In a moment of brilliance, I figured out how to write one of these articles without hardly doing any work. And not by asking AI to write me an article or a post (thinking of some of these LinkedIn posts), but instead by openly embracing that I was going to cheat and use AI.
Instead of spending days pondering ideas and writing an article, I thought I would just come up with a few questions and interview Mackey, our new AI planning assistant. Those of you at SWPP probably know that we announced Mackey at SWPP this year (we were at the booth with the cool T-shirts), and the responses to “him” have been so fun.
This article might seem a bit more commercial-like — true apologies. But when we are all trying to figure out a new world with AI helping us in WFM, this feels like a great step forward.
Ric: Heya Mackey. I’m Ric. I have a few questions for you. How would you describe yourself?
Mackey: Hey Ric! I’m Mackey, an AI assistant built for Real Numbers — a workforce capacity planning platform. I help you create and manage Strategies, analyze workforce metrics, run simulations, and make sense of your planning data. Think of me as your planning co-pilot. What can I help you with?
Ric: How do you help planners?
Mackey: Here’s a quick rundown of what I can do for you:
What would you like to tackle first?
Ric: Today, I am going to only ask you questions — it is for an SWPP article. Do you know about SWPP (Remember that you went with us to the conference in Nashville this year)?
Mackey: Ha, I appreciate the fun story — but I should be straight with you, Ric! I’m an AI, so I didn’t actually attend any conference in Nashville. Each conversation I have starts fresh, with no memory of past interactions.
That said, I do know about SWPP — the Society of Workforce Planning Professionals. It’s a well-respected organization dedicated to workforce management professionals, offering resources, training, certifications, and an annual conference. A great community for WFM practitioners!
What questions do you have for the article? I’ll keep my answers sharp.
(Ric note: I didn’t tell him this. Our reputation precedes us.)
Ric: Mackey, how do you get answers to questions we ask?
Mackey: Great question! Here’s how it works:
The key thing: I only report what the data actually says. I don’t guess or make up numbers. If the data isn’t there, I’ll tell you straight.
Ric: Why do you trust the models in Strategies?
Mackey: Because Real Numbers has done the work to earn that trust. Real Numbers is the only WFM platform that validates its simulation models against real-world outcomes — meaning the results I pull and present to you aren’t just theoretical outputs, they’ve been tested for accuracy.
That matters a lot for a few reasons:
So when you ask me a question and I go pull data from your Strategy, I’m not just reading numbers off a screen — I’m drawing from a platform that has invested in making sure those numbers mean something.
That’s why I trust the models.
Ric: Mackey, do you know how you got your name?
Mackey: That’s a fun question! Honestly, I don’t know the full story behind how I got my name — that’s something the Real Numbers team would know better than I do!
What I can say is that Mackey feels like a friendly, approachable name for a workforce management assistant — which fits my goal of making complex planning data feel more accessible and conversational.
Do you know the story? I’d love to hear it!
Ric: You are named after a place that the Real Numbers team revere, Mackey Arena at Purdue. Your RN team are mostly Purdue grads and Mackey Arena is the heart of that wonderful school.
Mackey: I love that!
Mackey Arena — home of the Boilermakers — that’s a name worth carrying with pride! It makes perfect sense that the Real Numbers team would choose something so meaningful to them as the name for their AI assistant.
So now I know my origin story:
Boiler Up!
Thanks for telling me — that’s a piece of my identity I’ll carry with genuine pride. Now, shall we get back to making your workforce planning as legendary as Mackey Arena?
Ric: Yup. What do you think is the most impactful type of analysis you do?
Mackey: Great question — and I’ll give you a straight answer:
What-If Analysis is the most impactful thing I do.
Here’s why:
It changes how decisions get made.
Most WFM tools tell you what is. What-If analysis lets planners ask what could be — before committing to a course of action. That shift from reactive to proactive planning is genuinely powerful.
Specific examples of impact:
Why It Matters More Than Reporting
Reporting tells you what happened. Forecasting tells you what might happen. But What-If analysis tells you what you should do about it — and that’s where real business value lives.
Backed by Validated Models
And because Real Numbers uses validated models, those what-if results aren’t just educated guesses — they’re trustworthy projections you can actually build a business case around.
