How to Prioritize Which Burglary Cases to Investigate

Estimated reading time: 9 minutes

Departments face different pressures, but many are working hard to balance two competing realities: every burglary case matters, and investigative resources are limited. When caseloads stack up, even well-staffed property units can struggle to give each case the level of attention they’d like.

And the reality? Most burglaries don’t get solved.

So what if there were a simple, evidence-based way to determine, from the very beginning, which cases actually have a chance?

That’s exactly what one research team in the UK developed: a solvability calculator built from thousands of burglary reports. It is a tool that can help prioritize which cases have a realistic chance of being solved, not because any case is unimportant, but because spreading investigators thin across every file often means fewer cases reach the finish line.

Imagine having instant clarity on which cases fall into “strong leads,” “possible leads,” or “unlikely with current information.” That kind of insight doesn’t replace investigative judgment—it supports it, helping detectives spend their limited time where it can make the biggest impact.

Let’s dig into what the study found.

What the Research Says About Burglary Solvability

Researchers Tom Olphin, Siddhartha Bandyopadhyay, and Anindya Banerjee reviewed 9,655 burglary cases from a UK police force. This wasn’t a small sample or a pilot. It was 3 years’ worth of real cases with real investigative work attached.

One important feature of the study is that the researchers didn’t rely only on the standard checkboxes in the reporting system. They also pulled information from the narrative portions of the reports, where officers often document details, actions, or opportunities that don’t always get captured in structured fields. This gave them a fuller picture of what investigators actually had to work with.

In total, they coded 253 different pieces of information from these reports and later narrowed that list down to the 40 factors that were most useful for predicting solvability.

To make sure the model actually worked, they split the dataset in half.

• Half of the cases were used to build the model, basically teaching it which factors were associated with solved burglaries.
• The other half was used to test it, meaning the model had to predict solvability on cases it had never “seen” before.

This approach allowed the researchers to check whether the model could reliably identify which cases had a realistic chance of being solved, based on the information available early in the investigation.

Key Factors That Predict Whether a Burglary Will Be Solved or Unsolved

The study identified 31 factors that show up more often in solved burglaries and 9 factors that appear more often in cases that remain unsolved. These are patterns based on thousands of real investigations.

Top factors associated with solved cases

1. An arrest already made
2. Any level of suspect information from the victim — such as a name, description, or address
3. Short “between times” — meaning the window between when the crime could have happened and when it was discovered was less than an hour
4. CCTV available — cases without camera footage were more limited
5. DNA recovered

Other helpful indicators included:

• Quick reporting to police
• Witnesses
• Stolen property recovered
• Seizure of suspect clothing
• Digital leads (usernames, phone data, card activity)

Factors associated with unsolved cases

To make the findings practical, the study also highlighted patterns in cases that typically don’t get cleared, below are a few examples:

• No CCTV available — officers have fewer avenues to identify the suspect
• No suspect found — meaning no workable lead was identified through canvassing or initial investigative actions
• Negative house-to-house — either no canvass of the neighborhood was done, or officers conducted a canvass, but no witnesses, cameras, or leads were identified
• Delayed reporting — long gaps between discovery and notifying police create fewer investigative opportunities

Choosing Cut-Off Scores to Prioritize Investigations

To evaluate how well their model worked, the researchers took the second half of the dataset (cases the model had never seen) and checked whether its predictions matched whether those burglaries were actually solved or not. This allowed them to estimate how accurate the tool would be in real investigative triage.

A key part of the tool is the cut-off score, which is simply the threshold a department chooses for deciding which cases should be assigned to detectives. Lower cut-offs mean more cases get assigned; higher cut-offs mean investigators focus on the strongest leads.

