Consultancy Technology Outlook - #3

Self-completing questionnaires

Previously, we saw that text-to-questionnaire algorithms might require additional curation by the consultant. Not so much the curation of the generated questions themselves; rather, the addition of new ones. New items to cover the keywords from the uploaded text that are still missing in the machine-generated questionnaire. Surely, consultants will make mistakes in creating these questions. So, other A.I. will oversee the curation of these A.I.-generated questionnaires. After all, we don't want a consultant downgrade answers to make these less verifiable. A.I. will comment on the consultant's curation to engage in a dialogue that eventually delivers questionnaires that meet the required standards. Compare such A.I. to a spelling or grammar checker.

Consultants might be well-versed in their profession and deliver top-notch assessments. Yet, they may also be somewhat overtaken by the business reality out there. Algorithms can suggest alterations to a questionnaire based on the responses after a certain number of clients. Using that response, so-called factor analysis identifies (and may delete) questions that contribute little to the overall score. Based on the respondents' answer profiles, algorithms design so-called maturity models that are the fundament under automated target setting. A.I. flags questions that need rewriting when respondents deem these questions either too delicate or too sensitive. Simply put, automated consultancy can complete a questionnaire based on the responses it gets.


Test drive benchmark

This benchmark is an extension of the scope bot. Consultants always want to engage in a more meaningful discussion with their clients.  Therefore, the scope bot might suggest one or two mini assessments as a benchmark to gauge the severity of the clients' issue at hand. Simultaneously, the easy-to-use questionnaires wow the client with real-time and already relatively detailed analysis & design. Plus, with these outcomes, the consultants have some concrete handles to start their sales pitch. More clients answered these assessments beforehand so the consultant can benchmark the seriousness of the client's case. Compare this to a test-drive: client and consultant can both verify whether they want to engage in a business transaction.


PRAIORITIZE is the world’s first SaaS platform for Virtual Consultancy. We use artificial intelligence to help organizations digitally transform in a smart, efficient and science-based way. PRAIORITIZE is owned and operated by Transparency Lab, a Dutch employee-owned company. We started in 2008, understood patterns around 2016 and started with generative A.I. in 2020.

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