Whereas conducting high-quality research is the foundation for data-driven decision making and research operations, the presentation layer is a vector for amplification. Expert-crafted research needs an audience to have an impact. Analysis, presentation, and sharing are how data leads to decisions and impact. Further, while transforming raw data into actionable insights, research teams have an opportunity to tag, organize, and create a taxonomy for future accessibility, covered in the next section.
Data doesn’t make decisions – people do. It’s the transformation of raw data into insight and narrative that motivates action. Many organizations overestimate the ability of stakeholders to adequately synthesize and leverage raw data, which is why analysis is often a ripe area for investment.
Synthesizing qualitative data into insights
The richness of text and video responses 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.
- What does a dire situation look like? Only positive snippets are shared and used to defend decisions. There are rarely decisions made that can be defended by both qualitative and quantitative insight.
- What are key indicators that there’s room for improvement? Qualitative data is summarized but a lack of context about the business objectives limits the amount of analysis and recommendations that would otherwise be possible.
- What does excellence look like? Synthesis includes shareable snippets, broader context with quantitative data, and expert guidance. Interviews are transcribed and tagged for keywords.
Synthesizing quantitative data into insights
The objectivity of survey data is also a double-edged sword, but in a different way. While it can mitigate the risk of cherry picking out-of-context quotes, it also lacks the depth of qualitative data.
- What does a dire situation look like? Charts are analyzed and shared outside the broader context of the survey and participant demographic and behavioral criteria. There are rarely decisions made that can be defended by both qualitative and quantitative insight.
- What are key indicators that there’s room for improvement? Qualitative data is presented thoroughly but a lack of context about the business objectives limits the amount of analysis and recommendations that would otherwise be possible.
- What does excellence look like? Synthesis includes key findings, broader context with qualitative data, and expert guidance.
Insight summarization and deliverables
While synthesis of qualitative and quantitative data is important, reports are the atomic unit of research for many organizations. It’s important to invest in a template that is flexible and efficient but also powerful and persuasive.
- What does a dire situation look like? Reports are tedious to create and slow down delivery. Reports are shared offline (e.g. .pdf) instead of online (e.g. DocSend) so that analytics are lacking. Stakeholders rarely review or use the data for decision-making.
- What are key indicators that there’s room for improvement? Reports are templatized but shared offline, with limited visibility into usage or sharing. Stakeholders frequently cherrypick several data points.
- What does excellence look like? Reporting is templatized and includes key findings and expert recommendations. Stakeholders read reports thoroughly and ask follow up questions. Analysis and decision making is collaborative. Reports are organized and categorized in an insights repository for benchmarking and future reuse for decision-making.
The full research lifecycle must include the impact of decisions informed by the data generated. This is key to how researchers continuously improve, make adjustments, and advocate for more budget.
Recommendations and decision-making follow through
In some sense, researchers always have skin in the game. Every time they make a recommendation, they will be held accountable to some extent for the results. Similarly, if their recommendation is ignored, a positive or negative outcome reflects inversely on their work.
- What does a dire situation look like? The initial learning objectives are never revisited. There is misalignment about the purpose and goals of the research study, and the recommendations are ignored.
- What are key indicators that there’s room for improvement? Recommendations are thoughtfully considered but researchers lack visibility into follow through and impact of decision-making by business stakeholders.
- What does excellence look like? Recommendations are made collaboratively, listened to by key stakeholders, and reviewed by executives.
Measurement and iteration
At a high level, each research study generates foresight into what will happen or hindsight into what did happen. It’s important to do both in order to finetune and improve the process, and ultimately to prove the ROI of an individual study.
- What does a dire situation look like? There are no systems or analytics in place to actually measure results after decisions are made. There is no debrief or post-mortem on key decisions.
- What are key indicators that there’s room for improvement? There is a standardized debriefing meeting after research studies to highlight room for improvement moving forward.
- What does excellence look like? Research studies are revisited after decisions are made to evaluate impact based on KPIs. The research team and business stakeholders debrief on the recommendations to document how closely they compare to real-world results. Future research studies are calibrated accordingly.
How can you improve research in your organization?
Take the Self-Assessment Quiz: Improving Your Research Operations
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