Reporting, Data Analysis & Business Intelligence
Data Analysis Pivot Grid Engine
The Data Analysis engine in MRSware Desktop is a multi-dimensional pivot grid allowing instant slicing and dicing of agency financial performance across any combination of fields.
The 5 Magical Columns
Every Data Analysis view centers around 5 core financial metrics:
| Metric Column | Description |
|---|---|
| 1. Sales Dollars | Total invoiced dollar volume. |
| 2. Cost Dollars | Cost of goods or factory baseline cost. |
| 3. Gross Margin | Net margin dollar spread (Sales - Cost). |
| 4. Commission Dollars | Total gross commission earned by the agency. |
| 5. Commission Rate % | Effective commission yield percentage (Commission / Sales). |
Customer Ranking & Ship-To Analysis
Run Top 20 Customer Ranking views by Principal, Product Line, or Territory. Utilize Ship-To analysis to track where products are physically delivered versus billed.
Share of Wallet OLAP Cube & Whitespace Discovery
While traditional sales reports only analyze invoiced revenue, MRSware's dedicated Share of Wallet Analysis OLAP Cube (ShareOfWalletCube.cdl) bridges the gap between sales figures and estimated wallet spend potential.
The Share of Wallet cube automatically unifies actual sales invoice transactions with customer potential benchmarks via an intelligent outer union dataset. If an account has an estimated spend potential of $500,000 in a category but has generated $0 in sales, the cube surfaces the customer row with 0.0% Share of Wallet and $500,000 Uncaptured Spend. This instantly illuminates white space that would remain completely hidden in traditional invoice-only reporting.
1. Multi-Dimensional Cube Dimensions
Analyze wallet capture from every perspective in the Data Analysis pivot grid:
| Dimension Hierarchy | Field / Attribute | Strategic Analytical Use |
|---|---|---|
| Customer Dimension | Customer Contact Name & ID | Identify top accounts by uncaptured dollar spend and overall wallet retention. |
| Product Category | Catalog Item Type | Pinpoint which product categories have low agency penetration across customer tiers. |
| Principal / Manufacturer | Manufacturer Contact Name | Compare actual factory billings against estimated addressable factory spend. |
| Sales Representative | Sales Rep Display Name | Evaluate rep performance based on account penetration percentage rather than raw volume alone. |
| Competitor Dimension | Incumbent Competitor Name | Map out competitor market share across territories to plan targeted displacement campaigns. |
| Geographic Breakdown | Business State & City | Discover regional whitespace pockets and underserved geographic territories. |
| Time Dimension | Invoice Year, Quarter & Month | Track year-over-year share expansion and quarterly penetration velocity. |
2. Calculated Measures & Performance Indicators
- Actual Sales (Currency): Sum of invoiced sales revenue for the selected time period and dimension slice.
- Estimated Spend Potential (Currency): Aggregated wallet size defined on customer master profiles for that calendar year.
- Share of Wallet % (Calculated Summary): Evaluated dynamically in real-time as
(Actual Sales / Estimated Spend Potential) * 100. Displays0.0%when no sales exist. - Uncaptured Spend (Calculated Summary): Computes
Estimated Spend Potential - Actual Saleswhen spend potential exceeds revenue. Instantly prioritizes accounts by actionable dollar upside.
3. Share of Wallet Analysis SSRS Report
For executive committee meetings, manufacturer annual reviews, and rep quota discussions, MRSware provides a standard cross-module SQL Server Reporting Services (SSRS) report: Share of Wallet Analysis (Share of Wallet Analysis.rdl) accessible in Report Explorer:
- Parameter Filtering: Filter simultaneously by Year, Customer, Product Category, Principal, and Sales Rep.
- Executive KPI Cards: High-level KPI summaries for Total Estimated Wallet, Realized Agency Revenue, and Overall Wallet Share %.
- Drill-Down Matrix: Grouped tabular presentation by Customer, Category, and Principal with color-coded variance indicators.
- Universal Export: Export finalized presentations to PDF, Excel, or CSV with preserved formulas and styling.
Customer Retention & Attrition Analysis (OLAP Cube & Churn Analytics)
In wholesale distribution and manufacturers' representative operations, customer accounts rarely send formal cancellation notices. Instead, customer churn manifests quietly as lapsed purchase frequency or zeroed replenishment orders. MRSware Desktop provides automated Customer & Revenue Attrition Analysis designed specifically to monitor account retention, quantify lost sales volume, and flag dormant customers before relationships dissolve.
Rather than relying on static calendar quarters, MRSware computes customer attrition across a non-overlapping Rolling 12-Month Inactivity Window:
- Baseline Cohort ($T_{-24}$ to $T_{-12}$ Months): All customer accounts that generated at least one invoice and > $0 in sales volume during the prior 12-month period.
