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Dealership CFO

Monitor daily cash position and floor plan management

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What You Do Today

Review cash balances, floor plan interest accrual, and upcoming cash requirements—payroll, manufacturer draft, floor plan curtailments. Manage the relationship between vehicle inventory, floor plan financing, and cash flow.

AI That Applies

AI forecasts daily cash positions based on expected vehicle sales, manufacturer draft timing, and scheduled disbursements. Automated alerts flag when floor plan curtailments are approaching.

Technologies

How It Works

The system ingests expected vehicle sales as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output is a prioritized alert queue, with the highest-confidence findings surfaced first for immediate review.

What Changes

Cash forecasting becomes more accurate and granular, predicting daily positions rather than weekly estimates.

What Stays

Managing the delicate balance between inventory investment and cash flow—deciding when to buy aggressively versus conservatively—requires business judgment shaped by market experience.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for monitor daily cash position and floor plan management, understand your current state.

Map your current process: Document how monitor daily cash position and floor plan management works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Managing the delicate balance between inventory investment and cash flow—deciding when to buy aggressively versus conservatively—requires business judgment shaped by market experience. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support CDK Global tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long monitor daily cash position and floor plan management takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your CFO or VP Finance

What's the current accuracy of our forecasting, and how would we know if an AI model is actually better?

They're prioritizing which finance processes to automate first

your ERP or finance systems admin

Which historical data do we have that's clean enough to train a prediction model on?

They know what automation capabilities exist in your current stack

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.