PM07 - Solution Design in Pricefx | Pricefx Knowledge Base

Address Customer Underperformance with Advanced Analytics

For this use case we are looking at a two step implementation approach of the Pricefx solution.

1. Solution Design

The solution considers the usage of the Customer Insights Accelerator package and the PriceFx modules used are Master Data, Analytics and Dashboards.

Design Summary

PriceFx Analytics allows a customer to get visibility into prices and margins. This module supports the definition and execution of the pricing strategy. It also allows for the analysis of actual and simulated pricing methods supporting the modeling of the enterprise performance and profitability. This module also provides for an easy and tight integration with MS-Excel.

The Customer Insights Package (CIP) is an accelerator built to leverage the Analytics capability. It allows you to set up all necessary data structures to be able to start quickly analyzing the sales data with minimum effort and limited requirements for the initial data set.

Core Concepts

The Customer Insights Accelerator is one of the pre-built solutions from PriceFx that provides a customer with a quicker path to the analysis of their pricing data. It allows the management teams to prevent margin leakages through a set of actionable analytics for sales and pricing. This enables the identification of customers at risk and the reasons behind.

The users can choose to analyze the performance of all customers, individual customers or customer groups using this accelerator. Also, product performance per customer can be performed.

The key KPI’s that are provided by the analysis are

Customer and Product health scores
Revenue, Margin and Volume trends
Pricing and Sales opportunities

These KPI’s are visualized through the dashboards made available by this accelerator. The key capabilities of these dashboards are as below:

Global Dashboard
Customer Detail Dashboard
Product Portfolio Dashboard

Global Dashboard

Provides customer performance via health score and revenue, pricing and selling opportunity, and overall customer summary.

Inputs:

Customer(s)
Time filter
Customer Rank – All, Top, Worst
Customer Rank Bucket – 5, 10, 50, 100
KPI – Revenue, Margin %, Volume, Health Score
Customer Class – Configurable and grouped to A,B,C etc
Customer Health Score – Excellent, Normal, Low, Problematic
Customer Base – Core or Long Tailed

The dashboard is comprised of the portlets below:

Global Dashboard Portlets

Customer summary

Customer Performance by health score last 12M

This portlet shows the relative sizes of the customer classification based on the health score in the last 12 months.

Customers Performance by Revenue Last 12M

This portlet shows the relative sizes of the customer classification based on revenue in the last 12 months.

Customer Health Summary

This portlet shows the customer’s health calculated based on the difference between two periods. It shows a co-relation between Health score and revenue, gross margin, volume.

Portlet showing customer health based on differences between selected periods

Trends

Pricing Opportunity

This portlet shows a list of customers who can be targeted to sell more products and more sales volume. The top of the list represents the highest opportunity, these customers are under the average point in the customers set. The bottom of the list represents the lowest opportunity.

Portlet showing potential customers for up-pricing

Selling Opportunity

This portlet shows the total value which can be gained for products that the customer already bought and not bought in the given period.

Portlet showing the total value to be gained for products already bought or not purchased

Inactive Customers

This portlet shows a list of “inactive” customers so that you can identify customers which are marked as active and for which there are no transactions in the chosen time period.

Customer Detail Dashboard

Provides a detailed customer view on revenue and margin, waterfall chart, high/low volume products, and revenue and margin trends.

Inputs:

Customer
Time filter
Category
Product Class
Product Health Score
Product Base

The dashboard is comprised of the portlets below:

Customer Detail Dashboard

Customer Summary

Specialty and Commodity Products

Shows the relative sizes of product classification based on their margin %. The specialty products are those that have a higher than defined margin % and commodity ones have lower.

High and Low Volume Products

Shows relative sizes of product classification based on volume. The chart is based on Data Source Customer Insights Aggregated Data.

Revenue and Margin Charts

Shows Revenue and Margin values over several months in the given period. The chart is based on Data Source Customer Insights Aggregated Data.

Waterfall Chart

Shows a running total profit as values are added or subtracted. This chart is based on Datamart. 

