Shadow Objectives

Everyone has objectives—even if they don’t tell you what they are.

I’ve noticed that if you look closely at the data, you can gain a much better understanding of what someone’s true objectives are. This applies not just to individuals, but to entire groups and organizations.

For example, a company investing heavily in R&D is likely preparing to release a new product. If they’re also submitting a high number of patents, it’s a clear signal they’re trying to secure a legal foothold. By tracking data like this, you can begin to uncover what a company’s true objectives are—those that go beyond their public statements.

This same concept holds true for governments. Watch the data, and you’ll often uncover unstated goals.

This is what I’m calling “Shadow Objectives.” In this article, I’ll explain what they are, how to detect them, and how you can verify when different objectives are actually driving behavior behind the scenes.

What Are Objectives and Key Results?

Objectives and Key Results (OKRs) are simple in theory. Your company defines its main goals (objectives) and how success will be measured (key results).

This system forces focus. It ensures that departments and individuals align their work with specific, measurable outcomes. Typically, teams adopt one or two company-level objectives and set their own aligned goals to help achieve them.

It’s a very metrics-driven approach to ensuring a company is actually doing what it says it wants to do.

However, sometimes you’ll notice something strange: the stated objective doesn’t seem to match what’s really happening.

Departments may instead choose to distract, grow in unrelated areas, or manipulate perceptions—making other teams look worse so they appear better by comparison. These hidden motivations are what I call shadow objectives: the unspoken but very real goals a person, department, or organization is actually pursuing.

How Would You Detect Shadow Objectives?

Start with the money.

Financial data is key. Look at which departments are growing disproportionately without clearly contributing to the company’s stated goals. Accounting data can help identify the areas where expansion doesn’t align with stated objectives.

Next, compare the OKRs at different levels of the organization. Are departments consistently hitting or missing their goals?

A healthy range is about 80% achievement. If a team is always at 100%, or consistently failing, that’s a red flag. It raises the question: What are they really working toward?

With just a few cycles of OKRs and some financial reports, I believe it’s possible to uncover the shadow objectives at play.

What If OKRs Aren’t Stated?

In some companies, no one explicitly states their objectives. Instead, they report only on results—often under the label of KPIs (Key Performance Indicators).

But KPIs alone are misleading if they aren’t tied to an upfront objective. Numbers without context can be used to paint any picture.

In these cases, I recommend ignoring the KPIs altogether. If a team can’t explain what they intended to achieve before doing the work, then the metrics are just noise.

Instead, look at what changed over time:

Did the company acquire more businesses?
Did they take on additional debt?
Was there excessive spending in areas unrelated to their core mission?

These are all strong indicators of what’s actually going on.

Let the Data Tell the Story

It’s my theory that, by analyzing a company’s financial statements, a machine learning model could predict what the company was really trying to do—not based on what they said, but on what they actually achieved.

And this is what I’m calling “Shadow Objectives.”