AI Governance
AI PDCA. Finally.
In its recent piece How evals drive the next chapter in AI for businesses, OpenAI points that “Evals” are shaping the future of AI in business.
Eval cycle is defined by OpenAI as Specify, Measure, and Improve.
Specify – Define what “great” looks like: outcomes, workflows, and key decision points.
Measure – Test your system using real scenarios, examples, and metrics.
Improve – Learn from the results, refine your prompts, data, and tools.Sam Altman. Photos: Getty Images.
To many of us, Eval is simply Deming’s PDCA (Plan–Do–Check–Act) and the process approach applied to AI.
Finally! The “wild west” of AI experimentation is hitting a wall. The recent MIT’s State of AI in Business found that 95% of projects yielded no financial return.
It’s time to bring AI ROI back to profitability using proven, time-tested techniques.
🎄AI Forecasting for the Holiday Season
Don’t let the holiday rush overwhelm you. Manually reviewing last year’s spreadsheets can leave you with missed sales and operational chaos. Let AI help!
Here are real examples of how SMEs use AI to plan and forecast for the holiday season.
👥 Zenius.co, remote recruitment company, 30+ employees
The Stack: Zoho Recruit ($25/user/month), Zoho Analytics ($24–$30/month), Airtable ($20/user/month)
The Workflow: Zenius team consolidated years of hiring data in Airtable, pushed it into Zoho Analytics, and let Zia forecast which roles (retail, hospitality, logistics) would surge over the next 12 weeks. Recruiters received pre-matched candidate lists before the rush even started, eliminating emergency vetting and overtime chaos.
📈 The Win: 40% faster time-to-hire during peak season and a 29% drop in recruiter overtime, plus 1–2 recruiter hours freed per week for proactive outreach.
🍋Pearl Lemon AI, fully remote digital marketing agency
The Stack: ChatGPT Team ($25/user/month), Internal Pearl Lemon AI system
The Workflow: Pearl Lemon AI team uploaded 36 months of workload, seasonality patterns, staffing, cost, and lead-flow data into ChatGPT to forecast December spikes and January dips. AI then calculated the exact internal-vs-contractor staffing mix, built timezone-aligned shift plans, and auto-generated schedules through Pearl Lemon’s internal AI system. It scores client renewal likelihood and automated retention emails.
📈 The Win: Accurately predicted Dec and Jan workload changes, cut weekly scheduling time by 60%, and increased January retention by 14%.
🪑Desky, ergonomic-furniture company, 35 employees
The Stack: Forecast Pro ($1,495), HubSpot CRM (~$15–$20/user/month), Zendesk AI (~$55/user/month)
The Workflow: Desky team used Forecast Pro to predict demand at the SKU level for desks and chairs across the Nov–Jan window. Zendesk AI absorbed the holiday surge in customer inquiries, and HubSpot segmented seasonal buyers, letting Desky adjust stock levels dynamically based on real-time buying trends.
📈 The Win: 22.5% reduction in unsold holiday inventory and customer response times cut from 14 hours to 2.5 hours.
💡Key Takeaways
1️⃣ AI Reads the Full Story, Far Beyond Sales Data
While traditional forecasting looks at past revenue, AI can also incorporate market trends, competitive info, staffing capacity, contractor costs, lead flow, turnaround times, and so much more. This multi-layered view can reveal patterns spreadsheets can’t detect.
2️⃣AI Predicts Far More Than Just Demand
From preventing staff burnout to avoiding stockouts, AI optimizes schedules, inventory, and workloads before the rush hits. This leads to fewer surprises, fewer overtime hours, and stronger margins.
3️⃣AI Makes Top-tier Forecasting Available to SMEs
You don’t need a big budget or custom software to predict holiday demand. Tools like Zoho Analytics, ChatGPT Team, and Forecast Pro plug into your existing systems and deliver forecasting accuracy that used to require a data team.
🚀Could you run a billion-user company with just 40 people?
Pavel Durov does.
The 41-year-old founder of Telegram manages one of the world’s most valuable tech platforms with a remarkably lean team. In a recent Forbes article, “The Founder Who Runs A Billion User Company With 40 People And No Phone”, Jodie Cook breaks down the strategies behind his $17.1 billion success.
Here are Durov’s three non-negotiables:
- Forced Automation: Durov refuses to let his engineers hire help. This constraint forces them to build automated systems rather than empires of middle management.
- Hiring via Combat: Durov recruits exclusively through coding competitions. He filters for pure problem-solving ability, hiring winners who have already proved they can handle Telegram’s specific challenges.
- Extreme Discipline: Before touching a screen, Durov starts his day with 300 push-ups and squats. He views self-discipline as the primary muscle that powers all other decision-making.
Takeaway for small business owners: You don’t need more bodies to solve your problems. You need better systems. Durov proves that constraints, like limiting headcount or refusing to check emails first thing, aren’t limitations. They are catalysts for efficiency.
Talk soon,
Natalia