Revenue Breakdown Chart

Shows what the difference in revenue between two periods can be attributed to. It allows you to compare two years or quarters and optionally filter for only certain products and/or customers. The chart is based on Data Source Customer Insights Aggregated Data. 

Number of Transactions in Last 12M and Projection

Bar & line chart shows the number of transactions for the last 12 months and estimation for the next 3 months. The current month is considered as a future month (as it has not ended yet). This chart is based on Datamart.

Customer Revenue and Margin Trend in Last 12M and Projection

Bar & line chart shows Revenue and Margin for the last 12 months and estimation for the next 3 months. The current month is considered as a future month (as it has not ended yet). This chart is based on Datamart.

Customer Products Portfolio Dashboard

Provides pricing opportunities by product type or attribute, identifies the top and bottom products.

Inputs:

Customer
Product Attribute
Time Filter
Product Rank
Product Rank Bucket
Product Class
Product Health Score
Product Base

The dashboard is comprised of the portlets below:

Customer Products Portfolio Dashboard

Customer Summary

Pricing Opportunity by Product Type

Shows relative sizes of product classification based on the margin %.

Pricing opportunity by product attribute

Sums revenue below target by the input value in the product attribute filter. The chart label reflects the input value in the product attribute filter.

Revenue and Margin Contribution

Shows revenue and margin split into ten buckets to visualize the number of products needed to cover each bucket (cumulative contribution).

Pricing opportunity by top products

Shows products (bars) by revenue below target descending and cumulative revenue below target (line). They are grouped by product ID.

Product Health Summary

Shows revenue and margin for top/worst products.

Average Invoice Price

Shows average unit price per product ID and customer classification by revenue.

Trends

Show trend values for top/worst products (ranked by Health Score).

Pricing Opportunity

Shows revenue below target value and % revenue below target. They are grouped by the input value in the product attribute filter.

Selling Opportunity

Shows the total value which can be gained for products that the customer already bought and not bought in the given period. They are grouped by the input value in the product attribute filter.

2. Implementation Approach and Effort Estimation

Implementation Approach

This solution is based on an accelerator, the deployment is simple and can be accomplished by ensuring all data is well defined and available in the partition before the package is installed. Being an extension of the Sales Insights Package its re-uses some of its components.

Configurable aspects of the accelerator are

Customer Segmentation definition – You can define grouping of customers by common characteristics/dimensions. Then selected KPIs of individual customers are calculated according to the values aggregated on the Customer Segment level.
Source of data – Defines from which source (Datamart / Data Source) your transactional data comes from and which fields should be used for calculations.
Parameters, which drive:
Calculations of KPIs – You can set class values and thresholds for various product and customer classifications.
Displaying of certain things – You can change lists of options for filters, and default presets for dashboard filters.
Waterfall chart configuration (it uses the configuration defined for the Sales Insights accelerator installed on the same partition)

The installation follows an intuitive process during which the user is guided to -

Ensure the data is available in the datamart prior to attempting the installation of the package
Set up the datamart mapping by selecting the appropriate fields for
Source Type
Datamart name
CustomerId
Customer Name
ProductId
Product Name
Pricing Date
Invoice Price
Margin
Quantity
UniqueId
Update the company parameters and advanced configuration options
PFXTemplate_CustomerInsights_Configuration

Most of the parameters used in the CI are saved in this table like

Category
Key Name
Value
Is Default
Order
Key Label
Note

The settings here are used for the time filter selection input, top/worst customers selector input, top/worst products selector input, KPI selector input, Display of Trend Columns, Display of Health Score Columns, Revenue and Margin Contribution Chart, Number of next months, Customer Health Score, Customer Revenue Classification, Customer Health Score Classification, Product Quantity Classification, Commodity vs Specialty Product Classification and Inactive Customer Classification

The details of the attributes for each can be found here

PFXTemplate_CustomerInsights_Customer_Segment

This table is used to define the customer segmentation. Customer segments can be obtained from multi data source types such as: Data Source, Customer Master, Customer Extensions. You can define it in this table.

