People Operations Consulting & Executive Search for Growth Companies | Recruiting Wisdom

Your Gut Instinct Isn't the Problem. Your Decision System Is.

Mon, 31 Aug 2026 15:36:16 -0700

Your Gut Instinct Isn't the Problem. Your Decision System Is.

Why growth companies need decision science - not more interview data - to make smarter, faster, and more defensible hiring decisions.

"I just have a better feeling about this candidate." Almost every executive has said some version of it. I have too. Gut instinct is not the problem. Unchecked gut instinct is.

Experienced leaders develop pattern recognition. They notice how candidates frame problems, respond to pressure, navigate ambiguity, and connect their experience to the work ahead. That
judgment matters. It should remain part of the hiring process. But judgment becomes risk when nobody can explain what created the feeling, test it against contradictory evidence, or compare it consistently across candidates.

That is where decision science belongs in hiring. Decision science is not about letting an algorithm select your next executive. It is the disciplined practice of combining human judgment, behavioral science, structured evidence, and analytical methods to improve how a decision is made.

In my conversations with growth companies, I am seeing the demand shift. Leaders are not only asking how to reach more candidates or move them through the process faster. They are asking
how to make the decision once strong candidates are in front of them. They want a clearer view of risk, evidence gaps, and tradeoffs - without surrendering the judgment or accountability of the people making the hire.

The distinction is important because companies are adopting more technology without necessarily building better decision systems. SHRM reported that AI adoption in HR tasks rose from 26% in 2024 to 43% in 2025....Read More

AI Can Measure Performance. That Doesn’t Mean It Can Manage People

Tue, 23 Jun 2026 09:38:03 -0700

AI can identify patterns that a human manager may never see. It can also make a flawed decision at a speed and scale no human manager could ever match. That creates a question every founder, CEO, and business leader will eventually need to answer:

Should AI be allowed to manage people?

My honest answer is that I am still on the fence.

I do not believe the right answer is to keep AI completely outside the management process. The technology can analyze enormous amounts of information, identify inconsistencies, detect emerging problems, and surface insights that even strong leaders can miss.

But I am equally uncomfortable with a future where an algorithm quietly determines:

Who receives the best assignments
Who is considered a high performer
Who receives a raise or promotion
Who is placed on a performance plan
Who is identified as a retention risk
Who is ultimately shown the door

AI can make management more intelligent. That does not mean we should allow it to become the manager.

This Is Not a Future Problem

“Algorithmic management” sounds like something that belongs in a future-of-work presentation. It is already here.

The OECD defines algorithmic management as technology that partially or fully automates work traditionally performed by managers. That can include assigning schedules and activities, monitoring work time and speed, tracking communications, setting targets, rewarding performance, and sanctioning poor performance.

In a survey of more than 6,000 mid-level managers across six countries, the OECD found that 90% of U.S. firms surveyed used at least one form of algorithmic management. More than three-quarters of U.S. managers said their organizations used at least 10 of the 15 categories included in the study.[1]

There is an...Read More

Conversational AI Isn’t the Strategy, Your Operating System Is

Mon, 30 Mar 2026 12:56:58 -0700

#ConversationalAI #AIinBusiness #PeopleOperations #BusinessStrategy

Conversational AI is quickly becoming the most overhyped and under-delivered tool in business today. Everyone’s talking about it - Few are actually using it to drive outcomes.

Based on my conversations - companies are typically stuck in one of three traps:

Automating conversations instead of improving decisions
Layering AI on top of broken processes
Treating it like a tool… instead of a system

Conversational AI doesn’t create value - Well-designed systems do.

So how do you actually cut through the noise?

A simple, no-BS framework:

1. Start with the outcome, not the tool
What decision should be faster, better, or more consistent?
Hiring? Customer qualification? Internal alignment?

If you can’t tie it to a measurable business outcome → it’s fluff.

2. Fix the process before you “AI” it
If your hiring, internal mobility, or client workflows are inconsistent…
Conversational AI will just scale the inconsistency.

Garbage in → faster garbage out.

3. Design for signal, not conversation
The goal isn’t better ‘chats’. The goal is finding patterns.

Think:
Candidate quality signals - Customer intent - Internal performance blockers

That’s where leverage lives.

