TalentOperations.io is a practical knowledge base for consulting firm leaders who need to make better decisions about talent — faster.
A structured framework for understanding and managing talent operations in knowledge-intensive consulting firms. The content is organised into seven decision areas — from demand forecasting and competency architecture to talent economics and operating model design.
Each page is written to help you make a specific decision, not just understand a concept. Every framework includes a concrete example using a canonical case company, an action checklist, and a list of the exact decisions it enables.
Primarily written for COOs, CFOs, and CEOs at consulting firms with 50–500 people. These are the operators who own the decisions that connect sales commitments to staffing realities to financial outcomes.
The frameworks also apply to Heads of Delivery, Talent Partners, and senior recruiters who need a structured way to think about capability and demand — not just individual hires.
The benchmarks and examples are calibrated to the Nordic and Northern European consulting market. Revenue figures, salaries, and day rates reflect Finnish and Scandinavian market norms, not US or UK defaults.
If you are new, start with the Talent Operations System section — it frames the whole approach and explains how the seven areas fit together.
If you have a specific decision in front of you, go directly to the relevant section. The knowledge base index lists all seven areas with a short description of what decisions each one helps you make.
My name is Janne Valtakari. Having worked across consulting operations of different sizes, I kept seeing the same problems recur — problems that needed more than a quick fix. At some point it became clear that most firms would benefit from at least one structured, end-to-end view of how to approach operations from a talent perspective. After all, talent is the most valuable IP a consultancy has.
This site is my attempt to build that reference. Feedback, corrections, and thoughts on how to make it more useful for real-life problems are always welcome.