, to gain clarity and momentum, to focus on the right things.
But depending on the maturity of research in an organization, building and advocating for research operations can require various levels of creativity and persuasion. Often "Why we need research" and "Why we need research operations" will be among the first two stories to tell... but when done well certainly not the last!
On a macro level a good research operations function uses stories and data to relate business outcomes to research, covering wins, losses, and even mistakes that were avoided as a result of research-led insights. And on a micro level research operations can help individuals conducting research to hone in on their storytelling skills, making it easy for them to follow compelling formats, incorporate rich data and experiences, and work closely with teams to tweak the messaging styles to those that work best across channels.
Every researcher desires for their work and insights to have an impact. Every research department ought to be measured by their team's collective impact. Storytelling is what takes good research across the finish line and makes it great.
To summarize the importance of storytelling we will leave this section with a quote from Maya Angelou, "I've learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel."
Another aspect of kicking off research operations is to choose a leader who has ownership over the research operations domain. Depending on the size of the organization, this might fall under Design Operations or the responsibilities of a designer or it could be a dedicated role that oversees the operations within and across teams. For a research practice that is just getting off the ground it's common (and effective!) that research operations is more of a shared function than a dedicated role. While it's preferable to have a dedicated owner who has final say over operational practices and process, it's not a requirement. As long as the functions are identified and documented, operations can also be a shared function until the team or budget evolves to support a dedicated role.
The important thing is to have clear ownership and responsibilities, even among a group of peer researchers. When research has grown organically many of the research operational tasks are shared by default or left to independent researchers. Centralizing ownership and formalizing process unlocks new potential and gives creative license to start formally growing not just research operations, but research as a whole.
Identify ways to introduce continuous research to your organization. These always-on, more bite-sized research initiatives are easier to get off the ground and usually the stakes are lower, making it easier to collaborate with stakeholders. At any given moment there are sources of feedback, conversations, and incoming data feeds that are ripe for analysis with a research lens.
Identify the people, process, and tools needed to support continuous research. Continuous research can increase the knowledge around repeatable flows such as onboarding or purchases or find insights around new initiatives such as improving a customer support experience. With a Research Enablement mindset, we can think of research as a constant stream rather than a faucet of information that is turned on and off at any given time.
By showcasing how quickly data can be collected, analyzed, and reported in a continuous way, research will feel more like an embedded function and supportive role, rather than just another step in the process or a bottleneck. Speaking of bottleneck, this article by Ryan Anderson does a great job illustrating the point that research isn't a bottleneck, it's a decanter. We love the analogy and agree with the sentiment that research isn't about restricting the flow of design or product development, but rather about ensuring better, faster successful outcomes.
Notably, is a single platform that helps teams collect, analyze and share research. It ensures better and faster analysis so that companies can improve their research practices and make a greater impact with research. Import raw research data, collaborate during analysis, and track participants with consistent documentation to support research operations.
Not only does Notably have research operations best practices baked in, but our team of trained researchers uses what we call the research maturity model to help our customers on their path to launch research operations and invest in research enablement.
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