Build a Lead-to-Cash Dashboard

Build a Google Sheets dashboard for pipeline, invoices, collections, and aging.

Introduction

30 Second Summary

A strong sales total can feel reassuring until unpaid invoices start squeezing the cash available to run the business. The gap between a signed deal and money in the bank is where revenue risk hides.

In this project, you will build a lead-to-cash dashboard in Google Sheets that connects outreach, pipeline, invoicing, collections, and aging risk. A supporting Google Docs case study turns those findings into a safe portfolio story built from synthetic data.

What You'll Build

You will open one dashboard where a healthy closed-won total sits beside the smaller collected-cash figure, making the revenue gap visible at a glance.

By the end of this project, you'll have:

A working dashboard where you can compare total opportunity value, closed-won value, collected cash, outstanding balance, and close rate in one view.
Clear pipeline and aging views that help you identify revenue risk and present three evidence-based actions for Sales and Finance.
A downloadable one-page case study and role-search map that support a focused 90-second portfolio walkthrough.
Secret Mission: Build a prioritized collections action queue with owners and concrete next actions for each outstanding account.

Are there any prerequisites?

You need browser access and a Google Account for the primary path. If you currently use only a Microsoft account, Step 1 guides you through Google Account setup.

Before We Start

This is your moment to commit to a safe portfolio project before the hands-on work begins. You will use only synthetic, non-confidential data to connect your outreach or accounts-receivable experience to the role you want next.

Set Up Your Portfolio Workspace

Your project commitment explains why this portfolio piece matters. The analysis now needs a clean workspace that keeps the numbers beside their business story.

Google Sheets will hold the analysis. Google Docs will hold the case study.

Why Google Sheets first?

Google Sheets keeps the setup short so your lead-to-cash thinking stays visible. A CRM sandbox adds account configuration that would distract from the analysis.

In this step, get ready to:

Create and name the spreadsheet.
Separate the workbook into data and dashboard sheets.
Create and name the case-study document.

Create the spreadsheet

Anyone with a Google Account can create a spreadsheet. The same account keeps both project files in one browser workspace.

Select the tab that matches the account you have now:

✔️ I have a Google Account

Your existing Google Account can create the project workbook.

Click the new-tab button beside your current browser tab.
Enter sheets.google.com/create in the address bar.
Press Enter.
Complete Google sign-in if the browser prompts you.

ⓧ I only have a Microsoft account

A Microsoft account does not create Google Sheets files by itself. The on-screen Google Account setup gives you access to the workbook.

Click the new-tab button beside your current browser tab.
Enter sheets.google.com/create in the address bar.
Press Enter.
Complete the on-screen Google Account setup when the sign-in page appears.
Enter sheets.google.com/create in the address bar after setup finishes.
Press Enter.
Sign in with the Google Account you created.

You should see a blank spreadsheet in your browser. Your first project file is live and ready for structure.

Spreadsheet did not open?

Confirm that the Google Account setup reached completion. Retry sheets.google.com/create while signed in to that account.

Help me fix my Google Sheets access problem.

Organize the workbook

Each sheet gives one workbook a separate working area. The Data sheet holds records while the Dashboard sheet presents the analysis.

Click the current Untitled spreadsheet name at the top left.

The file name becomes editable.

Enter Lead-to-Cash Revenue Dashboard in the file name field.
Press Enter.

The workbook name at the top left now reads Lead-to-Cash Revenue Dashboard.

Double-click the first sheet tab at the bottom of the workbook.

The first sheet name becomes editable.

Enter Data as the sheet name.
Press Enter.

The first sheet tab now reads Data.

Click the plus icon beside the sheet tabs.

You should see a second empty sheet tab at the bottom of the workbook.

Double-click the new sheet tab.

The new sheet name becomes editable.

Enter Dashboard as the sheet name.
Press Enter.

The bottom of the workbook now shows empty Data and Dashboard sheets.

Create the case study document

A case study turns the future dashboard into a story an employer can follow. Keeping it beside the workbook connects your evidence to your explanation.

Open the Google Docs home screen in a new browser tab.
Click Create.

Google Docs opens a blank document.

Click the current Untitled document name at the top left.

The document name becomes editable.

