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4 minute read

Decomposition Estimation Strategy

This is a profound question that moves beyond simple task listing and delves into the core discipline of Estimation Science. The challenge of “Forgetting Related Work” happens because we often focus only on the visible work (the code changes) and forget the essential supporting, infrastructural, and preparatory work.

The solution lies in forcing a comprehensive decomposition based on dependency mapping and reverse engineering before estimation begins.

Here is how you can use your proposed hierarchical structure to ensure completeness, focusing specifically on solving the “Forgetting Related Work” challenge during migration projects.


1. The Hierarchical Decomposition Framework

The structure you propose (Project $\rightarrow$ Phases $\rightarrow$ Tasks $\rightarrow$ Subtasks) is the correct foundation. To make it robust against forgetting related work, every layer must have a specific purpose:

Level Focus Area Goal of the Level Critical Action for Completeness
1. Project The Ultimate Goal Defining the Scope and Constraints (What are we migrating to?) Define clear In-Scope vs. Out-of-Scope.
2. Phases Major Milestones Grouping related tasks into logical, sequential stages (The “How” in sequence). Ensure phases have clear, measurable Exit Criteria.
3. Tasks Deliverables Defining the major work units that produce a tangible outcome (The “What”). Identify all necessary Dependencies between tasks.
4. Subtasks Work Units Breaking tasks down into granular, estimable actions (The “How much”). Ensure every piece of required configuration or setup is captured.

To achieve a truly complete list, you must adopt three strategic techniques: Reverse Engineering, Dependency Mapping, and Boundary Definition.

A. Reverse Engineering (Working Backward)

Instead of starting with “What steps do I need to take?” start with the end goal.

  1. Define the Target State: Clearly define what the final, successful state of the new system looks like (e.g., “System B is running,” “Data integrity is verified,” “All external APIs are functional”).
  2. Identify Prerequisites: Ask: What must exist for that final state to be true? (e.g., To deploy System B, we must have a working database schema; to build the API, we must have defined data models.)
  3. Deconstruct Backwards: Use these prerequisites as your Phase goals. This ensures that all necessary preparatory work (setup, configuration, setup) is forced into the task list.

This step directly solves the forgetting problem by forcing you to see connections between tasks.

  • Identify Predecessors: For every Task, identify which other Tasks must be completed first.
    • Example: Task 3: Build Migration Scripts $\rightarrow$ Requires Task 1: Analyze Legacy Schema and Task 2: Define Target Schema. (If you forget Task 1/2, Task 3 cannot start.)
  • Identify Successors: Identify which subsequent tasks depend on the completion of the current task. This helps manage scheduling and resource allocation.

C. Boundary Definition (Preventing Scope Creep)

Related work often slips in when boundaries are fuzzy. Use this framework to define where a task starts and ends, and what is explicitly out-of-scope for the estimation period.

  • Inputs: Define all necessary inputs (e.g., existing documentation, environment access).
  • Outputs: Define the measurable outputs of each Subtask (e.g., “Database connection string generated,” not just “Work on database setup”).
  • Constraints: Explicitly document constraints (e.g., “Estimation does not include resolving legacy business rule conflicts”).

3. Example: Migration Project Decomposition

Let’s apply this to a migration from System A $\rightarrow$ System B.

Level 1: Project Definition

  • Goal: Successfully migrate all production data, functionality, and operational processes from System A to System B with zero downtime.

Level 2: Phases (The Sequence)

  1. Discovery & Planning: Understand both systems and define the strategy.
  2. Schema Mapping & Data Preparation: Prepare the new environment for data ingestion.
  3. Development & Migration Logic: Build the actual transformation code.
  4. Testing & Validation: Ensure functional equivalence and data integrity.
  5. Deployment & Cutover: Execute the final transition and decommissioning of System A.

Level 3 & 4: Tasks $\rightarrow$ Subtasks (The Complete List)

Focusing on Phase 2: Schema Mapping & Data Preparation:

Task Related Work / Dependencies Subtasks (Granular Estimation Units)
T2.1 Analyze Legacy Schema (System A) Prerequisite for T2.2, T3.1 2.1.1 Extract all tables/views from System A DB. / 2.1.2 Document all data types and constraints. / 2.1.3 Identify orphaned data sets.
T2.2 Define Target Schema (System B) Depends on T2.1 results 2.2.1 Design new normalized schema for System B. / 2.2.2 Map legacy fields to new System B structure. / 2.2.3 Define all required foreign keys and indexes.
T2.3 Prepare ETL Scripts Depends on T2.2 results (Data models) 2.3.1 Write initial SQL scripts for data extraction. / 2.3.2 Develop data cleansing rules (handling nulls, formats). / 2.3.3 Create temporary staging environment setup.
T2.4 Data Validation Plan Depends on T2.3 completion 2.4.1 Define reconciliation metrics (checksums, record counts). / 2.4.2 Define acceptance criteria for data accuracy. / 2.4.3 Setup validation reporting framework.

Conclusion: How to Reach the Most Complete List?

The most complete list of tasks is reached by treating the process not as a linear checklist, but as a dependency graph.

  1. Start with the End: Define the final desired state (Reverse Engineering).
  2. Identify Gates: Use your Phases as checkpoints. The work in Phase 2 cannot start until all prerequisite work from Phase 1 is finished.
  3. Force Dependencies: Explicitly write down: “Task X requires Input Y.” This forces you to account for the supporting work (the related work) that must happen before estimation can be accurate.
  4. Iterate and Validate: Review the list with Subject Matter Experts (SMEs). Ask them, “If we deliver this, what is missing?”
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