WDL Executive Summary Template
Use this template to produce a clear, concise summary of a WDL workflow for leadership, project managers, and non-technical stakeholders. Focus on business value, outcomes, and key decisions — not implementation details.
1. Document Information
| Field |
Details |
| Workflow Name |
[Enter workflow name] |
| Document Version |
[e.g. 1.0] |
| Prepared By |
[Name and role] |
| Date |
[YYYY-MM-DD] |
| Audience |
[e.g. Senior Leadership / Programme Board / Product Owner] |
| Classification |
[Public / Internal / Confidential] |
2. Executive Overview
What This Workflow Does
In 2-3 sentences, describe what the workflow does in plain language. Avoid jargon.
[e.g. This workflow takes raw DNA sequencing data from patient samples and identifies genetic variants that may be clinically relevant. It automates a multi-step process that previously required manual execution by bioinformaticians, reducing turnaround time from days to hours.]
Why It Matters
Explain the business or scientific value.
[e.g. Automated variant calling enables faster clinical reporting, reduces human error, and supports the organisation's goal of processing 10,000 genomes per year.]
3. Key Facts at a Glance
| Metric |
Value |
| Processing Time (per sample) |
[e.g. ~4 hours] |
| Cost per Sample |
[e.g. ~$8-12 USD on cloud infrastructure] |
| Throughput Capacity |
[e.g. 50 samples per day in parallel] |
| Accuracy / Validation Status |
[e.g. Validated against NA12878 truth set — 99.5% sensitivity] |
| Automation Level |
[e.g. Fully automated — no manual intervention required] |
| Platform |
[e.g. Google Cloud via Terra / AWS HealthOmics / On-premises HPC] |
4. Business Problem and Solution
The Challenge
Describe the problem that existed before this workflow.
[e.g. The team was manually running 8 different bioinformatics tools in sequence for each sample. This process was error-prone, inconsistent across operators, and created a bottleneck that limited throughput to 5 samples per day.]
The Solution
Describe how the workflow addresses the challenge.
[e.g. The WDL workflow encodes the entire 8-step process into a single, reproducible, automated pipeline. It runs on cloud infrastructure, scales horizontally with demand, and produces consistent results regardless of who initiates the run.]
Key Benefits
- [e.g. Speed: Reduces per-sample processing time from 2 days to 4 hours]
- [e.g. Cost: Reduces compute costs by 40% through spot/preemptible instance usage]
- [e.g. Consistency: Eliminates operator-dependent variation in results]
- [e.g. Scalability: Can process 50+ samples concurrently without additional staffing]
- [e.g. Auditability: Full provenance tracking for regulatory compliance]
5. Workflow Summary (Non-Technical)
Describe the workflow steps at a high level. Use a simple numbered list or a visual diagram. Avoid tool names and technical parameters.
Process Flow
- Quality Check — Assess the quality of incoming data and flag any issues
- Data Preparation — Clean and prepare the data for analysis
- Core Analysis — Perform the primary analysis (e.g., identify genetic variants)
- Quality Filtering — Remove low-confidence results to ensure accuracy
- Reporting — Generate output files and summary reports
Visual Overview
Raw Data --> Quality Check --> Preparation --> Analysis --> Filtering --> Results
6. Inputs and Outputs
What Goes In
Describe inputs in non-technical terms.
| Input |
Description |
Source |
| [Sequencing data files] |
[Raw data files from the sequencing instrument] |
[Sequencing facility / LIMS] |
| [Reference data] |
[Standard reference dataset used for comparison] |
[Public repository — maintained by platform team] |
| [Sample metadata] |
[Patient/sample identifiers and associated information] |
[Clinical database / Sample tracking system] |
What Comes Out
| Output |
Description |
Used By |
| [Analysis results] |
[Primary findings from the analysis] |
[Clinical team / Downstream analysis] |
| [Quality report] |
[Summary of data quality and processing metrics] |
[QC review / Audit trail] |
| [Processing log] |
[Record of all steps performed and their status] |
[Compliance / Troubleshooting] |
7. Cost Analysis
Per-Sample Cost Breakdown
| Cost Component |
Estimated Cost |
Notes |
| Compute (cloud VMs) |
[$X.XX] |
[Using preemptible/spot instances where possible] |
| Storage (during run) |
[$X.XX] |
[Temporary storage deleted after completion] |
| Storage (long-term) |
[$X.XX / month] |