You can add more customer attributes to the table if they are not present yet. Set the value of the Is Active column to YES, if you want to add this attribute into the segmentation processing and exclude the field with isCustomerId = YES. The field set to Is Customer Id = “YES” will not join into the segment data, the system uses it as a key to find data.

CurrencySymbols

This is a Company Parameter of Sales Insights Package, and it should be deployed by this package. Customer Insights re-uses it to show the currency symbol in charts. If your currency is missing, you can add it to this table.

CI_QuoteType_Mapping

This table is used to define the Quote Type on each portlet of the dashboard. When a user selects multiple products and clicks the Create Quote button on a portlet, a new Quote with this Quote Type mapping will be created

Starting with the 1.6 version of this package, it is recommended to have 8 threads per partition where CI is deployed. If the number is lower, the DL calculations may fail.

Ensure the calculation flows are deployed and run. To keep the aggregated data (CI_AggregatedData Data Source) synchronized with customer classification data (CI_CustomerClassification Data Source), a scheduled job needs to be set to run the Data Load CI_CustomerClassification first and then run CI_AggregatedData Data Load (Distributed Calculation).

Note: If this package is deployed to a partition where it was installed before, it is recommended to delete the previously created objects of simulation (Analytics > Simulation: CustomerInsights) and company parameters (Company Parameters > CustomerInsights : All)

Customizations

The accelerators are built to work in different scenarios addressing different customer requirements. However, there are certain instances where the customer requirements might need subtle extensions or major changes.

The extensions/customizations are made through groovy code and the more custom work is done, the less consistency the solution may have with Pricefx and the Accelerators core features and intentions.

Excessive customization can lead to incompatibility issues or performance concerns and every effort should be made by both the implementation team and that customer to find solutions that merge specific user processes with Pricefx best practice for the ideal results.

The level of customization will be driven by customer’ needs and the data. This will define the level of detail these dashboards can visualize and aid in analysis. Also, in most dashboards, the filters can be customized based on the different data sources imported into the partitions.

The solution can be implemented by following the below steps:

Ensure access to the partition and the platform manager.
Ensure all prerequisite data is available in the partition
Follow the steps in the solution design section to deploy the accelerator

Estimate

The implementation is expected to take 1 sprint using 50% of a Configuration Engineer’s time. This estimate represents the full time to implement; not just the installation but also the preparation time, ramping up users to use it, and, overall, making it an effective tool for the customer.

User Stories

This is the collection of user stories that lead up to this use case.

