For decades, laboratories have relied on audit trails as the backbone of compliance. In audit trails, every change is logged, every action is timestamped, and every user is recorded. But when something goes wrong or scrutiny intensifies, audit trails often fall short. That’s because traditional lab systems capture records about workflow execution, rather than the actual execution itself. This distinction matters more than most labs realize.
Labbit, a modern lab informatics solution, offers a new approach. It uses the workflow execution as the system of record to enhance data provenance, validation, and compliance.
The problem with audit trails
Audit trails are chronological, reactive logs of changes recorded after the fact. Through the sequential logging of events with timestamps, they allow auditors to reconstruct the history of events from start to finish.
They can also answer simple questions like:
- Who changed this value?
- When was this record modified?
- What was the previous value?
These are necessary and important questions. However, they are not sufficient for labs working within a complex regulatory environment, which must be able to prove compliance.
Audit logs tell you that something happened, but they rarely explain why it happened, what it depended on, or what it caused downstream. They preserve history, but they don’t preserve contextual meaning.
They can also fail to capture actions made in parallel outside the lab system, such as lab staff taking notes on a benchtop notepad or using a separate Excel file, and they can be prone to human errors if instruments aren’t integrated within the system. When this happens, audit trails can be incomplete, making the reconstruction of events difficult.
Furthermore, there’s potential that they are not properly secured. If this is the case, data could be altered, or the audit trail itself could be turned off or deleted.
Thus, audit trails can create a false sense of security for labs that believe that because activity is logged, execution is defensible.
Labbit uses execution as the system of record instead
Most traditional laboratory information management systems (LIMS) treat workflow execution as an activity that produces records — rows, fields, and timestamps — rather than something that is captured structurally. The result is a narrative assembled from audit logs, notes, and interpretations.
Labbit takes a fundamentally different approach, proactively capturing the workflow execution itself as the system of record. It does this by modeling lab work in a knowledge graph, where every executed step is:
- Causally linked: Each action explicitly depends on prior actions and inputs.
- Contextualized: Every step is meaningful within the process that produced it.
- Reconstructable: The full execution can be analyzed, validated, and rerun.
This approach enables Labbit to produce execution semantics. The meaning of a step is stored within the context of the process that produced it. For example, a temperature reading isn’t just a number, a calculation isn’t just math, and an approval isn’t just a checkbox. Each of these things is captured within the context of a workflow step and its execution.
Audit trails describe history, but graphs explain it
While an audit trail is a list, Labbit’s graph is a structure. Graphs show what happened next, as well as what made something possible. They encode cause and effect, and answer questions that audit logs cannot, such as:
- Which prior measurements justified this calculation?
- What exact process path led to this result?
- If an input changed, what downstream outcomes are affected?
Within the knowledge graph, each action derives meaning from its position in the graph and its relationship with what preceded it, what it enabled, and what depended on it.
Provenance is more than lineage; it’s causality
Many traditional LIMS claim provenance because they can trace lineage, from sample to result to report. But true data provenance captures causality, including the relationships between actions, data, decisions, and outcomes. It explains not just where something came from, but how and why it came to be.
In Labbit, executed workflows (workbooks) are provenance. The graph created by execution encodes inputs and transformations, decision points and branches, and dependencies across steps. There is no separate provenance layer. Provenance emerges from executing the workflow. And everything is stored in a secure, tamper-evident graph database with robust, role-based access controls to preserve data integrity.
Validation is strongest when it disappears into execution
The strongest validation is the kind you don’t have to reconstruct. When execution is structural, as it is in Labbit, auditability is inherent. Defensibility is built in, and validation becomes a property of the system, not an afterthought.
Instead of assembling evidence of validation and regulatory compliance after the fact, the evidence already exists because execution itself is the record. This saves staff time and effort, reducing data overload. Instead of having to audit every single change, they verify that the automated workflow was followed.
It’s time for your lab to move beyond the false comfort of simple audit logs
The audit trails offered by traditional LIMS reassure labs that they are meeting compliance objectives. However, audit trails result in an incomplete picture that can lead to false confidence.
Today, in an environment of increasing stakeholder expectations and evolving regulatory requirements, your lab needs more than incomplete logs of what happened. You need a system that doesn’t just record the work, but explains it.
Labbit’s approach makes execution the system of record — ensuring that your lab has accurate provenance, validation, and compliance for every executed workflow — by design.
If you want to see what this looks like in practice, join our upcoming webinar “Electronic Records and Signatures: Rethinking 21 CFR Part 11 in a Graph-Based World.” We’ll explore how modern, graph-based architecture delivers immutable records that preserve context and traceability.
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