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Locked-In™ - Time Management System

Locked-In™ - Time Management System

$19.00

Locked-In™ Time Management System

What it does

  • Five-page weekly system that turns your plans into clear tasks, time blocks, and a 20-week record you can scan in seconds.

  • Helps you decide what actually matters this week, put it into real hours, and see what you finished instead of guessing.

  • Use it as your main weekly layout so all your important work, time, and proof of progress live in one place, not across apps.

What’s inside

  • Daily Done Planner – Turns each day into a short list of non-negotiable tasks with clear finish lines.

  • Big Wins Week – Pulls out the few moves that actually matter so you know what this week is really for.

  • Weekly Schedule Grid – Gives your week a simple structure with fixed slots for focused work and life essentials.

  • 20-Week At-a-Glance Tracker – Shows your consistency over months so you can see patterns, not just single days.

  • Intro + Sources page – Quick setup and the core studies behind the system, so you know it’s evidence-based.

Evidence (page by page)

  • Daily Done Planner – Time-specific “if it’s this time, I do this task” plans (implementation intentions) reliably improve goal completion versus vague intentions (Gollwitzer & Sheeran, 2006, meta-analysis).

  • Big Wins Week – Clear, specific written goals focused on a few key targets outperform “do your best” goals in work and performance settings (Locke & Latham, 2002, goal-setting theory review).

  • Weekly Schedule Grid – Repeating actions in a stable time and context helps them become more automatic over weeks, supporting real-world habit formation (Lally et al., 2010, longitudinal habit study).

  • 20-Week At-a-Glance Tracker – Monitoring and recording your own progress significantly increases goal attainment across many domains (Harkin et al., 2016, meta-analysis of progress monitoring).

  • Intro + Sources page – Moving plans out of your head onto external tools (“cognitive offloading”) reduces mental load and supports performance on complex tasks (Risko & Gilbert, 2016, review).

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