4. Embed it...Read More

The Disconnect: Growth-Stage Companies Aren’t Hiring to Business Outcomes

Mon, 23 Feb 2026 14:41:34 -0800

In the scramble for growth, small and mid-sized companies are obsessed with speed to hire. They hire recruiters, launch job ads, and rush through interviews, but the needle on business outcomes barely moves. What’s going on?
The root of the problem isn’t talent scarcity. It isn’t volume of applicants. It’s a flawed talent operating model, and a culture that confuses activity with impact and administrative HR with strategic people operations.
Data shows that most small businesses struggle just to fill open positions, let alone align hiring with strategic goals. Nearly two-thirds of small business owners report hiring challenges due to limited qualified applicants, competition on compensation, and lack of resources.
Meanwhile, foundational HR teams in these businesses often spend 36% of their time on back-office tasks and compliance - not strategic workforce planning.
This structure creates a paradox: companies care about growth and talent in principle but lack the operational framework to tie talent decisions directly to business outcomes, and they don’t think about succession plans until catastrophe strikes.

The center of the disconnect as I see it.
Too often, companies equate HR with people/talent strategy, when in reality:
HR historically focuses on compliance, payroll, benefits administration, and employee relations.
Recruiting focuses on sourcing and filling roles.
People Operations focuses on integrating workforce strategy with business outcomes, from hiring all the way through retention.
In...Read More

Hiring the Right People at the Wrong Time Is Still a Talent Failure

Wed, 21 Jan 2026 15:18:32 -0800

Many organizations still struggle to find top talent in key moments. That challenge is real, and it's not going away. But there’s an equally damaging issue that shows up after the search, and it’s discussed far less often.
Organizations also struggle to sequence leadership and capability correctly. Even when companies hire strong people, they often hire them out of order, and that misalignment affects execution, momentum, and value.
This isn’t a recruitment problem. It’s a talent operating model problem.
Why “Good Hires” Still Fail to Create Momentum
Across industries, I see the same pattern repeat:
A leadership or critical skills gap becomes visible
Pressure builds
A role opens quickly
A strong candidate is hire
Execution doesn’t accelerate the way leadership expected
That’s when you will hear – “They weren’t the right hire.”
In reality, the hire may have been strong, just early, late, or mis-sequenced relative to what the business actually needed next. Hiring quality and hiring timing are not the same thing – both matter, most organizations only manage one.
Sequencing Can Be The Missing Layer Between Strategy and Execution

Sequencing answers the fairly uncomfortable question – what capability must exist next for this organization to move forward now, not down the line. When sequencing is missing, organizations default to:
Hiring based on urgency instead of leverage
Filling multiple leadership roles in parallel without clear...Read More

Strategic Talent Acquisition: How Hiring Drives Revenue Growth

Tue, 14 Oct 2025 14:39:17 -0700

#TalentStrategy #GrowthLeadership #PeopleOperations #Startups #ScaleIntelligently
Most companies still treat Talent Acquisition as a necessary expense, sort of - something you must do when someone leaves or when a new project requires headcount.
Companies that scale sustainably - especially in tech startups, VC/PE portfolio companies, and high-growth sectors like fintech, healthcare, and manufacturing are integrating talent acquisition as a revenue engine instead of a cost center.
Below, quick outline on how to build a talent-led growth motion that aligns people, brand, and relationships directly to revenue.
1. Build a Talent Function that Mirrors Your Sales Organization
Revenue-driven hiring starts by syncing your talent strategy with your sales and product forecasts.
The sweet spot lies in predictive hiring models & aligning headcount planning directly with projected ARR, billable utilization, or client onboarding capacity.
This means talent leaders should have access to the same data your CRO does. They should be part of pipeline review meetings, product roadmaps, and delivery management discussions.
When executive talent acquisition is tied to forward-looking revenue metrics, it stops being reactive and starts becoming enablement.
2. Treat Employer Brand Like a Demand Generation Channel
Great candidates follow strong employer brands, but so do future clients, partners, and investors.
Employer branding builds market trust. When people see a company culture that values...Read More

Building a Data Culture *Strategies that actually stick*

Thu, 04 Sep 2025 07:07:06 -0700

Companies with mature, data-drivenHR strategies outperform peers by 20% in revenue per employee (Gartner). Yet most leadership teams still struggle to embed data into daily decision-making. In my latest blog, I share the strategies that actually work forbuilding a sustainable data culture.
I often hear executives and senior leaders talk about becoming data-driven organizations, yet many of us still struggle with truly embedding this philosophy into our corporate DNA. Building a lasting, data-driven culture, especially within HR, certainly includes leveraging bleeding-edge tech and investing in legacy analytics tools, but without fundamentally transforming how leadership teams and employees engage with, interpret, and act with data, there is no long-term culture shift.

