In my last article, we talked about why banks need to stop building “Data Swamps” and start building “Supermarkets.”
We agreed that before you buy a Data Lake, you need Logical Structure. You need to build the Aisles: Party (Who), Agreement (What), Event (When), and Location (Where).
But here is the hard truth: Organizing the shelves doesn’t make you money.
Organizing the shelves just allows you to see what you have. Now that we have built the aisles, we have to do the actual job of a shopkeeper: Inventory Management.
You can have the most beautifully organized Dairy Aisle in the world, but if the milk inside the cartons is sour, your customers will still leave.
In the banking world, we call this “Data Quality.”
The Glossy Eye Index
Usually, this is the part of the story where a Chief Data Officer walks into the Boardroom with a 50-slide deck titled “Data Quality Governance Framework V2.0.” It was likely produced by a consulting firm charging $5,000 an hour to state the obvious, and it cost more than the database itself.
And immediately, the Glossy Eye Index hits 100%.
- The CEO checks their watch.
- The CFO falls asleep.
- The Head of Sales starts texting under the table.
Why? Because bankers do not care about data quality. They care about money quality.
If you tell a banker, “Our data is 98% complete,” they will shrug. If you tell them, “We are burning $4 million a year fixing typos,” they will listen.
We need to stop reporting on “Technical Errors” and start reporting on “Business Damage.”
The Mechanic Analogy
When you take your car to the mechanic, you don’t want a report on “Oil Viscosity Coefficients” or “Piston Firing Latency.” You want to know three things:
- Will it start? (Revenue)
- Are the brakes safe? (Risk)
- How much gas does it guzzle? (Cost)
Your Data Dashboard must answer the same three questions. We are throwing away the technical jargon and replacing it with three metrics that actually hurt.
Metric 1: The Ghost Town Ratio (Revenue)
- The Technical Name: Contactability Score
- The Domain: The Party Domain (Aisle 1)
You claim to have 1 million customers in your “Party Domain.” But when we look closer, 30% have no email address, 10% have disconnected phone numbers, and another 25% have “Do Not Market” flags from 2004.
You don’t have a customer base. You have a digital graveyard. You are paying to store terabytes of data on ghosts you cannot sell to.
The Metric to Report:
“65% of our customers are Unreachable Revenue Opportunities.”
Now the Head of Sales isn’t texting. They are panicking.
Metric 2: The Time Bomb (Risk)
- The Technical Name: Orphan Record Ratio
- The Domain: The Agreement Domain (Aisle 2)
This measures active loans, deposits, or trades sitting in your “Agreement Domain” that are not linked to a verified, KYC-cleared human in the “Party Domain.”
Maybe it’s a legacy account from a migration five years ago. Maybe it’s a “dummy” profile created by a branch manager to hit a target.
This isn’t a data error. This is a money laundering investigation waiting to happen. It is a bag of cash left at the airport — if you are holding it and you don’t know whose it is, you are in trouble.
The Metric to Report:
“We are holding $50M in Unverified Assets (Time Bombs).”
This is the only metric that can get the CEO fired. Watch how fast the budget for “Data Remediation” gets approved when you frame it this way.
Metric 3: The Hamster Wheel Index (Cost)
- The Technical Name: First-Time Right / Straight-Through Processing
- The Domain: The Event Domain (Aisle 3)
How many times does a human being have to touch a loan application to fix a typo before it gets booked?
We love to call ourselves “Digital Banks,” but often, we have a basement full of Operations staff manually re-typing addresses because the web form didn’t validate the Zip Code.
This is the “Stupidity Tax.” It is the cost of fixing things we should have gotten right the first time.
The Metric to Report:
“40% of our applications require Manual Janitorial Work.”
Now the COO is listening, because that 40% represents their overtime budget.
The Executive Dashboard
When you present this, do not use a spreadsheet. Use a Traffic Light.
Executives are heat-seeking missiles for bad news. They will skip past all your “Green” success stories to find the one “Red” problem they need to kill.
When the Board sees Red on “Efficiency,” they won’t ask, “How do we write a better SQL query?”
They will ask, “Why are the branch staff bypassing the address validation rules?”
Congratulations. You have just tricked them. You have turned a boring conversation about Data Quality into an urgent conversation about Business Management.
Conclusion: Be a Leader, Not a Librarian
Librarians obsess over whether the books are in perfect alphabetical order. Leaders obsess over whether people are actually reading the books to get smarter.
Stop trying to make bankers fall in love with Data Governance. They never will. It’s like flossing — everyone agrees it’s important, nobody does it, and then they are surprised when their teeth fall out.
Don’t sell them the floss. Sell them the smile.
Show them the price tag of bad data (The Ghost Town, The Time Bomb, The Hamster Wheel), and you won’t have to beg for a budget ever again.
