S1E46 Exploring ServiceNow's Strategic Portfolio Management

Steele plays "Joe Schmoe", submits an espresso machine idea, then flips roles to the demand manager and carries it through ServiceNow Strategic Portfolio Management. Along the way, Steele and Pops cover how ideas get in, what a demand has to capture, and why a project can be approved and still not be able to start.

In this episode:

- Two intake paths: the service catalog form and the idea portal with crowd voting

- What a demand holds: sponsors, business justification, cost, risk, target dates

- Why vendor approval and MSA status belong on the demand

- Catching duplicate demands before they become projects

- Scenario planning in place of spreadsheet one and spreadsheet two

- The out-of-the-box business case tab Pops hates the most

- After launch: benefit plans, cost plans and the feedback loop

If you don't put the data in, the platform can't help you. That is the thread running through the whole episode.

KEYWORDS: ServiceNow SPM, ServiceNow Strategic Portfolio Management, ServiceNow demand management, ServiceNow idea portal, ServiceNow business case, ServiceNow scenario planning, ServiceNow Strategic Planning Workspace, ServiceNow goal framework, demand intake, portfolio management, value realization, project portfolio, IT leadership, ITSM, enterprise IT, The Wired Garage with Pops

See ya later.

The conversation explores the significance of portfolio management, its challenges, classic tools and frameworks, the impact of technology, and the role of AI in reshaping portfolio management. It emphasizes the importance of strategic decision-making, governance, and the shift from manual reporting to continuous intelligence.

Takeaways

• Portfolio management bridges strategy to execution
• AI shifts decision-making from project tracking to strategic investment
• Portfolio managers focus on strategic decision-making and organizational change management

Chapters

• 00:00 – Intro & Series Kickoff
• 00:42 – What Is Portfolio Management?
• 01:47 – Why Organizations Struggle
• 02:23 – Tools & Frameworks
• 04:03 – What's Changed Recently
• 04:53 – The Bottom-Line Impact
• 06:05 – The Human Element & Change Fatigue
• 07:07 – The Endurance-Race Analogy
• 07:55 – Case Study: The $30M CIO
• 10:05 – The Building-Blocks Analogy
• 11:00 – Enter AI: Real-Time Intelligence
• 12:40 – AI Easing PM Burnout
• 14:30 – Agentic AI in Action
• 15:45 – Are Portfolio Managers Still Needed?
• 16:53 – Wrap-Up & Next Episode Tease

Toby shares insights into managing a home lab, the challenges faced, and the transformative impact of leveraging AI to improve management and automation. He discusses disaster recovery testing, observability, and the applicability of home lab learnings to enterprise IT.

Takeaways

• AI can transform home lab management
• Disaster recovery testing is essential for home lab resilience

Chapters

• 00:00 Introduction to the Home Lab
• 03:01 Challenges of Managing a Home Lab
• 06:19 Leveraging AI to Improve Home Lab Management
• 15:30 Testing and Implementing Disaster Recovery
• 24:25 Observability and Future Plans
• 26:01 Applicability to Enterprise IT

The conversation with Chad Mattix delves into the concept of AI as an operating model, emphasizing the importance of human oversight and decision-making. It explores the integration of AI into business operations, the impact on scalability, and the need for clear governance and context. The discussion also highlights the challenges and considerations in deploying AI, including token consumption, cost evaluation, and the role of AI as a co-pilot rather than an autopilot.

Takeaways

• AI as an operating model
• Human oversight and decision-making
• Integration of AI into business operations
• Challenges in deploying AI
• Token consumption and cost evaluation

Chapters

• 00:00 Introduction to AI as an Operating Model
• 01:13 AI as an Operating System for Kinetics
• 05:00 Data Governance and AI Integration
• 06:31 Impact on Business Scalability
• 22:54 Challenges in Deploying AI
• 35:09 AI as a Co-Pilot, Not an Autopilot

The conversation with Chad Mattix delves into the concept of AI as an operating model, emphasizing the importance of human oversight and decision-making. It explores the integration of AI into business operations, the challenges of AI governance, and the need for a balanced approach to automation. The discussion highlights the role of AI in enabling scale and efficiency while empowering human workers to make informed decisions.

Takeaways

• AI as an operating model
• Human oversight and decision-making
• Balanced approach to automation
• AI governance and challenges
• Empowering human workers

Chapters

• 00:00 AI as an Operating Model
• 05:00 The Role of Human Oversight
• 06:10 Challenges of AI Governance
• 09:00 Balanced Approach to Automation
• 17:17 Empowering Human Workers
• 22:54 AI Integration and Business Operations
• 38:06 The Future of AI in Business

S1E39 Someone Racked Up $2,000 on AI in 24 Hours. Here's What They Did Wrong

Pops and Steele dig into a problem hiding in plain sight: uncontrolled AI subscription spend. As teams experiment freely with AI tools — often on personal corporate cards with zero IT or finance visibility — costs are quietly compounding into what could become a governance crisis. The two draw parallels to the early days of cloud computing and Shadow IT, arguing that AI subscriptions, tokens, and usage-based billing need to be tracked like any other IT asset, ideally landing in a CMDB. They walk through real-world cautionary tales (a $2K/day AI bill, a Meta token-spend anecdote), debate who actually owns AI risk within an organization, and lay out a practical cadence for reviewing AI spend — monthly until you understand it, then scaling back. The episode closes with concrete advice: read the fine print on your AI tool's usage limits, bring a real cost forecast to finance early, and don't wait for the invoice to start the conversation.
Key Takeaways

Shadow AI hides wherever there's no intake and governance process — not in one department, but across every team running its own point solutions.

