Enterprise Automation Prioritization Loop
Inventory repetitive work, rank automation opportunities, and prove the return
- Difficulty
- Advanced
- Time to result
- ~months to results
- Steps
- 6
- Confidence
- 98%
The Enterprise Automation Prioritization Loop creates a cross-functional automation capability rather than leaving isolated teams to automate locally. Begin by examining every function and documenting repetitive tasks, including the people, systems, triggers, decisions, and outputs involved. Rank opportunities so effort goes first to workflows with meaningful frequency, cost, delay, error, or unrealized capacity. Then integrate the relevant technologies and build scalable automation instead of adding more people to coordinate fragmented tools. The ambition is not limited to reproducing human tasks: technology may enable activities that humans could not feasibly perform at the same scale. Each implementation must show a return through time saved, better quality, lower cost, faster throughput, or new capability, after which the loop repeats.
Origin
Extracted from Marketing Against The Grain's discussion of Steph Smith's proposed chief automation officer role and the proliferation of business technology.
Core principles
- 01Automation is a company-wide capability rather than a single department's concern
- 02Document work before automating it
- 03Prioritize opportunities instead of automating indiscriminately
- 04Integrate systems to reduce fragmented manual coordination
- 05Use technology to expand capability, not only remove labor
- 06Demonstrate measurable return from automation
How to run it
- 1
Inventory repetitive work
Review every function and document recurring manual activities. Capture triggers, inputs, systems, owners, decisions, and outputs.
Pro tip Observe actual work rather than relying only on official process documents.
Watch out Automating an inaccurately documented process will preserve or amplify its defects.
- 2
Rank the opportunities
Score candidates by repetition, labor, delay, error rate, business value, technical feasibility, and risk. Order them before building anything.
Pro tip Start with a bounded workflow that is valuable enough to prove the model.
Watch out Do not prioritize merely because a task is easy to automate.
- 3
Consolidate and integrate systems
Identify unnecessary tool fragmentation and connect the systems required for end-to-end execution. Establish reliable data and handoffs.
Watch out A brittle chain of disconnected tools can create more operational burden than it removes.
- 4
Build with human controls
Automate deterministic portions while retaining review for ambiguity, exceptions, or consequential decisions. Define failure handling and ownership.
Pro tip Use automation to augment judgment where full replacement would be unsafe.
Watch out Do not remove human oversight before exception behavior is understood.
- 5
Prove the return
Compare the automated process with its baseline on time, cost, quality, throughput, and new capability. Report both gains and maintenance costs.
Watch out Hours saved without a useful business outcome may not justify ongoing complexity.
- 6
Scale and repeat
Standardize successful patterns, expand them to adjacent teams, and return to the ranked backlog. Reassess priorities as the technology stack changes.
Pro tip Maintain shared ownership so local automations do not become invisible infrastructure.
In the wild
An automation team documents a weekly report assembled manually from advertising, CRM, and finance systems. It ranks highly because it consumes many hours and frequently contains copy errors. The team integrates the sources, adds anomaly review, and measures preparation time and correction rates against the old process.
→ Reporting becomes faster and more reliable while analysts spend more time interpreting results.
After automating basic lead routing, the team uses integrated behavioral and account data to reassess routing continuously—something employees could not perform manually at the same frequency. Human review remains for unusual high-value accounts.
→ Automation creates a new operational capability rather than merely replacing data entry.
Common mistakes
Automating before documenting
Without understanding the current process and its exceptions, teams risk encoding confusion into software.
Adding people around fragmented tools
Using headcount to coordinate an expanding technology stack can conceal the integration problem instead of solving it.
Ignoring measurable return
Automation that cannot demonstrate better capacity, cost, speed, or quality may only relocate work into maintenance.
Is it for you?
Best for
It is best for scaling organizations with recurring cross-functional work and a proliferating technology stack.
Not ideal for
It is not ideal for rare, ambiguous, or high-risk tasks that still require substantial human judgment.
From the transcript
“There is just huge value in having a team who go through every function and document repetitive tasks and then stack rank and order things…”
“You need to integrate that technology so that it works really well together.”
“If you can solve for those first principles of great systems integration, building great scalable automation instead of throwing people at the problem and showing…”
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