- Active Current Cohort ($T_{-12}$ to $T_{0}$ Months): Customer accounts that generated invoiced sales during the active trailing 12-month period.
- Churned Customer Criteria: A baseline customer is classified as Churned if:
- They generated exactly $0 in sales across the entire current 12-month window; OR
- All associated customer accounts in
OMCustomerAccounthave an explicit deactivation date recorded (DisableDate ≤ CurrentDate).
1. Dual Attrition Metrics: Account vs. Revenue Churn
Losing five low-volume accounts has a vastly different financial impact than losing a single flagship Tier-1 customer. MRSware measures both account counts and dollar volumes simultaneously:
👥 Customer Attrition Rate %
Measures the percentage of prior active customer accounts that stopped purchasing entirely:
💵 Revenue Attrition Rate %
Measures the gross dollar revenue loss attributable directly to churned accounts:
2. Dedicated Data Analysis OLAP Cube ("Customer Retention & Attrition Analysis")
To pinpoint exactly where account attrition is occurring across product lines and sales territories, MRSware includes a dedicated pre-configured OLAP Cube: Customer Retention & Attrition Analysis (registered in DACubeDefinition). Rep agencies can drag and drop fields to slice retention metrics across any organizational hierarchy:
| Cube Dimension | Field / Attribute | Analytical Value |
|---|---|---|
| Customer Dimension | Customer Contact Name & ID | Isolate specific accounts that generated revenue in the prior year but $0 in the current year. |
| Principal / Manufacturer | Manufacturer Contact Name | Identify manufacturer product lines experiencing customer drop-off versus expansion. |
| Sales Rep on Customer | Customer Sales Rep Name | Review account retention rates by assigned territory manager or agency account rep. |
| Sales Rep on Invoice | Invoice Sales Rep Name | Analyze churn by originating transaction sales rep split crediting. |
| Geographic Breakdown | Business State, City & Zip Code | Detect regional attrition trends or geographic territories experiencing competitive displacement. |
| Time Dimension | Invoice Year, Quarter & Month | Analyze retention seasonality and trailing purchase patterns leading up to account dormancy. |
3. Calculated Summaries & Churn Indicators
- Prior Year Sales (Currency): Total invoiced baseline sales generated during the baseline comparison period.
- Current Year Sales (Currency): Total invoiced sales generated in the active period.
- Sales Variance ($) (Calculated Summary): Dollar difference (
Current Year Sales - Prior Year Sales), clearly highlighting revenue gains in positive values and losses in negative values. - % Change (Calculated Summary): Relative growth or contraction yield:
((Current Year Sales - Prior Year Sales) / Prior Year Sales) * 100. - Lost Revenue ($) (Calculated Summary): Captures prior baseline dollars specifically for accounts that dropped to exactly $0 in the current period:
(Prior Year Sales > 0 && Current Year Sales == 0) ? Prior Year Sales : 0. - Churned Flag (1=Yes, 0=No): Integer binary measure (
1if Prior > 0 and Current == 0, else0) allowing instant pivot aggregation of total lost accounts by sales rep, manufacturer, or state.
Line Profitability Analysis (True Net Margin & LPF Scorecard)
In multi-line sales rep agencies, gross sales volume and headline commission rates often mask whether a product line or customer account is actually profitable to represent. High-maintenance principals may demand excessive field sales time, extensive travel, or specialized technical support that erodes agency commissions. Conversely, lean lines with automated ordering may yield exceptionally high net margins despite lower top-line commission percentages.
MRSware Desktop's Line Profitability Analysis OLAP Cube (LineProfitabilityCube.cdl powered by LineProfitabilityData.edl) unites four operational streams into a unified profitability ledger: Invoiced Sales & Commission Splits, Activity Hours & Timer Logs, Direct Field Expenses, and Qualitative Line Performance Factor (LPF) Scorecards.
Rather than evaluating revenue in isolation, the Line Profitability engine executes a 4-branch SQL union across your agency's database:
- Branch 1 – Invoiced Sales & Splits: Invoiced revenue, gross earned commission, agency net split (
CommissionAmountAgency), and sub-rep payout split (CommissionAmountSalesRep) with security permission enforcement. - Branch 2 – Time & Activity Hours: Precise labor investment captured from CRM Journal touch points and stopwatch timer logs (
CRMTimerLog) linked to manufacturers, customers, and sales reps. - Branch 3 – Direct Expenses: Out-of-pocket field expenses (travel, lodging, entertainment, meals, samples) from
EXRExpenseandEXRExpenseReportlinked to specific principals or customers. - Branch 4 – Qualitative LPF Scorecard Events: Categorized CRM Journal entries tagged with
LPF+(strengths) orLPF-(operational friction) performance markers.