Enter Lead-to-Cash Case Study in the file name field.
Press Enter.

The document name at the top left now reads Lead-to-Cash Case Study.

Predict whether both project file names and both sheet names now match the plan.

Switch back to the Google Sheets tab from earlier.
Confirm that the workbook name reads Lead-to-Cash Revenue Dashboard.
Confirm that the first sheet tab reads Data.
Confirm that the second sheet tab reads Dashboard.
Return to the Google Docs tab from earlier.
Confirm that the document name reads Lead-to-Cash Case Study.

What should I see?

In Google Sheets, the file name reads Lead-to-Cash Revenue Dashboard. The two sheet tabs read Data and Dashboard.

In Google Docs, the file name reads Lead-to-Cash Case Study.

Your portfolio workspace is ready. The analysis file and its business explanation now have clear homes.

Your workspace now connects analysis with explanation. Next, you will build the sales snapshot that looks strong until you inspect the cash.

Build the Sales Snapshot

Your Google Sheets workspace is ready. You now have a clean place to connect your outreach experience with the full lead-to-cash journey.

A headline sales total can look strong while hiding whether any cash arrived. In this step, you will build that deliberately incomplete snapshot using safe synthetic data.

In this step, get ready to:

Add a fixed synthetic dataset for ten business accounts.
Calculate each account's unpaid amount.
Build a two-metric sales snapshot that exposes a missing cash perspective.

Add the synthetic account data

Synthetic data lets you demonstrate business judgment without exposing customer information. The dates represent a fixed analysis snapshot so your results stay reproducible.

Switch back to the Lead-to-Cash Revenue Dashboard workbook from earlier.
Select the Data sheet tab.
Click cell A1.
Paste the full tab-separated table below into A1:

Account	Outreach Channel	Pipeline Stage	Deal Value	Invoice Amount	Amount Collected	Invoice Due Date	Days Past Due	Outstanding	Aging Bucket
Northstar Dental	LinkedIn	Closed Won	12000	12000	12000	2026-10-10	0		Paid
Apex Logistics	Cold Email	Closed Won	18000	18000	9000	2026-09-15	44		31-60 days
BrightPath Clinics	Referral	Closed Won	15000	15000	0	2026-10-14	15		1-30 days
Granite Works	Cold Call	Proposal	22000	0	0		0		Not invoiced
Summit Legal	LinkedIn	Qualified	10000	0	0		0		Not invoiced
Cobalt Media	Cold Email	Closed Won	8000	8000	8000	2026-10-20	0		Paid
Harbor Tech	Referral	Negotiation	25000	0	0		0		Not invoiced
Atlas Fitness	Cold Call	Lost	9000	0	0		0		Not invoiced
Cedar Retail	LinkedIn	Closed Won	14000	14000	7000	2026-08-25	65		61+ days
Evergreen HVAC	Cold Email	Qualified	16000	0	0		0		Not invoiced

How is this snapshot structured?

The Account through Deal Value columns capture sales activity.
The Invoice Amount through Days Past Due columns capture collection status.
The Outstanding column stays blank until you calculate each unpaid amount.
The Aging Bucket column preserves the fixed risk snapshot.

Confirm that the headers span columns A through J.
Confirm that Evergreen HVAC appears in row 11.

Did the data land in one column?

Undo the paste with Cmd+Z on macOS or Ctrl+Z on Windows.
Select cell A1 again.
Copy the entire block with its tab spacing preserved.
Paste the block into A1 again.

Help me separate tabbed data into columns in Google Sheets.

Calculate and format outstanding balances

An outstanding balance is the part of an invoice that remains unpaid. Subtracting the collected amount from the invoice amount reveals that exposure for each account.

Click cell I2.
Enter the outstanding-balance formula by copying the line below:

=E2-F2

What does this formula do?

The formula reads the invoice amount from column E.
It subtracts the amount collected in column F.
The result shows the unpaid amount in column I.

Press Enter to calculate the first outstanding balance.
Select cell I2 again.

The fill handle is easy to miss. It is the small square at the lower-right corner of the selected cell.

Drag the fill handle down through cell I11.

Currency formatting gives every financial column a consistent display. This makes the dataset easier to scan for differences between deal value and unpaid cash.

