Complex allocation
Skills, availability, assignment windows, and project priorities created interdependent planning decisions.
Anonymous energy resource planning case study
Centralizing resource planning for complex energy projects
An energy organization needed one enterprise platform to plan specialist capacity, allocate people across complex projects, and replace fragmented resource data.
The situation
Project staffing decisions were spread across disconnected data and planning processes.
Complex energy work depended on coordinating thousands of specialists with different skills, availability, locations, and project commitments. Fragmented planning made conflicts and future capacity difficult to see.
The client needed an enterprise system that could support large data volumes and concurrent planning activity while migrating historical resource information safely.
The challenge
Turn a large, changing set of people and project constraints into a usable planning tool.
The product had to combine data scale, concurrent updates, scheduling rules, and practical planner workflows.
Data and concurrency
Large operational datasets and many users required efficient access and dependable updates.
Migration continuity
Historical and active planning data had to move without breaking current staffing work.
The solution
A centralized .NET platform connected capacity, allocation, and project demand.
The team modeled planning rules with domain specialists, built scalable services and SQL Server data structures, and migrated information in controlled stages.
- 01
Model planning rules
Define specialists, skills, availability, projects, demand, allocation, and conflict behavior.
- 02
Build for scale
Optimize services and data access for high-volume planning and concurrent use.
- 03
Migrate with evidence
Profile, map, move, and reconcile resource data before each transition step.
How we worked
Combine domain discovery, product increments, and migration rehearsal.
Agile workshops turned planning decisions into clear product rules and testable scenarios.
The team delivered usable planning slices so stakeholders could validate allocation behavior early.
Migration rehearsals measured completeness, reconciliation, and operating readiness rather than file transfer alone.
01Model
Define capacity, demand, allocation, and conflicts.
02Build
Deliver scalable services and planner workflows.
03Migrate
Profile, map, move, and reconcile data.
04Adopt
Validate planning scenarios and operational readiness.
The result
Project leaders gained one system for specialist capacity and allocation.
The platform centralized resource data, made project demand and conflicts more visible, and supported large-scale planning on a maintainable .NET and SQL Server foundation.
Centralized planningfor specialist capacity and project demand
Conflict visibilityacross availability and active allocations
Enterprise data foundationfor concurrent planning and reporting
Better staffing decisions
Planners could compare demand, capacity, skills, and timing in one context.
More dependable data
Migration and reconciliation created a clearer operational source of truth.
Designed for continued scale
Service and database work supported future growth without preserving the old fragmentation.
Case taxonomy
Searchable by industry, technology, product, and business need.
Industry and product
- Energy
- Project Operations
- Resource Management
- Workforce Planning
Technology and delivery
- .NET
- SQL Server
- Web Services
- Agile
- Data Migration
Business need
- Capacity Planning
- Resource Allocation
- High Concurrency
- Data Consolidation
- Conflict Management
Make resource constraints visible
Need one planning system for complex projects and specialist capacity?
Get in touch
Ready to build software that fits your business?
Tell us what you need to build, modernize, automate, or augment with AI. We can start with a focused discussion or a no-risk 1-week trial.
“A fantastic company to work with.” After the initial rapid development project, American Shipping Co. kept two Shinetech developers embedded for nearly four years, supporting internal and external tools and new AI initiatives.
CEO, American Shipping Co. - 5-star Google Review