[Output files retained per policy] |
| Data Transfer |
[$X.XX] |
[Ingress/egress charges if applicable] |
| Total per Sample |
[$X.XX] |
|
Annual Cost Projection
| Scenario |
Samples / Year |
Estimated Annual Cost |
| Low Volume |
[500] |
[$X,XXX] |
| Medium Volume |
[2,000] |
[$XX,XXX] |
| High Volume |
[10,000] |
[$XXX,XXX] |
Cost Comparison (Before vs. After)
| Metric |
Before (Manual) |
After (Automated WDL) |
Improvement |
| Cost per Sample |
[$XX] |
[$XX] |
[X% reduction] |
| Staff Hours per Sample |
[X hours] |
[X hours] |
[X% reduction] |
| Annual Operating Cost |
[$XXX,XXX] |
[$XXX,XXX] |
[$XX,XXX savings] |
8. Risk Assessment
| Risk |
Likelihood |
Impact |
Mitigation |
| [Cloud provider outage disrupts processing] |
[Low] |
[Medium] |
[Multi-region deployment; retry logic built into workflow] |
| [Tool version update introduces breaking change] |
[Medium] |
[High] |
[Pinned container versions; validation testing before upgrade] |
| [Cost overrun due to unexpected data volume] |
[Medium] |
[Medium] |
[Budget alerts; preemptible instances; auto-scaling limits] |
| [Data security breach] |
[Low] |
[Critical] |
[Encryption at rest and in transit; VPC isolation; access controls] |
| [...] |
[...] |
[...] |
[...] |
9. Compliance and Governance
| Requirement |
Status |
Details |
| Data Protection (GDPR/HIPAA) |
[Compliant / In Progress / N/A] |
[e.g. Data processed within approved regions; BAA in place] |
| Audit Trail |
[Compliant / In Progress / N/A] |
[e.g. Full execution logs retained for 7 years] |
| Validation (GxP/CAP) |
[Validated / Pending / N/A] |
[e.g. IQ/OQ/PQ documentation complete] |
| Access Control |
[Compliant / In Progress / N/A] |
[e.g. Role-based access; principle of least privilege] |
| Change Management |
[Compliant / In Progress / N/A] |
[e.g. All changes go through PR review and validation] |
10. Current Status
Development Status
| Phase |
Status |
Target Date |
| Requirements Gathering |
[Complete / In Progress / Not Started] |
[YYYY-MM-DD] |
| Development |
[Complete / In Progress / Not Started] |
[YYYY-MM-DD] |
| Testing and Validation |
[Complete / In Progress / Not Started] |
[YYYY-MM-DD] |
| Production Deployment |
[Complete / In Progress / Not Started] |
[YYYY-MM-DD] |
| Operational Handover |
[Complete / In Progress / Not Started] |
[YYYY-MM-DD] |
Key Milestones
| Milestone |
Date |
Status |
| [Requirements sign-off] |
[YYYY-MM-DD] |
[Achieved / Pending] |
| [First successful test run] |
[YYYY-MM-DD] |
[Achieved / Pending] |
| [Validation complete] |
[YYYY-MM-DD] |
[Achieved / Pending] |
| [Production go-live] |
[YYYY-MM-DD] |
[Achieved / Pending] |
11. Team and Ownership
| Role |
Name / Team |
Responsibility |
| Executive Sponsor |
[Name] |
[Strategic oversight and funding approval] |
| Product Owner |
[Name] |
[Requirements and acceptance criteria] |
| Technical Lead |
[Name] |
[Workflow design and implementation] |
| Platform / DevOps |
[Name / Team] |
[Infrastructure and deployment] |
| Operations |
[Name / Team] |
[Day-to-day running and monitoring] |
12. Decisions Required
List any pending decisions that require leadership input.
| Decision |
Options |
Recommendation |
Deadline |
| [e.g. Cloud provider selection] |
[GCP / AWS / Azure] |
[GCP — existing infrastructure and team expertise] |
[YYYY-MM-DD] |
| [e.g. Data retention period] |
[1 year / 5 years / 7 years] |
[7 years — regulatory requirement] |
[YYYY-MM-DD] |
| [...] |
[...] |
[...] |
[...] |
13. Next Steps
List the immediate next actions with owners and timelines.
| Action |
Owner |
Target Date |
| [e.g. Approve budget for cloud infrastructure] |
[Name] |
[YYYY-MM-DD] |
| [e.g. Complete security review] |
[Name] |
[YYYY-MM-DD] |
| [e.g. Begin production pilot with 10 samples] |
[Name] |
[YYYY-MM-DD] |
| [...] |
[...] |
[...] |
Appendix: Glossary of Terms
| Term |
Definition |
| WDL |
Workflow Description Language — a standard for defining automated data processing pipelines |
| Pipeline / Workflow |
An automated sequence of processing steps that transforms input data into results |
| Cloud Compute |
On-demand computing resources rented from a cloud provider (e.g., Google Cloud, AWS) |
| Preemptible / Spot |
Discounted cloud computing instances that may be interrupted — used to reduce costs |
| Container |
A packaged software environment that ensures tools run consistently across platforms |
| Scatter / Parallelism |
Running multiple copies of a step simultaneously to process data faster |
| [...] |
[...] |