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Confidential selected work · Enterprise 3PL

A daily view of distribution-center profitability.

Arc Data built a custom application that gives 3PL finance and operations leaders an updated view of facility profitability each day.

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01 Built from operating data

02 Co-designed with decision owners

03 Shipped to replace a real process

Selected work / 01

From fragmented records to one daily profitability signal.

The hard part was agreeing on how profitability should be calculated across finance, labor, and facility activity, then putting that logic into software people could use every day.

Aerial view of an industrial distribution area
Industry photograph. Not a client site.Photo: Marcin Jozwiak / Pexels

Built and delivered

A profitability forecast updated every day

Confidential enterprise engagement

Align the decision

Work directly with executive, finance, and operational leaders to define profitability, reconcile competing business rules, and clarify what the daily forecast must help them decide.

Connect the operating record

Integrate financial actuals, timesheet data, and operational signals from the systems already used across the business.

Replace the old process

Deliver an application that absorbs new data, recalculates the distribution-center profitability forecast daily, and gives leaders a common product around which to operate.

What Arc Data builds

Custom software for the decisions 3PL leaders make every day.

We start with the decision. Then we choose the data, architecture, and interface needed to support it.

01 / Decide

Software for executive and financial decisions

Forecasting, profitability views, scenario tools, and operating reviews shaped around a decision leaders already need to make.

  • Operating-model definition
  • Forecast and planning logic
  • Role-specific product design

02 / Connect

Cross-system operational data

We build on the systems already running the business, including WMS, LMS, HRIS, ERP, TMS, and spreadsheets.

  • Source-system integration
  • Shared business rules
  • Data quality and reconciliation

03 / Replace

Software that replaces manual work

Purpose-built applications that move a process out of fragile handoffs and into a repeatable, owned operating workflow.

  • Workflow and application engineering
  • Human review where judgment matters
  • Adoption with process owners

A focused first conversation

Start with a process that no longer works.

Bring the forecast, review, or operational call your team no longer trusts. We will work through the decision, the people involved, the source systems, and the friction in the current workflow.

  1. 01

    Name the decision

    What must a finance or operations leader decide, and what makes the current answer arrive too late?

  2. 02

    Trace how the answer gets built today

    Which systems, manual inputs, owners, and business rules create the answer today?

  3. 03

    Choose a practical first project

    Decide whether the right next move is discovery, a focused prototype, or no project at all.

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Exploration library

Reference Patterns

Illustrative only. The Reference Patterns below are thought experiments for discussing adjacent 3PL opportunities. They are not client case studies, delivery claims, or evidence of work performed. Any approach would need to be validated against real data, operating constraints, and user needs.

RP1 Illustrative pattern

Detecting Logistics Anomalies

A BlueYonder event stream could be explored for work patterns that may indicate unrecorded value-added services or operational exceptions requiring review.

Candidate methods: Autoencoders or Isolation Forest for anomaly screening; XGBoost or Decision Trees for review prioritization. Method choice would depend on the available data and validation design.

Potential operating aim
Billable exception capture
Potential review cadence
Same-day visibility

RP2 Illustrative pattern

Predictive Capacity Hedging

An LTL planning concept could combine confirmed freight with historical lane behavior to help teams examine when and where capacity is likely to be underfilled.

Candidate methods: LSTM or Prophet for forecast exploration; Reinforcement Learning only where a safe objective, constraints, and evaluation framework can be established.

Potential operating aim
Fewer underfilled moves
Potential planning posture
Earlier load shaping

RP3 Illustrative pattern

Contract-to-cash decision support

Coming Soon

Exploration note in development

Tell us what your team is struggling to answer

It may be a good fit for custom software.

We’ll talk through the problem, the current process, and the systems involved.

Engage Arc Data tyler@arcdata.co