By now, virtually every organization left standing has completed an agile transformation to some extent. You’ve reorganized around customer segments and jobs-to-be-done, you’ve invested in research leadership and fostering a culture of customer-centricity, and you’ve outlined key market trends and opportunities. Now it’s time for the hard work to begin: actually making decisions to innovate and grow.
The problem is that the tools of yesterday won’t meet tomorrow’s needs. Building digital solutions is fundamentally different from building physical solutions, requiring a different set of research tools and technologies.
Traditional Research vs. Agile Research
Whereas physical manufacturing involves significant upfront costs and strategic decision-making, digital products can be shipped iteratively. For organizations building digital products, this nuance dramatically impacted decision-making workflows, as most one-way doors essentially became two-way doors.
Agile transformations exist to enable teams to more effectively iteratively develop and test solutions. This impacts researchers and the tools they need in three meaningful ways:
- Risk tolerance: Whereas decisions in an analog world are often irreversible (you cannot move a factory after building it), digital products can be changed quickly. Therefore, the risk involved in decisions shifted from avoiding being wrong to avoiding being slow.
- Timing of decisions: Because digital products can be changed continuously, investing in continuous improvement can dynamically redefine the competitive landscape. Instead of investing almost exclusively in upfront strategic decisions, decision-making is distributed throughout the product development lifecycle.
- Number of decisions: As a function of the first two points, there is an order of magnitude more decisions that are made in digital product development than there ever were with physical product development.
The above factors have placed an inordinate amount of pressure on research teams to suddenly “keep up” with product teams that are otherwise “flying blind.”
Research toolkits that balance quality and velocity
While decision-making in agile environments requires speed, quality is of course still a critical factor. Fortunately, substantial venture capital has been poured into the research tool market. In the following five broadly defined categories alone there are 500+ tools:
- Market research: Primary research to better understand trends in a market at large. See a list of market research tools →
- User research: Primary research to better understand the impact of existing and proposed product experiences on cohorts, individual users, and prospective users. See a list of user research tools →
- Voice of customer: Ongoing data collection to quantify and track the impact of predefined touchpoints on cohorts and existing users or customers. See a list of voice of customer tools →
- Analytics: Ongoing data collection to quantify and track events across digital experiences. See a list of analytics tools →
- Syndicated research: Third party research and data about various trends and topics. See a list of syndicated research tools →
All of this is to say that on top of exponentially more decisions that need to be made within an organization, there are also exponentially more tools and technologies that research teams need to consider and master.
This is in large part why we’re seeing the emergence of Research Operations (ResearchOps). Put simply, ResearchOps is a set of practices that combines research techniques, technology solutions, and processes in order to transform research into a repeatable and scalable system that serves the decision-making requirements of the organization.
Research teams need to construct a toolkit that meets the evolving needs of the organization. While that varies from organization to organization, here are three capabilities to invest in first:
Qualitative research at scale
Interviews can be tedious to conduct but incredibly powerful for developing empathy within an organization, particularly amongst executives. Consider investing in unmoderated interview capabilities to scale your qualitative research.
Data doesn’t make decisions – people do. It’s the transformation of raw data into insight and narrative that motivates action. However, many organizations overestimate the ability of stakeholders to adequately synthesize and leverage raw data.
The richness of text and video responses for example is a double-edged sword. It has the power to facilitate empathy but also to be taken out of context or used as an isolated data point to reinforce a foregone conclusion. Consider investing in a transcription and report generation capability.
Redundant research is often conducted because of a lack of a centralized and digestible insight repository. Only a handful of people are aware of any of the research going on in the organization, and the information primarily lives within their heads. Similarly, when decision-makers need insight, they have no way of accessing previously conducted studies. Insight repositories solve this problem and are one of the most exciting new technologies in research.
Introducing ResearchOps tools
At Tetra Insights, we work with organizations determined to achieve Research Operations excellence. To learn more about the emerging tools and technologies required, download our report on Leveling Up Your Research Operations featuring data from 100+ corporate research teams.