The scoreboard, honestly: the hard targets, how often each one is actually looked at,
and the quiet human signals that never make it onto a dashboard.
Data Accuracy for Models
The percentage of data points (e.g., postal codes, freight rates, product dimensions) used in your analyses that are correct and validated.
Target · Greater than 99.5% accuracy on all primary data inputs.If you're building a network model using 1,000 data points, you should have no more than 5 errors identified during validation. For instance, catching an incorrect weight for a major product line before it skews a cost-to-serve analysis.
Standard Analysis Turnaround Time
How quickly you can complete routine network analyses or reports once the request and necessary data are received.
Target · Complete 90% of standard analysis requests within 48-72 hours.A request for a 'cost-to-serve' analysis for a new product category should be delivered within three working days, allowing the Sales team to price it correctly for launch.
Identified Cost Savings Opportunities
The value of potential cost savings you identify through your network optimisation efforts, even if not yet implemented.
Target · Identify and validate at least £500K in annual network cost savings opportunities per year.Through a 'node optimisation' study, you might identify that consolidating two smaller regional depots into one larger, more central one could save £750K annually in rent and labour costs.
Report Timeliness
Ensuring all recurring reports and dashboards you're responsible for are delivered on schedule.
Target · 100% of recurring reports delivered on time.The weekly transport lane cost report needs to hit the Transport Manager's inbox every Monday morning without fail, giving them time to react to changes.
Clarity of Insights & Recommendations
Your ability to translate complex analytical findings into clear, understandable insights and practical recommendations for non-technical audiences.
- Feedback from Operations and Finance teams on the readability and usefulness of your reports. Are they asking for clarification constantly, or are they able to act on your suggestions? Do they 'get' the core message without needing a deep dive into your model? Are your presentations easy to follow, even for someone who doesn't live and breathe logistics?
Proactive Problem Identification
How well you anticipate potential network issues (e.g., capacity constraints, rising costs in a lane) before they become critical problems.
- You're flagging potential issues to your Senior Planner or Manager before they're escalated by other teams. You might spot a trend in carrier performance data that suggests future delays, or a spike in fuel costs that will impact a specific region, and bring it to attention with a proposed mitigation. It's about seeing around corners.
Collaboration with Operations Teams
Your effectiveness in working with warehouse, transport, and inventory teams to gather data, validate assumptions, and ensure your recommendations are practical.
- Operations teams feel you're a partner, not just someone who sends them spreadsheets. They're willing to share their 'on the ground' insights with you, and you're seen as someone who listens and incorporates their practical knowledge into your models. Are they actively engaging with your proposals, or just nodding politely?
Documentation Quality
The completeness and clarity of your model documentation, analysis methodologies, and data sources.
- Can another planner pick up your work and understand exactly what you did, why you did it, and how to replicate it without having to ask you a dozen questions? Are your assumptions clearly stated? This is about making sure your work is transferable and auditable, not just a 'black box'.