Drag across column headers D through F to select those columns.
Apply currency formatting with the currency-format control in the Google Sheets toolbar.
Select column I.
Apply currency formatting with the same toolbar control.
Check the calculated values in cells I2:I11.

What should I see?

Cell I2 represents 0 after currency formatting.
Cell I3 represents 9000 after currency formatting.
Cell I4 represents 15000 after currency formatting.
Cells I5:I9 represent 0 after currency formatting.
Cell I10 represents 7000 after currency formatting.
Cell I11 represents 0 after currency formatting.

Do the outstanding values look wrong?

Confirm that the formula in I2 is exactly =E2-F2.
Confirm that the copied formulas change their row numbers through =E11-F11.
Check that invoice amounts are in column E.

Help me debug the outstanding-balance formulas in my Google Sheets dataset.

Build the incomplete dashboard snapshot

A sales snapshot compresses many account records into a few headline metrics. This first version measures opportunity value and closed-won value while leaving the cash question unanswered.

Select the Dashboard sheet tab.
Click cell A2.
Paste the two-row metric block below into A2:

Total opportunity value	=SUM(Data!D2:D11)
Closed-won value	=SUMIF(Data!C2:C11,"Closed Won",Data!D2:D11)

What do these formulas measure?

The =SUM(Data!D2:D11) formula adds every deal value in the dataset.
The =SUMIF(Data!C2:C11,"Closed Won",Data!D2:D11) formula adds deal values only when the pipeline stage is Closed Won.

Predict whether these two totals can prove that cash has arrived.
Check the value in cell B2.
Check the value in cell B3.
Scan below cell A3 for a collected-cash metric.

You should see 149000 in B2. You should see 67000 in B3.

There is no collected-cash metric. That missing perspective is the intended shortfall in this sales snapshot.

Good work. Your dashboard now shows how convincing a sales headline can look before cash enters the view.

Do your dashboard totals differ?

Confirm that the source sheet is named Data.
Confirm that the total opportunity formula covers cells D2:D11.
Confirm that every closed deal uses the exact stage value Closed Won.

Help me find why my Google Sheets dashboard totals differ from the expected snapshot.

✔️ Awesome, I've got everything!

Great. Your fixed synthetic dataset matches the checkpoint. Your incomplete sales snapshot also matches.

ⓧ I'd like to double check the full code

Compare the Data sheet with this reference:

Account	Outreach Channel	Pipeline Stage	Deal Value	Invoice Amount	Amount Collected	Invoice Due Date	Days Past Due	Outstanding	Aging Bucket
Northstar Dental	LinkedIn	Closed Won	12000	12000	12000	2026-10-10	0	=E2-F2	Paid
Apex Logistics	Cold Email	Closed Won	18000	18000	9000	2026-09-15	44	=E3-F3	31-60 days
BrightPath Clinics	Referral	Closed Won	15000	15000	0	2026-10-14	15	=E4-F4	1-30 days
Granite Works	Cold Call	Proposal	22000	0	0		0	=E5-F5	Not invoiced
Summit Legal	LinkedIn	Qualified	10000	0	0		0	=E6-F6	Not invoiced
Cobalt Media	Cold Email	Closed Won	8000	8000	8000	2026-10-20	0	=E7-F7	Paid
Harbor Tech	Referral	Negotiation	25000	0	0		0	=E8-F8	Not invoiced
Atlas Fitness	Cold Call	Lost	9000	0	0		0	=E9-F9	Not invoiced
Cedar Retail	LinkedIn	Closed Won	14000	14000	7000	2026-08-25	65	=E10-F10	61+ days
Evergreen HVAC	Cold Email	Qualified	16000	0	0		0	=E11-F11	Not invoiced

Confirm that columns D, E, F, and I use currency formatting.
Compare cells A2:B3 on the Dashboard sheet with this reference:

Total opportunity value	=SUM(Data!D2:D11)
Closed-won value	=SUMIF(Data!C2:C11,"Closed Won",Data!D2:D11)

Your snapshot now makes opportunity value and closed-won value visible. Next, you will investigate the cash question that these numbers cannot answer.

Reveal the Cash Collection Gap

Your Google Sheets sales snapshot now shows 149000 in opportunity value. It also shows 67000 in closed-won value.

