Skimle is the Excel for text

Would you trust a calculator's number for a €1 billion decision with no visible workings... or use real tools? We think qualitative analysis deserves the same rigour as a quantitative.

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Would you trust a number from a calculator for a high-stakes quantitative decision? Or would you want to see the spreadsheet, with its assumptions, formulas and sensitivity analysis laid out?

At Skimle we are advocating applying the same standard to qualitative research. Instead of a black-box chatbot spitting out themes, or someone skimming the material manually, you can now analyse it rigorously with an AI-assisted workflow modelled on the academic methods for thematic analysis. With Skimle, you get full transparency, manual control and the versatility to analyse your data the way you actually need to.

The calculator problem

Olli's point in the video is a simple one: nobody makes a billion-euro decision off a single number typed into a calculator. You want the interim steps, the assumptions, a team that can look at the working and agree the answer is right. Qualitative research routinely informs decisions of similar weight, yet it is often handed over the way a calculator hands over a number: skim 50 interviews or a thousand customer comments, or paste them into a chatbot, and accept the three or four themes that come back.

With ordinary tools, you cannot go further than that. With Skimle you can look at every coding decision, every category, and every individual verbatim quote, see exactly what people said and how it rolls up into the summary, and freely edit any of it. You never have to accept the AI's answer as final: recode manually, change the categories, and stay in control throughout. When you are done, export the results in the format you actually need rather than copy-pasting text out of a chat window.

That is the Excel-for-text argument in full: a spreadsheet earns trust because every cell traces back to a formula you can inspect, not because the final number looks plausible. We think qualitative analysis deserves the same bargain, and it is the same case we make in more depth in our design criteria for AI-assisted qualitative analysis tools and in two-way transparency. For the full tour of everything else the product does, see what is Skimle, which pairs our product film with all 15 features.


About the author

Olli Salo is a former Partner at McKinsey & Company where he spent 18 years helping clients understand the markets and themselves, develop winning strategies and improve their operating models. He has done over 1000 client interviews and published over 10 articles on McKinsey.com and beyond. LinkedIn profile

참고: Signal & Noise 글에는 AI 도구로 작성, 편집 또는 번역한 텍스트, 동영상, 이미지가 포함될 수 있습니다.

Skimle로 데이터를 더 깊이 파고드십시오

Skimle은 인터뷰, 설문 응답, 보고서 등 질적 데이터를 자동으로 수집, 분석, 분류합니다. 현대적인 질적 분석 소프트웨어로서 엄밀하고 투명한 워크플로와 AI의 속도를 결합합니다.

텍스트나 오디오를 업로드하고, Skimle Anonymise로 민감한 데이터를 제거하고, 카테고리와 하위 카테고리를 자동으로 만들고, 문서 전반의 데이터를 탐색하고, 워크플로에 매끄럽게 맞도록 데이터를 내보내십시오. 전문가가 전문가를 위해 만들었으며, 완전한 개인정보 보호와 GDPR 준수를 갖췄습니다.

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