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How One Recovery Firm Cut Field Data Lag to Same Day

A disaster-recovery COO scaling crews to 5,000 wired GPS and HR data into a same-day alert feed — catching $100K-a-day field leakage before it compounds.

Same-day data

Replaces two-week reporting lag

< 4 weeks

Implementation Time

$100K – $250K

Project Cost

the challenge

A disaster recovery company that scales from 100 to 5,000 employees during crisis events had no real-time visibility into field operations. Individual days on a job site could cost over $100,000 — and data from the field took up to two weeks to surface. Operational leakage was hiding everywhere: workers logging in before leaving their hotels, trucks not filled to capacity, contract bids placed without current cost data. With no way to see what was happening, there was no way to stop the bleeding.

what they built

Synopsis connected the company's HR systems and field IoT devices — GPS trackers on trucks and phones — and gave them something they'd never had: same-day visibility into what was actually happening in the field. The first thing they built was a simple workflow alert: any worker who logs in but hasn't left for the job site within 30 minutes gets flagged to their on-site supervisor. Small intervention, significant cumulative impact in an environment where a single field day costs over $100,000.

Kris began by addressing master data management — a step most implementations skip. Without entity resolution, the same worker or account appeared under different names across HR systems and GPS devices, making any aggregated view unreliable. Solving this first made every downstream capability trustworthy. With a clean data foundation, Synopsis connected the company's HR systems and IoT GPS trackers on field trucks and phones into a unified real-time operations layer. The first workflow was a simple but high-impact alert: any worker who logs in but hasn't left for the job site within 30 minutes gets flagged to their on-site supervisor. Small intervention, significant cumulative impact in an environment where a single field day costs over $100,000.

best fit for

Mid-market companies with large distributed field workforces — construction, disaster recovery, field services — where money is leaking every day and leadership can't see it fast enough to stop it.

Ai ROLE

The AI integrates data from HR systems and field IoT devices — GPS trackers on trucks and phones — to provide same-day operational visibility into field activity. It triggers automated workflow alerts when field workers log in but do not depart for job sites within a defined window, enabling supervisors to intervene before losses compound across a day that costs over $100,000.

impact

Same-day data

Field operational data that previously took up to two weeks to surface is now available the same day

$100K+/day at risk

Each day of operational leakage costs over $100,000 — real-time alerts let supervisors intervene before losses compound

implementation complexity

The implementation required integrating HR systems with IoT GPS data from field devices — a non-trivial data pipeline — and building a real-time alerting layer on top of a clean entity resolution foundation.

Kris Krisco

Co-Founder @ Synopsis

Synopsis

Co-Founder & CEO of Synopsis, building AI-ready data infrastructure for PE-backed mid-market companies to unify systems, enable trusted insights, and power autonomous execution.

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industry

Construction & Engineering

business organization

Operations

Finance & Accounting

AI TYpe

Data Synthesis & Reporting

Process Automation (RPA + AI)

value type

Cost Reduction

Time Savings

Risk & Compliance

other(firm) Case studies

frequently asked questions

How did a mid-market field-services firm get same-day visibility into its field operations?

The experts started with master data management — resolving the entity-matching problem where the same worker or account appeared under different names across HR systems and GPS devices — so every downstream view was trustworthy. They then connected the HR systems and IoT GPS trackers on trucks and phones into a unified real-time operations layer and built a first high-impact alert: any worker who logs in but hasn't left for the job site within 30 minutes gets flagged to their supervisor. Field data that previously took up to two weeks now surfaces the same day.

What AI tools and approach powered the field operations layer?

The work combined data synthesis and reporting with process automation (RPA + AI), built on a custom/proprietary platform integrating GPS trackers. It started with entity resolution across HR and GPS data, then unified those sources into a real-time operations layer driving workflow alerts.

What results did the field-services firm achieve?

Field operational data that once took up to two weeks to surface became available the same day, and real-time alerts let supervisors intervene in an environment where each day of operational leakage costs over $100,000.

How long did the field operations engagement take?

About four to eight weeks, beginning with master data management before the real-time operations layer and alerting were built.

Who is this approach best for?

Mid-market companies with large distributed field workforces — construction, disaster recovery, field services — where money leaks every day and leadership can't see it fast enough to stop it.

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How One Recovery Firm Cut Field Data Lag to Same Day

Same-day data

< 4 weeks

$100K – $250K

Same-day data

$100K+/day at risk

Kris Krisco

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