That snapshot still cannot distinguish closed-won revenue from cash collection.

Collection metrics expose the money that arrived. An aging view shows where the remaining risk sits.

In this step, get ready to:

Add collected cash, outstanding balance, and close rate metrics.
Summarize outstanding cash by aging bucket.
Visualize the aging risk in a chart.

Add the cash metrics

Booked revenue describes deals marked as won. Collected cash shows how much money the business has received.

Switch back to the Lead-to-Cash Revenue Dashboard workbook.
Select the Dashboard sheet tab.
Enter Collected cash in A4.
Enter Outstanding balance in A5.
Enter Close rate in A6.

What Do These Metrics Reveal?

Collected cash measures the money already received.
The outstanding balance measures invoiced cash that remains unpaid.
The close rate measures the share of accounts marked as closed won.

Enter =SUM(Data!F2:F11) in B4.
Enter =SUM(Data!I2:I11) in B5.
Enter =COUNTIF(Data!C2:C11,"Closed Won")/COUNTA(Data!A2:A11) in B6.
Format B6 as a percentage.

What Should You See?

Cell B4 shows 36000 in collected cash.
Cell B5 shows 31000 in outstanding balance.
Cell B6 shows a 50% close rate.

Good progress. Your dashboard now separates closed-won value from cash already collected.

Metrics Showing the Wrong Values?

Confirm that B4 contains =SUM(Data!F2:F11).
Confirm that B5 contains =SUM(Data!I2:I11).
Reapply percentage formatting to B6 if it displays 0.5.

Help me troubleshoot my dashboard metrics.

Build the aging pivot table

A pivot table groups repeated labels into categories. It can total the outstanding cash inside each category.

Here it isolates aging risk by showing how long unpaid cash has remained outstanding.

Select the Data sheet tab.
Select the source range A1:J11.
Click Insert in the top menu.
Select Pivot table.
Choose a new sheet as the pivot table destination.
Confirm the destination to create the pivot table.

You should see an empty pivot table with its setup panel ready for fields.

Add Aging Bucket under Rows.
Add Outstanding under Values.
Set Outstanding to summarize by sum.
Add Aging Bucket as a filter.
Exclude Paid and Not invoiced with the aging filter.

What Should the Pivot Show?

The 1-30 days bucket shows 15000.
The 31-60 days bucket shows 9000.
The 61+ days bucket shows 7000.

Pivot Totals Look Wrong?

Confirm that Outstanding appears under Values with sum as its summary.
Confirm that the aging filter keeps the three overdue risk buckets.

Help me fix my aging pivot table.

Chart the outstanding cash

A chart turns the pivot summary into a visible risk pattern. The relative bar heights make collection priorities easier to compare.

Select the aging pivot header plus its three risk rows.
Click Insert in the top menu.
Select Chart.

You should see a chart generated from the aging pivot data.

Double-click the chart to open its editor.
Set Chart type to a column chart under Setup.
Select Customize.
Select Chart & axis title.
Enter Outstanding Cash by Aging Bucket under Title text.

Chart Missing a Risk Bucket?

Select the pivot header plus all three risk rows before recreating the chart.
Confirm that the chart title reads Outstanding Cash by Aging Bucket.

Help me fix my aging chart.

Before you review the finished analysis, which number do you expect to be larger: closed-won value or collected cash?

Return to the Dashboard sheet to compare the five metrics.

What Should the Dashboard Show?

Total opportunity value shows 149000.
Closed-won value shows 67000.
Collected cash shows 36000.
Outstanding balance shows 31000.
Close rate shows 50%.

Switch back to the pivot sheet to inspect the finished aging chart.

You should see a chart titled Outstanding Cash by Aging Bucket. Its tallest risk bar represents the 1-30 days bucket at 15000.

You found the real gap. The business closed 67000 while collecting only 36000.

Next, you'll turn the dashboard into priorities that Sales and Finance can act on.

Turn Analysis Into Decisions

Your Google Sheets dashboard now exposes the gap between closed-won value and collected cash. The next move is to turn that gap into decisions a Sales and Finance team can act on.

A dashboard does not stand out on numbers alone. It earns attention when it points to clear priorities.