Here’s what the testing showed:

Cut-off score: 3.2

• 93% of solvable cases were correctly assigned for investigation
• 39% of unsolvable cases were correctly filed
  • Meaning the system flagged them as having so little information that a full investigation was unlikely to lead anywhere
• 33.5% reduction in investigative workload
  • About 1,049 fewer cases per year
  • Roughly £555,000 saved (about $720,000 USD)

Cut-off score: 2.8

• 87% of solvable cases correctly assigned
• 52% of unsolvable cases correctly filed
• 42.2% reduction in workload
  • About 1,321 fewer cases per year
  • Roughly £700,000 saved (about $900,000 USD)

The researchers note that some cases predicted as “solvable” were not solved in real life. They suggest that limited time and staffing may have prevented investigators from fully working those cases, meaning the model may be identifying cases that could have been solved with more resources.

Try the Burglary Solvability Calculator (Free Excel Tool)

In the research article, the authors created a predictive solvability algorithm using the factors outlined above and presented it in chart form. The goal is to help departments assign cases to detectives only if they meet a predetermined threshold for solvability. I’ve taken those values and built a user-friendly Excel tool where you can select the relevant case details and instantly generate a predicted solvability score.

Here’s how it will work:

1. Enter your cut-off score, just like the thresholds tested in the study (e.g., 3.2 or 2.8)
2. Select the factors present in this case.
3. Receive a predicted solvability score based on the research

Choosing a cut-off is important. A higher cut-off means focusing on the cases with the strongest leads; a lower cut-off means assigning more cases but spreading resources thinner. Agencies can decide what fits their workload, staffing, and priorities.

It’s also important to note: this study tested the model on past cases only, not in a live operational setting. The calculator should be seen as an aid for decision-making, not a replacement for investigative judgment.

The goal is simple: help departments focus their limited investigative time on the burglaries that have the best chance of being solved, instead of unintentionally spreading resources so thin that strong cases don’t get the attention they need.

Benefits of Using a Solvability Tool for Burglary Investigations

Picture a mid-size department drowning in 20-40 new burglaries a month. Detectives are burned out. Sergeants are forced to triage cases based on gut feeling and skimmed reports.

They start using the solvability calculator.

A case comes in where:

• A neighbor saw the suspect
• DNA was recovered
• The burglary happened during daylight
• Reporting was fast

The calculator spits out a solvability score well above the cut-off. It gets pushed to detectives immediately.

Another case shows:

• No CCTV
• No suspect info
• Delay in reporting
• House-to-house turned up nothing

The score is far below the cut-off. Rather than burying detectives with another likely-dead-end case, the department provides the victim with prevention advice and closes the case appropriately.

Over time, the unit notices something: Detectives finally have the breathing room to fully work the cases that have a stronger chance, not just the ones that happen to land on their desk.

That’s what this tool is for: a practical, organized way to make the most of limited investigative time.

Final Thoughts

Burglaries cost communities billions, financially and emotionally. Property crime units are often stretched thin. This study offers a simple, credible, evidence-based way to prioritize the cases that detectives can realistically investigate.

What’s surprising is that 40 different factors can actually predict whether a burglary will be solved. It really highlights how much useful information is already sitting in reports. Information that often isn’t being used to guide investigations.

I’ve included an Excel-based calculator based on the study, so you can see how it works with your own cases.

It’s important to note, though: this tool has only been tested on past cases, not in real-time operations. More research is needed to understand how effective it would be as a live triage tool in an active department.

Until then, here’s the takeaway: Use the data you already have to help make investigators’ workloads more manageable and give more victims a real chance at justice.

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Carlee Ruiz

Carlee Ruiz is the founder of PoliceResearchHub, a platform that turns academic research into practical insights for law enforcement. She brings seven years of experience as a crime analyst and justice researcher, with a focus on evidence based policing, gun violence prevention, and public safety strategy. Carlee currently works as a researcher at National Policing Institute, where she supports evaluations of law enforcement programs and criminal justice initiatives across the country. Through PoliceResearchHub, she aims to make research easier to understand and more useful for the people doing the work on the ground.