Merit-Based Iterative Testing (MBIT): How to Make Your Organization a Meritocracy : Chris
by: Chris
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What if you built an organization based on merit, not CVs, human biases, or legacy credentials?
You would grow faster at a lower cost!
I have written extensively about the benefits of remote work and freelancing in modern organizations. But recently, one of my subscribers asked me to elaborate how to hire freelancers effectively (instead of how to become a successful freelancer?).
So I decided to formalize my intuitive approach with Finxter: Let’s call it the MBIT method. 
The Merit-Based Iterative Testing (MBIT) method is an inclusive approach to talent management that prioritizes merit over traditional credentials, allowing individuals from all walks of life to showcase their abilities through practical tasks.
There is no application process, no CV, no academic or formal requirements – if they successfully complete the first small gig, they move on to a larger gig.
By gradually increasing project complexity and responsibility based on performance it ensures a continuous optimization of talent within an organization.
This method fosters a culture of continuous improvement and innovation, leading to a dynamic, merit-driven ecosystem that evolves to meet future challenges.
Three Phases of MBIT
(1) Testing Phase: Initial Exploration and Assessment
Action: Assign a standard, small task to a diverse pool of freelancers (e.g., designing a product label), each with a modest budget (like $50).
Objective: Assess skills and creativity impartially, providing equal opportunity to all candidates regardless of their background.
(2) Scaling Phase: Gradual Increase and Convergence
Action: Select the most promising freelancers based on their performance in the Testing Phase for larger tasks. Increase the complexity and budget of the tasks gradually, moving towards more substantial, regular gigs or the overall project completion.
Objective: Establish a meritocratic system where continued high performance leads to greater responsibilities and rewards, ensuring that the best talents are progressively engaged in more significant aspects of the project.
(3) Post-Convergence Monitoring Phase: Ongoing Performance Evaluation
Action: Continuously monitor the performance of top freelancers. Evaluate if they maintain or improve their quality over time and adapt to evolving project needs.
Objective: Ensure sustained high-quality output. If a freelancer fails to meet the required standards or demonstrate continuous improvement, consider discontinuing the collaboration for maintaining overall project quality.
Implementing MBIT: An Amazon Store Example
Let’s have a quick example.
Say, you run an Amazon FBA business selling organic coffee. Your store relies on high-quality designers to attract more clicks and convert these clicks to sales more effectively. You need lots of different high-quality visuals for your changing inventory – like this:
Phase 1: Testing Phase
Task: Design a product label for a new organic coffee line.
Number of Freelancers: 10 graphic designers.
Price Point per Gig: $50 for each designer.
Performance Metrics: Creativity, adherence to brand guidelines, turnaround time, and feedback incorporation.
Phase 2: Scaling Phase
Selected Freelancers: 3 designers with the best label designs.
New Task: Create a series of promotional materials for the coffee line, including social media graphics, packaging design, and an email marketing template.
Price Point per Gig: $200 per designer for the series.
Performance Metrics: Consistency in design quality, innovation in promotional concepts, effectiveness in audience engagement (measured by social media interaction and email open rates), and ability to meet deadlines.
Phase 3: Post-Convergence Monitoring Phase
Top Freelancer Selection: 1 designer who excels in the Scaling Phase.
Ongoing Task: Monthly creation of varied marketing materials and new product designs.
Price Point per Gig: Retainer of $500 per month.
Performance Metrics: Continued excellence in design, ability to adapt to new product lines, consistency in meeting deadlines, and effectiveness in driving sales or marketing goals (measured by campaign conversion rates and customer feedback).
In this specific Amazon Store example, MBIT methodically identifies, tests, and scales freelancer talent, ensuring that the final retained designer is not only the best fit for the current needs but also capable of adapting and growing with the store’s evolving marketing strategies.
Benefits of the Refined MBIT Method
- Merit-Based Progression: Talents are rewarded and responsibilities are increased based on proven skills and performance.
- Cost-Effective Scalability: The gradual increase in gig volume and complexity ensures financial prudence while identifying the best talent.
- Quality Assurance: Continuous performance monitoring maintains high standards of output, ensuring the project’s success.
The ultimate benefit of implementing the MBIT Method in an organizational ecosystem is creating a self-sustaining environment where continuous improvement and excellence become the norm.
This method enhances immediate project outcomes through optimal talent utilization and fosters a culture of perpetual growth and innovation. It leads to an organization that excels in its current endeavors and evolves to meet future challenges with agility and a robust, ever-improving skill set.
There is no friction.
The small overhead at the front-end, i.e., hiring a lot of freelancers for small gig experiments, is overcompensated by the huge efficiency-gains in the back-end, i.e., paying larger gigs only for top talent.
The emerging organization has high talent standards through selection and self-selection while still being open, inclusive, and fair. It filters out freelancers who are not suitable or willing to engage in a sustainable relationship with the organization to the benefit of all parties, i.e., freelancers, customers, and organizations.
December 18, 2023 at 09:19PM
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