A data-driven culture is imperative for a sustained competitive advantage, period, end of blog 🙂 You’re not that lucky. Keep reading for insights, formulas, and overall geeking out on the subject.
Companies That Harness HR Data Effectively Experience:
Increased Profitability: Companies with mature data-driven HR strategies outperform peers by 20% in revenue per employee.
Enhanced...Read More

How AI is Helping Technology Companies Overcome Skills Gaps and Boost Training

Tue, 12 Aug 2025 08:32:14 -0700

Not surprising considering the pace at which technology is evolving, specifically within the AI/ML space, that skill gaps have emerged as one of the most pressing challenges organizations face. These gaps touch almost every aspect of the tech stack, from cybersecurity & cloud computing to software development & artificial intelligence, technology companies often struggle to find and retain talent equipped with specialized, future-ready skills. Yet, AI-driven solutions have become a powerful ally for bridging these gaps while enhancing employee training and organizational outcomes.
Understanding the Skills Gap Challenge
Several studies, including insights from HR Dive and CompTIA, highlight key areas where skill gaps are most exposed:
Cybersecurity: According to various case studies on average – 65% of companies identify cybersecurity as a critical skills gap, affecting roles such as security analysts and network...Read More

From Workflow Chaos to Talent Strategy: The Recruitment Reboot

Tue, 10 Jun 2025 15:08:20 -0700

#RecruiterEnablement #WorkflowAutomation #TalentAcquisition #FutureOfWork

Talent acquisition isn’t an issue because of a pipeline problem; it’s usually an issue for one of two reasons:
- Because your recruiters are stuck playing calendar Tetris and toggling between five platforms just to schedule one interview, rather than doing what they’re best at - recruiting, selling the company vision to the talent community, and building employer brand value.
- Because your corporate hiring strategy is broken, you aren’t ready to face it, and the people you have hired to advise you on hiring strategy have been reduced to glorified workflow managers, and on bad days - part-time therapists.
If this feels uncomfortably familiar, you’re not alone. But here’s the good news: AI isn’t here to replace recruiters, it’s here to release them.
What’s Broken in the Current Talent Acquisition Workflow?
The average recruiter today is spending less than 30% of their time actually building rapport with candidates. The rest? Endless coordination, duplicate data entry, inbox juggling, and documentation. Aptitude Research Report:
- 72% of recruiters say they don’t have time to be strategic.
- 63% say manual screening and admin tasks are their biggest productivity blockers.
- And only 26% of TA teams report confidence in their ability to consistently hire top performers.
Where Generative AI Starts to Shift the Game
Unlike traditional AI which relies on rigid rules - GenAI adapts to context, learns your organization’s hiring DNA, and can create new outputs based on lengthier inputs:
1. Contextual Resume Screening
No more keyword bingo. GenAI understands that "built internal dashboards" in a startup resume could match "data visualization...Read More

Unlocking Manufacturing Success with People-Led HR Efficiency:

Wed, 28 May 2025 08:07:05 -0700

Unlocking Manufacturing Success with People-Led HR Efficiency:
HR teams face significant pressures to support production demands, ensure regulatory compliance, and enhance workforce agility. Despite these expectations, common HR inefficiencies often create blockers to achieving optimal operational performance. Adopting a people-centric approach, with strategic technology utilization, can significantly transform manufacturing HR functions, turning blockers into advantages.
Common HR Inefficiencies in Manufacturing:
- Talent Acquisition Struggles: Persistent skill shortages and industry misconceptions prolong vacancies and elevate hiring costs.
- High Employee Turnover: Insufficient employee engagement and ineffective onboarding processes contribute to costly turnover.
- Manual, Outdated Processes: Over-reliance on manual tasks and outdated systems slow decision-making and hinder responsiveness.
- Compliance and Safety Challenges: Complex regulations and training requirements pose continual challenges for HR teams.
- Limited Data Utilization: Under utilization of data analytics limits informed decision-making regarding workforce management and strategic planning.
Strategic People-Led Solutions:
A strategic, people-focused HR model effectively addresses these inefficiencies by placing employee engagement, technology integration, and continuous improvement at the forefront. Organizations that successfully deploy these solutions will see improved outcomes, such as:
- Enhanced employee retention through targeted engagement and career development.
- Streamlined recruitment and onboarding processes powered by AI-driven solutions.
- Increased workforce agility and responsiveness through real-time data analytics.
Common Manufacturing Executive Concerns:
Concern:...Read More