1. Core Cube Dimensions & Hierarchies
| Cube Axis | Dimension Hierarchy | Dimension Table | Analytical Purpose |
|---|---|---|---|
| Rows | Principal (Manufacturer) | ManufacturerDimensionTable | Evaluate net agency profitability, labor burden, and margin by product line. |
| Rows | Customer | CustomerDimensionTable | Identify high-maintenance vs. high-yield customer accounts across represented lines. |
| Pages (Filter) | Sales Rep | SalesRepDimensionTable | Slice agency profitability and time allocation by assigned territory representative. |
| Columns | Activity Year > Quarter > Month | Calculated Date Hierarchy | Track quarterly profitability trends, seasonal expense spikes, and margin growth. |
2. Summary Metrics & Calculated Performance Indicators
The cube computes granular baseline figures and dynamic calculated summaries in real-time:
💰 Agency Commission Split
Calculates true agency retained revenue after deducting outside sub-rep splits:
⏱️ Labor Cost
Monetizes field sales hours and customer service effort at standard agency hourly cost ($50/hr baseline):
📈 Net Profit
Bottom-line dollar profit retained by the agency after direct expenses and labor allocations:
📊 Net Margin %
Percentage of gross commission retained as agency net profit:
| Summary Measure | Type | Format | Calculation & Strategic Significance |
|---|---|---|---|
| Sales | Currency | $#,##0.00 | Total invoiced sales volume generated for the product line or customer account. |
| Gross Commission | Currency | $#,##0.00 | Total gross commission earned before rep splits. |
| Agency Commission | Currency | $#,##0.00 | Retained agency commission after deducting sub-rep commission splits. |
| Rep Commission | Currency | $#,##0.00 | Commission split payable to territory sales reps (optional/toggleable view). |
| Expenses | Currency | $#,##0.00 | Direct travel, entertainment, and field expenses charged to the line or customer. |
| Hours | Float | #,##0.0 | Cumulative labor hours recorded via stopwatch timers and journal activity logs. |
| Commission / Hr | Calculated Summary | $#,##0.00 | Return on invested time: Gross Commission / Hours. Reveals high-return vs time-sink lines. |
| Net Profit / Hr | Calculated Summary | $#,##0.00 | Net agency yield per invested hour: Net Profit / Hours. |
| Expense / Comm % | Calculated Summary | 0.0% | Expense ratio: (Expenses / Gross Commission) * 100. Flags excessive travel or entertainment spend. |
| Commission Rate % | Calculated Summary | 0.00% | Effective commission yield: (Gross Commission / Sales) * 100. |
| Net LPF Score | Calculated Summary | #,##0 | Qualitative scorecard: LPF+ - LPF-. Aggregates factory ease-of-doing-business feedback. |
3. The Line Performance Factor (LPF) Qualitative Scorecard
Financial numbers tell only part of the story. A product line may appear profitable on paper while causing significant operational friction through late shipments, pricing errors, poor customer service, or delayed commission disbursements. To balance hard financials with operational reality, MRSware incorporates the Line Performance Factor (LPF) framework:
- LPF+ Events (Positive Performance): Tag CRM Journal entries with categories starting with
LPF+(e.g., "LPF+ Fast Quote Turnaround", "LPF+ On-Time Shipments", "LPF+ Quality Marketing Leads"). Each occurrence increments theLPF+counter. - LPF- Events (Negative Friction): Tag CRM Journal entries with categories starting with
LPF-(e.g., "LPF- Shipping Delay", "LPF- Commission Discrepancy", "LPF- Backordered Catalog SKU"). Each occurrence increments theLPF-counter. - Net LPF Score (
LPF+ - LPF-): In the pivot grid, the Net LPF Score provides an objective, empirical rating for annual manufacturer reviews, contract renewals, or principal contract negotiations.
Report Explorer & Saved Views
Generate standard financial statements, Class Master Lists, and Rep Commission Statements. Save custom Data Analysis pivot layouts for one-click re-opening.
📚 Related Documentation & Deep-Dive Articles (7)
View in Documentation Library →Explore additional procedural tutorials and technical documentation references for this chapter:
Data Analysis: Monthly
Technical guide for Data Analysis: Monthly.
Data Analysis: Product Details
Technical guide for Data Analysis: Product Details.
Data Analysis Totals for Company with Branches
Technical guide for Data Analysis Totals for Company with Branches.
How to Save & Re-Open Data Analysis Views
Technical guide for How to Save & Re-Open Data Analysis Views.
Now Showing: Sales Summary Analysis and the magical 5 columns
Technical guide for Now Showing: Sales Summary Analysis and the magical 5 columns.
Retiring Reports
Technical guide for Retiring Reports.
Ship To in Data Analysis
Technical guide for Ship To in Data Analysis.