Dummies Guide to TalEction
| Data Collectors and Digital Twins | |
| Matchmaking and AI Algorithms | |
| The TalEction Platform | |
| The META Perspective |
| The Key Principles | |
| Scenario: AI Recruiting | |
| Scenario: Career Advice | |
| Scenario: Readiness |
Click through the slides above on your own, or watch this video where I walk you through the presentation.
Data Collectors and Digital Twins
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| A Data Collector is a tool used to gather data about You or a Job/Company ex. a personality test, intelligence test, culture survey, games etc. | |
| A Digital Twin is a virtual representation that serves as the real-time digital counterpart of a physical object (you, job, company). | |
| TalEction use Data Collectors to build (fill) Digital Twins (with data). |
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Matchmaking and AI Algorithms
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| TalEction uses Digital Twins both on the Employer, Job (context) side and the Employee, Candidate (you) side. | |
| TalEction has developed a number of functions that match elements of the Two Digital Twins with each other. | |
| The Matchmaking can as an example say which personality trait fits well with a certain team role or organization culture. | |
| TalEction uses both traditional Statistical and AI models, functions for the Matchmaking functions. |
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The TalEction Platform
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| TalEction has built Products and Services around each of the Digital Twins in isolation in addition to on top of the Matchmaking Algorithms that connect them. | |
| Examples of Digital Twin based services are Career Advice, Smart-CV, Company Consistency and Indexes. | |
| Examples of Matchmaking based services are AI Recruiting, Readiness, Right-Sizing. | |
| TalEction has also developed foundational services like Sharing, Smart Search in addition to data analytics services and research. |
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The Meta Perspective
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| ERP/HCM Systems support HR in solving tasks administratively and embrace fixed set-ups - driven by forms and aim for documentation of work performance. Employer produce work skills. | |
| TalEction supports Talent Management in solving tasks strategically and embrace growth set-ups. The solution is driven by AI and aim for documentation of learning. Employers produce Learning Skills. | |
| We need both systems to meet both formal obligations and informal expectations in the future. |
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The Principles
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| Tools for leadership and governance of knowledge workers. | |
| Recognition for knowledge and the ability to drive your own development. | |
| Management must govern employees on results (output) or effects. | |
| The new (digital) economy must be based on platforms, artificial intelligence and digital twins. | |
| Enhanced Privacy: the individuals own and manage their own data. | |
| A learning system with a focus on lifelong learning, learning skills and culture. |
| Creates a basis for developing learning-based measurement indicators (KPIs) | |
| Platform should cover: recruitment, organizational development and mobility, change management, training of mental skills and workforce optimization | |
| Collect structured data for the Digital Twins that opens up for simulations and automated analysis. | |
| Individuals and Companies must have full access to own data to run tailored analysis and potentially develop bespoke AI. | |
| The solution must be intuitive, easy to integrate and based on self-service. |
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Scenario: AI Recruiting
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| Recruitment is about Reaching as many right talents as possible and then Selecting the best fit for the job in question. | |
| Step 1, Job Analysis: Use Data Collectors to create a Digital Twin for the Job and generate job profile, recruitment project, campaign, candidate landing page etc. | |
| Step 2, Selection: Candidates complete tasks to apply and build their own digital twin - the platform automatically calculate match score with Job digital twin and recommends best match. | |
| STEP 3, OnBoarding: Re-Use digital twins and match algorithms to generate onboarding tasks and contextual recommendations (success path). |
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Scenario: Career Advice
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| Step 1, Populate Twin: Use Data Collectors to populate your own Digital Twin (personality tests, intelligence tests, cognitive flex test, skills detection games etc.). | |
| Step 2, Simulate: Use your Digital Twin and apply AI Algoritms to Simulate Career options and choices (jobs, functions, industry, sector, maturity, team role, culture etc.). | |
| Step 3, Get Advice: Run our Advisory services against your own Digital Twin and get an instant analysis and associated recommendations. | |
| Use our advanced search and sharing functions to interact with others. |
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Scenario: Readiness
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| Readiness is about identifying the likelihood of a group of individuals being able to successfully implement a change. | |
| Step 1, Populate Twins: Use Data Collectors to populate digital twins for people involved in the change and for the desired target state. | |
| Step 2, Analyse Gap: Apply AI algorithms to the people twins against target state twin - establish gap and recommendations. | |
| Step 3, Develop Plan: Use identified gap and associated analysis to develop targeted road map (plan) to reach desired target state. | |
| Re-Run process to identify effect of implemented road map. |
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Get Started
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I just want to use it for myself - build Awareness, Smart CV, Simulate, Get Advice etc.
Free (no cost)
I want to use it for my company, many people - Run Recruitments, Assessments, Readiness etc.
Paid Service (cost)
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