PM 06 - Prescriptive Delivery Requirements (PPDR) Overview
- Mike Deskis
- Ioana Kocurova
Business Use Case Summary
Cost Recovery Dashboard
This use case fills a the need for a system that provides access to cost-to-serve category tracking metrics. The primary purpose of this functionality is to enable users to gain comprehensive visibility into the performance of various cost-to-serve elements.
When accessing such insights, users can quickly identify areas where cost recovery can be improved, allowing for more efficient targeting of opportunities. The solution aims to support more frequent and data-driven management and improvement of cost-to-serve strategies. Ultimately, this capability is designed to contribute to the overall improvement of the business's contribution margin by enabling more informed and timely decision-making based on accurate cost-to-serve data.
Business Objectives
Cost recovery optimization
Margin improvement
Data-driven decision making
Time Estimation
Estimation Assumptions (based on in scope / out of scope items):
Data is available prior to the start of the build phase and functional data elements – filters, aggregations, etc. have been isolated and verified with the customer.
Relevant measurables – cost-to-serve elements – have been identified and are measurable and have the necessary data available (costs and charges)
Data has the necessary orientations (described in “Input Data”) – i.e. – cost to serve element impacts are broken out by transaction line item
Any thresholds that will be used to “traffic light” various metrics will be hardcoded, not parameterized
The “base case” charts and calculations can be used as is
No integration is considered to be part of this use case
1 sprints/1FTE CE
Stakeholders
The cost-to-serve analysis dashboard serves sales representatives and pricing managers who monitor cost recovery and identify improvement opportunities. Business analysts and finance team members utilize the data for in-depth financial analysis. Product managers, regional managers, and customer segment managers gain insights specific to their domains. Admins ensure data integrity and application functionality, while executives leverage the dashboard for strategic decision-making on cost management and pricing strategies.
Business Context (Use Case Description)
This section outlines the functional requirements for a cost-to-serve metrics dashboard. The point is to collect and display up-to-date predefined metrics with adjustable granularity through various filters. Users can select time periods, customer attributes, product attributes, and currencies for display. The dashboard features four main portlets: Margin Impact, Recovery Heat Map, Recovery Trend, and Recovery Data Table. These portlets provide detailed breakdowns of cost recovery completeness, opportunities, and status across different categories. This allows for aggregation by selected attributes and includes a health indicator for recovery percentages. Additionally, it offers the functionality to download portlet data in various formats such as PNG and PDF.
Ability to get a dashboard where up-to-date predefined cost-to-serve metrics are collected
Ability to switch level of granularity of the reporting using filters
The dashboard has the following filter options:
Ability to select a time period
Ability to filter on some Customer attributes, including Ship-To
Ability to filter on some Product attributes
Ability to select a currency for the values displayed in the portlets
Ability to select an aggregation metric that will show Margin Impact and Recovery Data (in the table portlet) breakdowns by the selected attribute
Features and Capabilities (Overview)
The dashboards below provide Pricing Managers and Product Managers with comprehensive insights into the impact of various factors.
The dashboard has 4 portlets
The portlets are showing the following metrics:
Margin Impact
Occurring recovery completeness and recovery opportunities expressed in margin absolute value
Recovery Trend
Recovery evolution trends over time (month, with potential to change this period type) per cost-to-serve category
Recovery Data Table
Recovery status overview per cost-to-serve category with Total Cost, Total Charge (to customer) and Recovery % for each cost-to-serve metric. A “health indicator” will also show any recovery % metric that falls into certain % thresholds in three traffic light (green, yellow, red) tiers.
Ability to download portlets in various formats (PNG, PDF...)
Prerequisites for PDR Implementation
The following tables can be either manually loaded in Pricefx via Pricefx Excel Client or can be automatically integrated using CSV files in a Pricefx dedicated SFTP folder:
Frequently updated costs (costs-to-serve) data
Customers data
(Customer) Ship-To data
Historical Transactions data enriched with Ship-To details
Historical Transactions data enriched with cost-to-serve elements details
Limitations and Risks
Data formats:
As all the portlets from this dashboard will be using data from the Transactions data set, the input data must be carefully curated as improper data will subsequently offer improper insights.
For more information on data readiness, check out the links below.
LEARN MORE: For more information on Data Readiness Methodology, click here.
LEARN MORE: For more information on Data Identification, click here.
LEARN MORE: For more information on Data Quality, click here.
LEARN MORE: For more information on Data Availability, click here.
Out of Scope
While there may be available features and customization based on customer requirements, the following are out of scope for this use case.
Metrics reporting beyond those mentioned above
Customization
May be done but it is out of scope for this use case and subject to discussion in terms of effort.
Additional filters
Additional filters outside what is OOTB are out-of-scope
User entitlement of the dashboard
Data integration
Any additional data transformations or integrations required to make data available needs to be considered as an additional configuration effort.
Terms and Definitions
Check out a video demonstration for this use case, here.