TOOLS FOR BETTER OPERATIONS.

Make the process clearer
before you automate it.

Use these practical checklists and guides to identify strong automation candidates, clean up reporting workflows, prepare safer sample data, and define alerting that actually helps the people receiving it.

Start with the Readiness Check Let's Connect

START WITH THE WORK

Useful before the first line of code.

Good automation begins with a clear understanding of the current process. What triggers the work? Which systems are involved? Where do people make decisions? Which exceptions matter? What does “done correctly” actually look like?

These resources are designed to help teams answer those questions before they commit to a tool, a platform, or a build.

You do not need a technical specification. You need a process someone can explain.

RESOURCE LIBRARY

Four places to start.

01Checklist

Workflow Automation Readiness Check

Ten quick questions to help determine whether a repetitive process is stable and rules-based enough to be a strong automation candidate.

Open the checklist
02Audit

Reporting Process Audit

Find the hidden manual work inside recurring reports: repeated exports, cross-file matching, cleanup, validation, formatting, and last-minute corrections.

Audit a reporting process
03Guide

Redacted Dataset Prep Guide

Prepare representative data for workflow design without sharing names, account numbers, or other identifiers that are not needed to reproduce the logic.

Prepare a safer sample
04Framework

Operational Alerting Checklist

Define what should trigger an alert, who owns it, how quickly it matters, and what should happen when the first notification does not produce action.

Design better alerting

Workflow Automation Readiness Check

A good candidate does not have to be glamorous. It usually just has to be repeated, explainable, and important enough that inconsistency costs time.

  • The process happens on a recurring schedule or is triggered by a predictable event.
  • The same information is copied, re-entered, reformatted, or moved between systems repeatedly.
  • The steps can be explained in a consistent order, even if there are exceptions.
  • The inputs usually arrive in structured formats such as spreadsheets, CSV files, exports, forms, emails, or APIs.
  • People spend time matching records across two or more sources.
  • The workflow contains repeatable rules such as inclusion, exclusion, categorization, thresholds, or status logic.
  • A mistake can produce rework, bad reporting, missed notifications, or inconsistent decisions.
  • The final output is predictable: a report, tracker, import file, notification, scorecard, or updated dataset.
  • The process has enough volume or frequency that saving even a few minutes per cycle matters.
  • Someone on the team can explain the normal path and the important exceptions.
0–3 TRUEProbably define and stabilize the process before automating it.
4–6 TRUEWorth exploring. There may be targeted pieces that can be automated now.
7–10 TRUEStrong candidate for a workflow review and automation design.

Map one reporting cycle from start to finish.

Do not start with the final report. Start with the first export, download, email attachment, or system query that begins the cycle.

Document the manual steps

  • Every source file or system used
  • Every filter, exclusion, and cleanup step
  • Every lookup or match between sources
  • Every formula, calculation, and derived metric
  • Every manual correction or judgment call
  • Every formatting step required before delivery

Look for automation red flags

  • “We do this every month.”
  • “That column always has to be fixed.”
  • “Then we VLOOKUP against the other file.”
  • “Only these statuses count.”
  • “Someone has to check the totals manually.”
  • “We copy this into the customer template.”

Record the exception logic.

Exceptions are often the most valuable part of the process map. Write down what changes by customer, department, location, status, date, threshold, or source—and what a knowledgeable person does when the normal rule does not apply.

Redacted Dataset Prep Guide

The goal is not to make the data meaningless. It is to keep the fields, relationships, and edge cases that drive the process while removing identifiers that are irrelevant to the automation.

STEP 01Keep the original structurePreserve column names, tabs, file relationships, data types, and the general shape of the source.
STEP 02Remove direct identifiersReplace names, account numbers, employee IDs, emails, phone numbers, and similar fields when they are not needed.
STEP 03Preserve relationshipsIf two files must match on an ID, replace the real ID with the same fictional value in both files so the relationship still works.
STEP 04Keep meaningful variationInclude normal records, edge cases, missing values, exceptions, and unusual statuses that affect the real workflow.
STEP 05Include the desired outputA redacted example of the finished report or file is often as useful as the source data itself.
STEP 06Explain what changedNote which fields were masked or altered so nobody mistakes the sample for production-ready data.

A small representative sample is usually enough to start.

You generally do not need to send an entire historical dataset just to determine whether a workflow is feasible. A small sample containing the relevant scenarios can be enough to map the logic, identify questions, and establish what—if anything—would be needed next.

Operational Alerting Checklist

Every useful alert needs a condition, an owner, a time expectation, and a next step.

TriggerWhat measurable event or condition makes this alert necessary?
ThresholdIs the alert immediate, or should it fire only after a duration, count, percentage, or other threshold is reached?
OwnerWho is responsible for acting on it—not simply receiving it?
ContextWhat information must be included so the recipient can understand the issue without opening three other systems?
ChannelEmail, SMS, Teams, Webex, dashboard, ticket, or another path: where is action most likely to happen?
AcknowledgmentDoes someone need to confirm receipt or ownership?
EscalationWhat happens if nobody acts within the expected time?
ResolutionWhat condition closes the alert and prevents repeated noise after the problem is already being handled?

Automation Project Brief

You can use this outline internally or send the answers to TetherOps. It is enough to start a useful conversation without writing a technical requirements document.

COPY THIS OUTLINE
1 · PROCESSWhat task or workflow are you trying to improve?
2 · TRIGGERWhat starts the process, and how often does it happen?
3 · INPUTSWhich files, systems, emails, forms, exports, or APIs provide the information?
4 · STEPSWhat does a person do today, in order?
5 · RULESWhat gets included, excluded, categorized, matched, calculated, or escalated?
6 · EXCEPTIONSWhat situations make the normal process change?
7 · OUTPUTWhat should exist when the process is complete?
8 · SUCCESSHow will you know the automated workflow is correct and useful?
9 · VOLUMEHow many records, files, calls, events, or transactions are handled per cycle?
10 · SENSITIVITYWhich fields contain confidential or identifying information, and can they be redacted during development?

A USEFUL FILTER

Not everything should be automated.

The process is still changing every week.Stabilize the workflow first or build only the pieces that are unlikely to change.
The “rules” are actually expert judgment.Automation can prepare information and surface exceptions without pretending to replace decisions that require context.
The task is rare and inexpensive to perform manually.Sometimes the simplest process is still the best process.
Nobody can explain what a correct result looks like.Define the desired outcome before trying to encode it.

Found a workflow that checks too many boxes?

Walk us through it. If you can explain how the work happens today, we can help determine what can be automated and what the right first step looks like.

Let's Connect