Usage-based billing breaks traditional software asset tracking. Unlike flat licensing, token/consumption-based spend is jagged and hard to forecast without active monitoring.

Treat AI subscriptions like governed IT assets — track what models, datasets, and prompts are in use, ideally inside a CMDB, the same way you'd track any other asset with blast-radius risk.

Review cadence should match maturity, not comfort: monthly (or even daily/weekly for new capabilities) until the org actually understands its usage pattern — then it can stretch to quarterly.

Ownership of AI risk is shared, but accountability isn't. The team that brings a tool in without going through proper process still owns the consequences.

Bring a number to finance before they ask for one. Proactive cost forecasting protects the relationship — and the budget.

"Ferrari to the grocery store" problem: using frontier/premium models for simple tasks is where a lot of runaway spend comes from — match the model to the job.

AI spend management, Shadow AI, Shadow IT, AI asset management, CMDB, IT asset management, ITAM, AI governance, token-based billing, usage-based billing, AI budget, finance and IT alignment, AI subscription tracking, consumption-based licensing, AI cost governance, enterprise AI adoption, CAB governance, AI risk management
Suggested CTAs

Is AI spend already a line item at your shop — or are you still finding out about it from the invoice? Drop a comment and let us know.

If you're wrestling with AI governance at your org, hit subscribe — we're covering this space every week.

Tag someone in IT or Finance who needs to hear this before the next invoice lands.

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S1E13 Significance of community for IT leaders with Michael Alshouse
In this episode of The Wired Garage, Michael Alshouse from Byteworks joins to discuss insights from leading IT leadership roundtables and the vital role of community among technology leaders. Focusing on healthcare IT, he explores how organizations are tackling evolving cybersecurity threats, mounting compliance demands, and vendor complexity—all while realizing the promise of AI and automation. Alshouse shares practical guidance for CIOs and IT executives on building strong peer networks, avoiding common leadership pitfalls, and aligning strategic priorities with organizational goals. The conversation offers a grounded look at how modern IT leaders can navigate change and empower their teams in a rapidly shifting digital landscape.

Keywords
IT leadership, cybersecurity, healthcare technology, AI automation, peer networking, compliance, vendor management, roundtable discussions, technology insights, cybersecurity, regulations, community, technology adoption, service desk

Takeaways
Community is a cheat code for modern IT.
AI policies help govern the use of technology.
Prioritize strategic work over mundane tasks.
Healthcare organizations face unique cyber risks.
Building trust in peer networks enhances idea sharing.
Community is essential for modern IT leaders.
Healthcare organizations face unique IT challenges.
AI is a hot topic but requires careful governance.
Cybersecurity is a new normal for IT leaders.
Regulatory pressures can be overwhelming; seek peer advice.
Building a peer network can provide valuable support.
Automation can significantly improve IT operations.
Top-down leadership is crucial for technology adoption.
Learning from peers can save time and resources.
Establishing comfort at the leadership level is key.

Chapters
The Importance of Community in IT Leadership
Navigating Healthcare IT Challenges
The Role of AI in IT Operations
Cybersecurity in Healthcare: A New Normal
Understanding Regulations and Best Practices
Leveraging Automation and AI for Efficiency
Building Your Own Network of Peers
The Role of Leadership in Technology Adoption

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S1E14 Balancing Fatherhood and Fitness with Michael Alshouse
In this episode of The Wired Garage, Michael Alshouse shares insights on balancing fatherhood, health, and sports. He discusses his ideal day as a dad, which includes early morning workouts, smoking meat, and spending quality time with family. The conversation delves into the importance of family dinners, the challenges of parenting, and how to instill a love for sports in children. Alshouse emphasizes the need for balance in life, the significance of accountability in fitness, and the joy of sharing sports experiences with family.

Keywords
dad life, health, family, sports, parenting, cooking, fitness, balance, traditions, routines

Takeaways
Early morning workouts are essential for personal time.
Cooking meat on a Traeger takes patience and skill.
Family dinners provide energy and connection.
It's okay to have off days in fitness routines.
Involving kids in physical activities fosters family bonding.
Accountability is crucial for maintaining fitness goals.
Balancing health and family requires planning and flexibility.
Sports can be a shared family experience.
Teaching kids about winning and losing is important.
Traditions in sports can create lasting memories.

Chapters
The Dream Day of a Dad
Balancing Health and Family Life
Cherishing Family Moments
Navigating Fatherhood and Family Dynamics
Balancing Health and Family Life
Starting Your Health Journey
Sports Fandom and Team Loyalty
College Basketball Passion
March Madness vs. College Football
The Impact of NIL on College Sports
The Evolution of NFL Offense
Integrating Sports into Family Life
Lessons in Sportsmanship and Team Spirit

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