What Is Depersonalized Data in FoodBank Manager?

What is depersonalized data in FoodBank Manager?

Depersonalized data is central to how FoodBank Manager (FBM) protects client identities while still giving food banks the reporting insights they need.

Rather than sharing names, addresses, or other sensitive details, FBM uses a hashing system that removes identifiable information from client records when data is reported at the food bank level.

What is depersonalized data?

Depersonalized data refers to information that has had all personally identifiable details (PII) removed or replaced, making it impossible to trace the data back to an individual.

In FBM, depersonalization is achieved through data hashing. Hashing takes sensitive values — like a name or address — and converts them into a long, unreadable string (called a “hash”) that looks like this:

• "Don DeDecker" → 2a54b8a0654d8f583ba377f37432e8f403495154

• "3209 W Cactus Rd" → fdfb808a2dbd4a479abd251eaf133188b5a59a46

These hash values are used instead of actual names or addresses when data is pushed to the FBM Data Lake.

Why is depersonalization important?

• Limits legal risk in a data breach

  If a bad actor gains access to depersonalized data, it’s meaningless. There are no names, addresses, or identifying details — just hash strings and statistics.

• Builds trust with agencies and clients

  Agencies serving undocumented or vulnerable populations often fear shared systems. Depersonalized reporting allows participation without compromising safety or dignity.

• Supports privacy-by-design architecture

  FBM avoids the risks of shared databases by segmenting data and only sending depersonalized reports to the food bank level.

What data is depersonalized?

When FBM pushes agency-level data to the central reporting system (called the “Data Lake”), the following types of data are depersonalized:

Note: The same client at different agencies will produce the same hash — allowing visit tracking across the network without exposing identity.

How is this different from anonymized data?

Anonymized data is often stripped of PII but may still be vulnerable to inference or re-identification. FBM’s hashing approach creates permanent, consistent values that cannot be reversed — making the data both useful and safe.

A balance of insight and protection

FBM’s depersonalized data model provides the best of both worlds:

• Food banks gain accurate, unduplicated reporting across agencies and regions

• Agencies and clients enjoy strict data separation and privacy

This design is what makes FBM uniquely capable of delivering both granular control and aggregate insight — without compromise.

Summary

• FBM uses hashing to depersonalize client data at the reporting level

• This approach protects client privacy while enabling regional data analysis

• Depersonalization helps meet privacy standards and limits exposure in the event of a breach

Need help understanding FBM’s reporting model or privacy settings?

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