Before you buy another tool, measure the work

Written By Lauren .

By Jack

Sep 01, 2026

The number of Artificial Intelligence tools available to businesses today is overwhelming.

Every week brings another platform promising dramatic improvements in productivity, growth, cost reduction, and customer experience.

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The temptation is to start with the technology:

Which AI tool should we buy?

I think that’s the wrong first question.

A better question is:

What does your team actually spend its time doing—and what is that work worth to your business?

Before selecting an AI tool, companies should first identify, quantify, and prioritize the operational opportunities AI might solve.

Start by Measuring the Work

Choose a core function such as Sales, Operations, Customer Service, Finance, or Recruiting.

Select several employees performing substantially the same role. Include a representative mix of high and average performers so you’re observing the role rather than one individual’s working style.

Then observe the work.

Document the major activities employees perform throughout the day and capture three things:

1. Time: How long does the activity take?

2. Volume: How frequently is it performed?

3. Value: How much does the activity contribute to revenue, margin, customer outcomes, risk reduction, or another important business objective?

Once the work is understood, categorize the activities using what I call an Operational Value Matrix.

High Effort / High Value: Augment

These activities matter to the business but consume substantial employee capacity.

Don’t automatically automate them. Look for ways technology and AI can make your best people dramatically more productive.

High Effort / Low Value: Eliminate or Automate

This is usually the first place to look for opportunity.

These activities consume meaningful employee capacity without requiring the judgment, expertise, or relationships you’re paying those employees to provide.

Examples might include data entry, information retrieval, repetitive reporting, shared inbox management, routine customer inquiries, scheduling, or administrative research.

Ask:

Can we eliminate the work? Simplify the process? Automate it? Move it to a lower-cost resource? Or use AI to perform or accelerate it?

Low Effort / High Value: Protect and Scale

These are activities you want your people doing more often.

Calling an at-risk key customer. Reviewing a daily exception report. Sales follow up with a qualified prospect.

The objective of automation isn’t simply to reduce labor cost. It should also create capacity for more valuable work.

Low Effort / Low Value: Simplify

Don’t overengineer these activities.

If they consume little organizational capacity and create little value, an expensive AI implementation may produce negligible returns.

Now Quantify the Opportunity

Once you’ve mapped the work, quantify what each activity is costing the organization.

Start simply:

Time per occurrence × frequency × fully loaded labor cost = current activity cost

If five employees each spend ten hours per week performing an administrative task at a fully loaded labor cost of $50 per hour, the organization is consuming approximately:

5 × 10 × $50 × 52 = $130,000 of annual labor capacity.

If a redesigned process or AI solution reduces that workload by 80%, you’ve identified substantial potential capacity.

But don’t stop there.

The value of eliminating work isn’t necessarily equal to the employee’s hourly cost.

Ask what happens to the capacity you create.

If you give a salesperson five hours back every week and those hours produce additional sales, the economic benefit may substantially exceed the labor savings.

If you give a technician additional productive capacity, the value may be incremental gross profit.

If automation allows a growing business to avoid hiring another employee, the value may be avoided cost.

Therefore, evaluate potential improvements across at least four dimensions:

  • Cost Reduction

  • Capacity Creation

  • Revenue or Gross Profit Creation

  • Cost Avoidance

This is where AI moves from an interesting technology experiment to a measurable business investment.

Technology Comes Last

Only after understanding the work and quantifying the opportunity should you ask:

What’s the best solution?

Sometimes it will be AI, traditional automation, process redesign, or sometimes the work should move to a different role.

And occasionally, the right answer is to stop doing the work altogether.

The objective isn’t to implement more AI. The objective is to improve the economics and performance of the business.

Map the work. Quantify the opportunity. Prioritize the highest-value problems. Then select the technology.

Companies that follow that sequence will be in a much better position to capture the extraordinary potential of AI—while avoiding expensive solutions searching for problems.

Thanks for reading! Subscribe for free to receive new posts and support my work.

Lauren .