100% OCCUPANCY DOESN'T MEAN THE RIGHT TENANT MIX

A shopping mall reaches 100% occupancy. There are no vacant units left to lease. On paper, that is about as clean a sign of commercial health as the industry can ask for.

But suppose one fashion tenant is in the wrong part of the property. Another category occupies more space than its contribution justifies. Two individually successful brands weaken rather than reinforce each other as neighbours. A high-value unit is occupied, but by a tenant whose potential might be greater somewhere else.

The mall is still 100% occupied.

So what exactly is the 100% telling us?

Occupancy is important, of course. Empty units affect rental income, visitor perception and the overall commercial strength of a property. No landlord is going to stop caring about vacancy because someone wrote an article questioning occupancy. But occupancy answers a very specific question: how much of the available space is leased? It does not necessarily tell us whether that space is being used in the most productive way.

Experienced leasing teams have understood this distinction long before anyone started talking about artificial intelligence. Tenant mix has never simply meant filling empty boxes on a floor plan. Category balance, anchors, adjacencies, visitor profile, circulation, price positioning and the identity of the property all influence leasing decisions. Sometimes an experienced leasing manager can look at a unit and immediately know that a particular concept is unlikely to work there, even when the brand itself is strong.

That Experience Matters Because A Tenant Does Not Perform In Isolation

The same brand can perform very differently in two shopping malls. It can also perform differently in two locations within the same mall. Visibility changes. Visitor movement changes. The neighbouring brands change. Proximity to anchors, food and beverage, entertainment or vertical circulation changes. The city and catchment change. Even the reason visitors use that particular part of the property can change.

This means tenant mix is not really a list of brands.

It is a network of commercial relationships.

Once we look at it that way, the floor plan begins to mean something different. A store is not simply 400 square metres occupied by a fashion tenant. It is 400 square metres interacting with everything around it. The performance of that space is connected not only to the strength of the tenant, but also to where it sits, what surrounds it and how visitors behave in that environment.

This is also why a property can improve commercially without adding a single square metre and without increasing occupancy by a single percentage point.

The Opportunity May Already Be Inside The Occupied Space

Consider a simple example. A strong fashion brand is performing reasonably well in its current unit. There is no obvious problem to solve. But perhaps the same brand would perform significantly better in another part of the property. Perhaps another category would create more value in its current location. Perhaps changing that relationship would also benefit neighbouring tenants. The existing situation is not necessarily bad. It may simply not be the best available configuration.

And that is a much harder thing to identify.

Vacancy announces itself. Underperformance does not always do us the same favour.

We can see an empty storefront. We can measure lost rent. We can put the unit on a leasing list and begin looking for a tenant. An occupied unit that is producing acceptable results creates much less urgency. It may remain exactly where it is for years because nothing appears to be wrong.

But “nothing is wrong” and “this is the best possible outcome” are very different standards.

This is where the traditional strength of historical reporting also reaches a natural limit. We can know last month's footfall. We can know a tenant's turnover. We can analyse category performance, rent-to-sales ratios and historical trends. Those numbers are essential for understanding the property.

But they describe the performance of the tenant mix that already exists.

The More Difficult Question Is What Might Happen Under A Tenant Mix That Does Not Exist Yet

What if a different sector occupied a particular unit? What if an existing tenant moved twenty metres, one floor, or from one commercial cluster to another? What if a neighbouring brand changed? Could the turnover potential of that space change? Could the surrounding area change with it? Could a decision that appears to affect one lease eventually influence a wider part of the property's commercial performance?

Those are not questions that should be answered by intuition alone. But they should not be handed blindly to an algorithm either.

The leasing team knows things that are difficult to capture in a model. A brand may be changing strategy. A retailer may be preparing to enter or leave a market. Negotiations have context. Relationships matter. Investment requirements matter. Architectural constraints matter. Timing matters. Sometimes the commercially correct decision on paper simply cannot happen in the real world.

The objective of technology should therefore not be to replace leasing judgement. It should be to give that judgement another perspective.

This is one of the areas we are exploring with PredictAI at EPPSO. By examining relationships between historical commercial performance, tenant characteristics, location, adjacency, visitor behaviour and lease economics, the ambition is not to create a machine that declares which brand belongs in which unit.

That would reduce a complicated commercial decision to a recommendation button.

The More Interesting Objective Is To Evaluate Possible Outcomes Before The Decision Is Made

Instead of asking only which tenant is available for an empty unit, we can begin asking which type of commercial use appears to have the strongest potential there. Instead of looking only at whether an existing tenant performs well, we can ask whether the relationship between that tenant and its location appears to be working as well as it could. Over time, the same thinking can extend beyond turnover toward the question that ultimately matters to the owner: how could these decisions affect the income and long-term commercial productivity of the property?

None of this makes tenant mix a mathematical problem.

If anything, it makes the problem more visible.

For decades, experienced leasing teams have been building this understanding through years of observation: which brands work together, which locations behave differently, how visitor patterns evolve, when a category has become too dominant, and when a tenant that looks right on paper simply does not belong in a particular place.

The opportunity now is not to discard that experience. It is to combine it with the growing amount of operational and commercial information properties already generate, and use both to examine possibilities that are difficult to evaluate from historical reports alone.

Because the next major improvement in a mature shopping mall may not come from constructing more space.

It may not come from attracting more visitors.

It may not even come from signing another tenant.

It may come from looking at a floor plan everyone already considers successful and asking a more uncomfortable question:

If we were making these decisions today, knowing everything we know now, would we put the same tenants in the same places?

A shopping mall can reach 100% occupancy.

The harder question is whether it has reached 100% of its commercial potential.