Evidence, Insights, Knowledge and the Rutabaga Analytical Framework

Analytical Framework showing the relationship between evidence, insights and knowledge

In the pre-Rutabaga days of our consultancy, we recognized the necessity of a robust analytical framework. This need wasn’t just about articulating our post-research process in proposals or ensuring internal consistency in training, but also about visualizing research findings and highlighting the web of connections between insights. In some organizations, our frameworks were such a hot commodity that people would end our presentation by calling first dibs on the poster we’d produced.

As we officially launched Rutabaga, we delved deeper through co-design sessions, and truly learned the relevance of our framework in the context of a research repository. At its core, our analytical framework is built on three pillars: Evidence (what we observed and heard), Insights (what it means), and Knowledge (why it matters). Originally, we used ‘Observations’ instead of ‘Evidence’ and ‘Critical Themes’ instead of ‘Knowledge.’ However, continuous refinement based on feedback and research led us to adopt terms that resonated more universally across teams.

We were smart in deciding not to focus our exploration exclusively on researchers, as a fascinating discrepancy emerged as we dug in with extended members of the product team. Researchers and Product Managers (PMs), attempting to communicate the same ideas, often find themselves lost in translation due to differences in terminology. This realization unveiled a significant opportunity: a unified framework could serve as a common language for seamless communication across product functions.

Turning Insights Into Actionable Intelligence

The ‘Knowledge’ layer of our analytical framework presents a unique opportunity to bridge research findings directly with company strategy, turning insights into actionable intelligence. This approach has informed the development of a lightweight data paradigm in our platform, enhancing the findability of information. Central to our solution is an AI chat feature that transcends the pitfalls of traditional, tag-dependent repositories. Where good intentions often give way to inconsistent taxonomies, our platform ensures that insights remain accessible and coherent, fostering a culture of informed decision-making.

Our journey from consultants to platform developers has been driven by a commitment to breaking down silos, increasing transparency and fostering understanding. By embedding our tried-and-tested analytical framework into Rutabaga, we’re not just offering a tool; we’re offering a new way to align teams around shared insights. It’s about transforming individual pieces of evidence into a collective pool of knowledge that informs strategy, drives innovation, and ultimately, shapes the future of products in tune with customer needs.

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