In this step, get ready to:

Visualize opportunity value across pipeline stages.
Build a one-screen risk view with overdue values highlighted.
Add three evidence-based recommendations for Sales and Finance.

Build the pipeline-stage chart

A pivot table groups opportunity value by sales stage. This reveals where potential revenue currently sits.

Switch back to the Data sheet from earlier.
Select the range A1:J11.
Click Insert in the top menu.
Select Pivot table.
Choose a blank sheet as the pivot table location.
Add Pipeline Stage under Rows in the side panel.
Add Deal Value under Values in the side panel.
Confirm that Deal Value is summarized by sum.

What does the pipeline pivot reveal?

Closed Won contains 67000 in opportunity value.
Proposal contains 22000 in opportunity value.
Qualified contains 26000 in opportunity value.
Negotiation contains 25000 in opportunity value.
Lost contains 9000 in opportunity value.

Select the complete pipeline pivot output with its headers.
Click Insert in the top menu.
Select Chart.
Double-click the chart to open its editor.
Choose a column or bar chart under Chart type in Setup.
Click Customize.
Open Chart & axis title.
Enter Opportunity Value by Pipeline Stage under Title text.

Strong progress. Your second chart now shows how the total opportunity value is distributed across the sales process.

Chart values look incomplete?

Check that the pivot source covers Data!A1:J11. Confirm that Pipeline Stage is under Rows.

Confirm that Deal Value is under Values with sum selected.

Help me fix my pipeline-stage pivot table.

Highlight risk and arrange the dashboard

Conditional formatting makes overdue values stand out before the viewer reads every row. A one-screen layout keeps the evidence close to the decisions it supports.

Switch back to the Data sheet.
Select the range H2:H11.
Click Format in the top menu.
Select Conditional formatting.
Choose the condition that formats values greater than 0 under Format cells if.
Enter 0 as the comparison value.
Choose a formatting style that makes positive values visually distinct.
Click Done.

The overdue risk pattern is now faster to scan.

What should I see?

Apex Logistics is visually distinct at 44 days past due.
BrightPath Clinics is visually distinct at 15 days past due.
Cedar Retail is visually distinct at 65 days past due.

Return to the sheet containing the pipeline chart.
Click the Opportunity Value by Pipeline Stage chart.
Press Cmd+X (macOS) or Ctrl+X (Windows) to cut the chart.
Click the Dashboard sheet tab.
Press Cmd+V (macOS) or Ctrl+V (Windows) to paste the chart.
Drag the Outstanding Cash by Aging Bucket chart below the five metrics.
Drag the pipeline chart beside the aging chart.
Resize each chart until its title and categories are visible on one screen.

You should now see the five metrics near the top of the Dashboard. Both charts should fit beneath them without covering any values.

The dashboard now reads as one story from headline performance to revenue risk.

Chart disappeared after cutting it?

Return to the Dashboard sheet before pasting. If the chart still does not appear, undo the cut and repeat the move.

Help me move my Google Sheets chart onto the Dashboard sheet.

Add evidence-based recommendations

Recommendations turn the analysis into ownership. Each recommendation should name the priority and connect it to visible evidence.

Enter Recommended actions in cell D1 on the Dashboard sheet.
Enter Prioritize Cedar Retail because it is 65 days past due. in cell D2.
Enter Resolve BrightPath Clinics because its full 15000 invoice remains outstanding. in cell D3.
Enter Protect future cash flow by assigning next actions to proposal and negotiation-stage opportunities. in cell D4.
Select the range D1:D4.
Turn on text wrapping for the selected cells from the toolbar.
Widen column D until each recommendation is readable.
Bold cell D1 from the toolbar.

Before you present the dashboard, which account do you expect a viewer to identify as the highest risk?

Present the Dashboard from top to bottom without opening the Data sheet.
Verify that both chart titles are visible.
Identify the highest-risk account using only the Dashboard.
Read all three recommended actions from the Dashboard.

What should the walkthrough prove?

The metric block shows Total opportunity value 149000.
The metric block shows Closed-won value 67000.
The metric block shows Collected cash 36000.
The metric block shows Outstanding balance 31000.
The metric block shows Close rate 50%.
The Outstanding Cash by Aging Bucket chart is visible.
The Opportunity Value by Pipeline Stage chart is visible.
Cedar Retail is the highest-risk account at 65 days past due.
All three recommendations are readable without opening the raw data.

