In the Summer issue of Tribal Gaming & Hospitality, I shared some thoughts about why organizations should resist the urge to jump straight into artificial intelligence before understanding and optimizing the processes underneath it.
The message was simple: Don’t automate a bad system.
But that’s only the beginning.
Once we understand how work is actually getting done, Lean and AI can become powerful tools together. Lean helps us identify the root cause and remove the waste. AI helps us see trends sooner and act with more strategic precision and confidence.
The order matters.
Lean optimizes the process. AI accelerates the insight.
The Waste You Don’t See Still Costs You
One of the concepts we use in business optimization is Cost of Poor Quality, or COPQ. It sounds technical, but the idea is pretty straightforward.
COPQ represents the costs an organization carries because processes aren’t performing at their best.
In gaming and hospitality, that cost can show up as rework on a marketing campaign, an incorrect player offer, a service error that requires recovery, or a guest who leaves unhappy. It can also be the time spent auditing, checking, and rechecking work that should have been done right the first time.
Some of the highest costs, however, are the ones we’ve simply learned to live with.
A skilled host spends hours on manual data entry instead of building guest relationships. A campaign gets stuck in a multi-level approval process. Team members navigate multiple disconnected systems to complete a single guest request. The same guest information gets entered into multiple systems. Marketing, IT, and operations pass information back and forth because systems don’t communicate.
Each one may seem relatively small on its own. Repeat it every day, across departments, and it becomes something else entirely.
Lean gives us a way to identify that waste. One framework uses the acronym DOWNTIME: defects, overproduction, waiting, non-utilized talent, transportation, inventory, motion, and extra-processing.
You don’t have to become a Lean expert to start looking for these things.
Where are we doing work twice? Where are our team members waiting? Where are our guests waiting? Where are talented people spending time on work that doesn’t make good use of their skills? Where are we moving information unnecessarily? Where are mistakes being corrected over and over?
Before you can fix it, you have to see it.
Don’t Just Look at the Final Number
Consider a casino marketing promotion built around a 1,000-seat ticketed dinner show.
The plan projected $122,500 in revenue from tickets, promotional dinners, and drinks. Actual gross revenue came in at $78,800.
You could look at that result and conclude that the promotion didn’t work.
But that doesn’t tell you enough to make a better decision next time.
Look at what was happening inside the process. Only 82 of the targeted 125 four-ticket packages sold. Player information had to be re-entered across marketing, the box office, and player services because the systems weren’t integrated. Hosts didn’t have a real-time list of high-value players to personally invite.
At the same time, drink sales significantly exceeded the original target.
Now we can start asking better questions.
Was the right audience targeted? Where were the bottlenecks? How much time was spent entering the same information more than once? Did our hosts have the information they needed when they needed it? Why did one part of the promotion underperform while another overperformed?
Most importantly, what should the process look like in the future?
That’s where Lean moves us beyond simply identifying the problem. We analyze the current state, find the root cause, remove the waste, and design an optimized future state.
Now Bring in AI
Once the process has been optimized, we can determine where AI belongs in that future state.
Maybe predictive offer and segmentation modeling helps identify the players most likely to respond. Player propensity or churn scoring can help prioritize outreach. Automated host alerts can get information to the right person at the right time. AI can also support demand and staffing forecasting, dynamic pricing, inventory management, and anomaly detection.
The point isn’t to use every capability available.
AI needs a job.
Instead of starting with “Where can we use AI?”, start with the problem.
What are we trying to improve? What is causing the problem? Where is the waste? What should the optimized process look like?
Then ask where AI can help us see something faster, predict something sooner, or automate something that no longer needs to be done manually.
AI is most powerful when it runs on a Lean, optimized process.
Fix the process first. Then accelerate it.
What Did We Actually Improve?
This is where realized value becomes important.
A new process isn’t successful because the process map looks better. An AI initiative isn’t successful simply because the technology works.
What changed?
Did we save time? Reduce rework? Eliminate unnecessary reinvestment? Improve response rates? Reduce guest wait times? Give hosts more time to build player relationships? Improve revenue or market share?
Every improvement should be traceable to something measurable.
That could be time saved, dollars saved through COPQ reduction, revenue growth, or another realized benefit such as guest experience, team member retention, or satisfaction.
If we can’t identify the value created by the change, we need to keep looking.
Start With One Problem
You don’t need a tech team or a big budget to begin.
You need a starting point.
Pick one problem. Look at the current state and use your data to understand what’s actually happening. Identify the waste and the root cause. Remove what isn’t creating value and design a better future state.
Then determine whether AI has a role in making that process faster, smarter, more predictive, or easier for your team to execute.
Finally, measure the outcome.
Lean optimizes. AI integrates. Value is measurable.
AI can help us see patterns sooner. Lean gives us the discipline to address the process behind them. Together, they can create better guest experiences, stronger margins and more resilient operations.
For tribal gaming enterprises, that realized value goes beyond operational efficiency. Better use of our people, technology and resources ultimately strengthens the enterprise and its ability to serve the community.
Start with one problem. Apply one principle. Measure one outcome.
Then build from there.
About the expertise behind this article: Jeff Gray is part of Raving’s Business Optimization team. Learn more about Raving’s work by visiting https://betravingknows.com/services/business-optimization/