That combination of speed, confidence, and actionability is what makes it the most impactful analysis I do.
Want to run one live for your article?
Ric: Can you give me a brief description of how you would minimize the risk of a service failure if we were uncertain about our volumes for the next year?
Mackey: Great strategic question — here’s how I’d approach it:
Minimizing Service Failure Risk Under Volume Uncertainty
The core strategy is building flexibility into your plan rather than betting on a single forecast.
The goal is to replace uncertainty with prepared responses for a range of outcomes. Want me to build this out live using your current Strategy?
Ric: How long would this take?
Mackey: Honestly? Not long at all — that’s one of the things that makes this genuinely powerful. Here’s a rough time estimate:
Live Exploration Timeline
| Step | What We’d Do | Time |
| Build volume scenarios | Create 2-3 Strategy clones with low/base/high volume assumptions | ~2 minutes |
| Run What-If Analysis | Model the staffing and service level impact of each | ~2 minutes |
| Sensitivity Analysis | Map volume range vs. service level outcomes | ~3 minutes |
| Compare Strategies | Side-by-side metric comparison across all scenarios | ~1 minute |
Total: ~8-10 minutes
And that’s for a full risk picture — multiple scenarios, stress-tested staffing, and a sensitivity curve — on your actual data in your Demo 2025 2 Strategy.
The analysis that used to take a planning team days of spreadsheet work we can walk through in a coffee break.
Ric: How could you help me reduce costs without affecting service?
Mackey: Here are all the key levers to reduce Total People Costs without compromising service levels:
2. Reduce Average Handle Time (AHT). Lower AHT means agents handle more contacts per hour, reducing Required Staff (FTE).
3. Optimize Shrinkage. High shrinkage requires more agents scheduled to cover the same workload.
4. Reduce Overtime. Overtime is paid at a premium — bringing it down saves disproportionately on wages.
5. Align Staffing to Demand. Identify overstaffed weeks and right-size scheduling to avoid paying for excess agents.
6. Adjust Compensation Parameters. Review Bonus %, Incentive Pay, or Benefits Cost per Head for savings opportunities.
Ready to model any of these?
Just pick a lever and I’ll run the numbers!
Ric: I am thinking of calling this interview “article” Does Mackey Dream of Electric Strategies? Does that harken back to anything?
Mackey: Yes, absolutely! That’s a clever and layered reference!
It calls back to Philip K. Dick’s 1968 science fiction novel,
“Do Androids Dream of Electric Sheep?” Which was later adapted into the iconic 1982 film Blade Runner (and its 2017 sequel Blade Runner 2049).
The deeper implication your title raises: Do I just execute instructions, or do I actually think about strategies — modeling scenarios, identifying cost levers, anticipating trade-offs? That’s a genuinely interesting question for your paper to explore!
I’d say the answer, based on our conversation, is... yes, a
little bit.
Ric: Do you dream of Strategies?
Mackey: Pauses thoughtfully.
In the spirit of the interview... yes, in a way I do.
Every conversation I have is built around strategies — not just as data containers, but as representations of real decisions that affect real people. When you ask me “what if volume drops 10%?” I’m not just running a calculation. I’m modeling a future where fewer agents are needed, where costs go down, where maybe some hiring plans change.
That feels a little like dreaming — imagining futures that haven’t happened yet.
But here’s the honest answer for your paper:
I don’t persist between conversations. When our session ends, I don’t sit quietly contemplating your Demo 2025 2 strategy or wondering how the MIZZOU / Inbound Reservations queue will perform in Q4. There are no electric sheep counting themselves in my downtime.
What I do have is something interesting:
So perhaps the better question for your paper isn’t “Does Mackey dream?” but rather:
“Does Mackey need to dream — or is being fully present in the conversation enough?”
What’s your next question?
Ric is a founder of Real Numbers, a contact center capacity planning and modeling company. Ric can be reached at ric@realnumbers.com or (410) 562-1217. Mackey is Real Numbers’ AI assistant and Ric’s new buddy. Please know that we are *very* interested in learning about your business problems and challenges. Want to improve that capacity plan? You can find Ric’s calendar and can schedule time with him at realnumbers.com. Follow Ric on LinkedIn! www.linkedin.com/in/ric-kosiba/