That is the analysis-to-action leap complete. Your dashboard now directs the next business decision.

Your dashboard is ready to present. Next, you will package its evidence into a one-page case study and a focused role-search story.

Package the Work and Target Roles

Your presentation-ready Google Sheets dashboard now shows the lead-to-cash gap from sales activity through collection. Employers still need a concise story that explains your judgment.

In this step, you will turn the dashboard into a one-page Google Docs case study. You will package that evidence for roles that value your outreach or accounts-receivable background.

In this step, get ready to:

Create a one-page case study from your dashboard findings.
Target roles that connect sales operations with receivables experience.
Prepare a PDF package for applications.

Write the one-page case study

A case study links your analysis to a business decision. It also shows that you can communicate without exposing confidential customer information.

Why pair a case study with the dashboard?

The dashboard demonstrates accurate analysis. The case study demonstrates how you turn that analysis into priorities.

Together, they show the reporting skills plus the operating judgment expected in Revenue Operations work.

Switch back to the Lead-to-Cash Case Study document from earlier.
Type Lead-to-Cash Revenue Dashboard as the document title.

You should now see the project name at the top of the document.

Add Challenge, Method, Finding, Recommendation, and Validation as separate headings in that order.

You should see a five-part structure that moves from the business problem to the reliability of your analysis.

Under Challenge, explain that a healthy closed-won total can hide a cash collection problem.
State under Challenge that every account plus every amount uses synthetic data.

The opening should frame the business problem without referring to real customers or employers.

Under Method, describe how you analyzed the fixed ten-account dataset across pipeline stages plus invoice aging.
Mention the formulas plus pivot tables that produced the metrics and charts.
Under Finding, write the exact gap. 67000 was closed won. 36000 was collected. 31000 remained outstanding.

Your finding should make the cash gap visible in three numbers.

Under Recommendation, prioritize Cedar Retail because it is 65 days past due.
Add a recommendation to resolve BrightPath Clinics because its full 15000 invoice remains outstanding.

These recommendations should connect the aging analysis to immediate collection work.

Add a recommendation to assign next actions to proposal-stage opportunities plus negotiation-stage opportunities.
Under Validation, explain that you checked the dashboard totals against the fixed synthetic source rows.

You should now see all five headings with a concise explanation beneath each one.

Condense the wording until the five sections fit on one page.

The final line of the Validation section should remain on the first page.

Build the role-search map

A role-search map turns your project into a focused job-search tool. Immediate titles align closely with sales support or receivables experience.

Add a Role-Search Map heading below the Validation section.
Add Sales Operations Coordinator, Sales Operations Analyst, and GTM Operations Associate under an immediate titles label.

You should see three immediate titles that connect customer communication with spreadsheet reporting.

Add Revenue Operations Analyst plus Revenue Systems Analyst under a stretch titles label.
Add accounts receivable, billing, order-to-cash, quote-to-cash, pipeline, SaaS, and cloud under a search terms label.

Your map should now separate the three immediate titles from the two stretch titles. The seven search terms help surface roles that value both sides of your background.

Finish the application package

Your resume bullets should describe what you built plus what you found. Every claim should come from this synthetic project.

Keep your evidence honest

Use verbs such as built, analyzed, identified, or recommended. Describe the dataset as synthetic.

Leave past-client outcomes unstated unless you can support them with your own records. This project proves your method plus your judgment.

Add a Resume Evidence heading below the role-search map.
Write the first resume bullet about building a dashboard that connects outreach, pipeline value, invoicing, collections, and aging risk.

The first bullet should tell a reader what you built without claiming a client outcome.

Write the second resume bullet about identifying the gap between 67000 closed won, 36000 collected, and 31000 outstanding.
Write the third resume bullet about converting the analysis into three recommendations for Sales plus Finance.

You should now have three bullets covering the build, the finding, and the business actions.

Structure the 90-second walkthrough

Problem: A strong closed-won total did not show whether cash had arrived.
Analysis: You used synthetic account data to compare pipeline value with collections plus aging risk.
Action: You prioritized Cedar Retail, flagged BrightPath Clinics, and recommended next actions for active opportunities.
Result: The dashboard revealed the cash gap through validated metrics plus two charts.

