How to Score & Prioritize a Workstream
In this article you'll find clear criteria, real examples, and a quadrant model you can actually use to prioritize your accounting firm's workstreams
Some workflows are obvious wins: repetitive, rules-based, data-heavy. Others? Messy, complex, or too rare to be worth the lift.
To identify exactly where AI will deliver the most benefit (and where it might stumble) you need a structured, score-based approach.
By systematically scoring your workstreams on two key dimensions (Impact—the benefit of automating—and Feasibility—ease of implementing the automation—) you move from intuitive guesses to confident, clear prioritization.
The Core Idea: Score It to Sort It
Not all processes are equally automatable or equally worth it.
Prioritization doesn't need to be complicated. It boils down to answering two simple questions:
• Impact Factors: How much value would automating this workstream create?
• Feasibility Factors: How easy would it be to implement AI for this workstream?
Each lens is backed by five attributes. You’ll score each on a 1–5 scale, then combine them into a clear picture of your AI opportunity landscape.
Feasibility Attributes
1. Systems & Tools Involved
How complex is the tech stack? How many different systems does this workstream touch?
Simpler tech stacks are easier to integrate AI into.
- Score 1: Multiple disconnected systems involved.
- Score 5: Single, integrated platform.
2. Technical Complexity
How complex is the workstream, and how often does it change? How much human judgment or nuanced decision-making is needed? Simple, stable processes are easier to automate.
• Score 1: Multi-step, variable, and constantly evolving. Requires nuance, decision-making, or context.
• Score 5: Straightforward and consistent, simple, rules-based tasks.
3. Data Complexity
Is the data clean, structured, and easy for AI to use?
• Score 1: Unstructured, messy data (e.g., scanned documents). Manual PDFs, handwritten notes, messy formats.
• Score 5: Standardized and structured.
4. Time to Implement
How quickly can you realistically implement the AI Pilot?
• Score 1: Extensive planning, months-long implementation.
• Score 5: Quick setup within days or weeks.
5. Resources Required
What resources (time, budget, personnel) will you need to imnplement the AI Automation.
• Score 1: High resources needed, cross-functional involvement.
• Score 5: Minimal resources, can be managed by a small team.
Impact Attributes
1. Number of People Involved
How broadly does this workstream affect the firm? How many team members rely on or execute this process? The more people involved, the broader the benefit of AI.
• Score 1: Limited to a small group or department, a niche process used by one person or team.
• Score 5: A firm-wide workflow that touches everyone from interns to partners.
2. Client Value
Does it directly improve the client's experience? Would it allow the firm to deliver higher value, better insights or faster turnaround?
• Score 1: Minimal direct client impact.
• Score 5: Significant enhancement in client experience.
3. Commercial Value
Is there clear revenue or monetization potential? Will it improve margins or open new service lines?
• Score 1: Little to no direct revenue opportunity.
• Score 5: Clear path to increased revenue or profitability.
4. Efficiency Gains
What’s the potential ROI? Does automation significantly save time or costs? This factor helps gauge the upside and/or opportunity cost.
• Score 1: Limited efficiency gain, minor efficiency improvement.
• Score 5: Huge savings in time or cost, scalability, or risk reduction.
5. Strategic Alignment
How closely aligned is the workstream to strategic firm objectives? How core is this process to your firm’s operations or client delivery? AI should support what matters most.
• Score 1: Peripheral or unrelated to strategic priorities.
• Score 5: Core to the firm’s strategic direction, mission-critical to firm success or compliance.
How to Score Clearly & Practically
• Rate each attribute clearly from 1 to 5, using real scenarios to guide consistency.
• Remember scores are RELATIVE to your firm specifics.
• Combine scores for each dimension (Impact & Feasibility), averaging or summing for simplicity.
• Validate your scores with stakeholders, your team knows best which scores ring true.
• Adjust the granularity if necessary: if something scores high on impact but low on feasibility, consider breaking it into smaller parts to boost clarity and ease of execution.
Using this structured approach simplifies decision-making, ensuring you prioritize workstreams that offer maximum benefits with the most realistic paths to AI implementation.