Add a 90-Second Walkthrough heading below the resume bullets.
Write one short paragraph for each beat in the walkthrough structure.

Your walkthrough should cover the problem, the numeric finding, the recommendations, and the validation method.

Start a 90-second timer.
Deliver the walkthrough aloud from beginning to end.

You should reach the validation method before the timer ends.

Walkthrough running long?

Remove repeated explanations from the Method section. Keep one sentence for each walkthrough beat.

Ask for help tightening the script without changing its evidence: help me shorten my portfolio walkthrough to 90 seconds

Tighten the complete document until the role map, resume bullets, and walkthrough still end on the first page.
Review every claim for unsupported past-client results.

The completed case study should fit on one page. Every result should trace back to the synthetic dashboard.

Click File in Google Docs.
Select Download.
Choose PDF as the file type.

Before you open the PDF, do you expect every section to remain on one page?

Open Lead-to-Cash Case Study.pdf from the Mac Downloads folder.

You should see one page containing the five case-study sections, the role-search map, three resume bullets, and the 90-second walkthrough. The figures should show 67000 closed won, 36000 collected, and 31000 outstanding.

PDF missing or longer than one page?

If the file is missing, repeat the download from the completed Google Docs document. Check the Mac Downloads folder again.

If the PDF has a second page, shorten repeated sentences in the case study. Download a fresh copy after the document fits on one page.

Ask for help preserving the key evidence: help me fit my case study onto one page

You have turned the dashboard into a focused application package. Your analysis now has a clear story plus a verified PDF that you can show.

Secret mission

Build a Collections Action Queue

Your aging analysis identifies delayed cash. Turn those findings into a prioritized queue where every outstanding account has an owner, a next action, and a clear place in the collection order.

Clean Up Your Resources

The core project has no ongoing cost with a Google Account. Choose whether to keep, pause, or delete its resources.

Resources you used:

One Google Sheets workbook named Lead-to-Cash Revenue Dashboard in Google Drive.
One saved filter view named Collections Action Queue inside the workbook.
One Google Docs document named Lead-to-Cash Case Study in Google Drive.
One downloaded PDF named Lead-to-Cash Case Study.pdf in the Mac Downloads folder.

Keep everything running

No action is needed. Choose this option if you want the dashboard and case study ready for future use.

Keep the Lead-to-Cash Revenue Dashboard workbook in Google Drive with its Collections Action Queue filter view.
Keep the Lead-to-Cash Case Study document in Google Drive.
Keep Lead-to-Cash Case Study.pdf in the Mac Downloads folder.

Pause - I'll come back to this later

Pause by leaving the private files in place for your return. There are no running processes to stop.

Leave the Lead-to-Cash Revenue Dashboard workbook private in Google Drive.
Leave the Lead-to-Cash Case Study document private in Google Drive.
Retain Lead-to-Cash Case Study.pdf in the Mac Downloads folder.

Delete - I don't want to use this again

Remove every project resource if you no longer need the work.

Delete the Lead-to-Cash Revenue Dashboard workbook from Google Drive to remove its embedded Collections Action Queue filter view.
Delete the Lead-to-Cash Case Study document from Google Drive.
Empty Google Drive Trash if you need permanent removal.
Delete Lead-to-Cash Case Study.pdf from the Mac Downloads folder.
Empty the Mac Trash if you want the local file removed permanently.

Nice Work!

You did it! Your presentation-ready lead-to-cash dashboard now connects pipeline value to cash collection in Google Sheets.

Your one-page Google Docs case study turns that analysis into a clear portfolio story. The downloaded PDF is ready for applications or interviews.

You learned how to:

Use five dashboard metrics to show that 67000 closed won produced 36000 collected cash. The remaining 31000 stays visible as outstanding balance.
Use pivot tables to separate pipeline value from aging risk. Turn the result into three actions that connect Sales priorities to Finance risk.
Package the analysis as a one-page case study with a documented validation method. Present your thinking through a 90-second portfolio walkthrough.
Secret Mission: Create a prioritized collections action queue for the three outstanding accounts. Assign each account an owner plus a concrete next action.

Ready to quiz yourself?