User Stories
Use Story Name	I want to…	so I can …	Acceptance criteria
Epic: Customer Insights – Global view
Datamart Setup	Set up an aggregated data mart	Perform analysis using Pfx PriceAnalyzer.	Product Datamart available. Transactional data mart available. Customer data mart available.
Global view – Customer Summary legend	See the customers performance based on the summary of relevant KPIs (revenue/ margin/volume trends and total values, Health Score calculated by revenue and margin trend, pricing/selling opportunity).	Understand the overall customer performance.	Portlet shows Revenue/margin/volume totals and YTD trends, pricing and selling opportunity, average Health Score. Data affected by these user inputs: Customer(s), Time Filter.
Global view – Customer Health Summary	See the best/worst customers (5,10, 20, 50 or 100) for the selected KPI (revenue, margin %, volume, health score) and their essential KPIs.	Understand the most/least performing customers by KPI and set relevant action steps.	Table shows Health Score and revenue/margin/margin %/volume/number of transactions totals. Data affected by these user inputs: Customer(s), Time Filter, Top/Worst Customers, KPI. Top/Worst filter is applied to the value of the KPI filter.
Global view – Trends table	See the best/worst customers (5,10, 20, 50 or 100) for the selected KPI (Revenue, Margin %, Volume, Health Score) and their essential KPIs.	Analyze the most/least performing Customers by KPI on the YTD/Last 12M basis and set relevant action steps.	Table shows revenue/margin/volume YTD and Last 12M trends. Data affected by these user inputs: Customer(s), Time Filter, Top/Worst Customers, KPI. Top/Worst filter is applied to the value of the KPI filter.
Global view – Customers Performance by Health Score Last 12M	See the customers' performance based on the Health Score, split into four classes (problematic, low, normal, excellent) with the possibility to see the number of customers, total revenue, and average margin % for each group.	Understand the overall proportions of customers portfolio by their health score.	Pie chart shows number of customers per classes by Health Score Last 12M. Number of customers, total revenue, and average margin % information is available for each class. Data affected by these user inputs: Customer(s), Time Filter.
Global view – Customers Performance by Revenue Last 12M	See the customers' performance based on the classification by cumulative revenue contribution, split into four classes (A, B, C, D) with the possibility to see the number of customers, total revenue, total volume, and average margin % for each class.	Understand the overall proportions of customers portfolio by their revenue.	Pie chart shows number of customers per class by Revenue Last 12M. Number of customers, total revenue, total volume, and average margin % information is available for each class. Data affected by these user inputs: Customer(s), Time Filter.
Global view – Pricing Opportunity table	See top (5, 10, 20, 50 or 100) customers with the highest pricing opportunity in terms of revenue/average prices compared to customer segment.	Do a deeper analysis (looking at the other, more detailed dashboard) and make a corrective action.	The table shows customers and their pricing opportunities. Data affected by these user inputs: Customer(s), Time Filter, Top/Worst Customers. Top/Worst filter is applied to the value of Pricing Opportunity.
Global view – Selling Opportunity table	See top (5, 10, 20, 50 or 100) customers with the highest selling opportunity considering buying behavior of the segment.	Do a deeper analysis (looking at the other, more detailed dashboard) and make a corrective action.	The table shows customers and their selling opportunities. Data affected by these user inputs: Customer(s), Time Filter, Top/Worst Customers. Top/Worst filter is applied to the value of Selling Opportunity.
Epic: Customer Insights – Detail view
Customer Detail View – Customer Summary legend	See the Customer performance based on the summary of relevant KPIs (revenue/ margin/volume trends and total values, Health Score (calculated by revenue and margin trend), pricing/selling opportunity).	Understand the total performance of Customer.	Portlet shows revenue/margin/volume YTD totals and YTD/Last 12 months trends, health score Last 12 months. Data affected by these user inputs: Customer(s), Time Filter, Category.
Customer Detail View – Waterfall chart	See a standardized Price waterfall chart.	Understand the product portfolio profitability for the customer and take corrective action.	The chart shows the waterfall analysis with grouped adjustments. Data affected by these user inputs: Customer(s), Time Filter, Category.
Customer Detail View – Revenue Breakdown chart	Analyze revenue causality for the relevant period with a breakdown into several categories (Lost Business, New Business, Price Effect, Volume Effect, other effects)	Understand revenue drives and adjust strategy to improve performance in each bucket.	Revenue Breakdown waterfall chart Show total revenue Show breakdown of revenue by grouping the data into: "Lost Business" vs "New Business" *Change to revenue due to "Price Effect" Change to revenue due to "Volume Effect" Change to revenue due to "Portfolio Mix Effect" Change to revenue due to "Other Effect" Data listed per/aggregated by these user inputs: Customer(s), Time Filter, Category.
Customer Detail View – Specialty and Commodity Products chart	See the products categorization by their type with the possibility to see the number of products, total revenue, and average margin % for each type.	Understand the overall proportions of products by their product type.	Pie chart shows number of products per product type. Total revenue, and average margin % information is available for each product type. Data affected by these user inputs: Customer(s), Time Filter, Category.
Customer Detail View – High Volume and Low Volume Products chart	See the products performance based on the classification by cumulative volume contribution, split into four classes (low, normal, high, extremely high) with the possibility to see the number of products, total revenue, and average margin % for each class.	Understand the overall proportions of products by their volume.	Pie chart shows number of products per volume class. Total revenue, and average margin % information is available for each product volume class. Data affected by these user inputs: Customer(s), Time Filter, Category.
Customer Detail View – Nr of Transactions in Last 12M & Projection chart	See the number of transactions realized in particular months of a given period.	Understand the number of transactions progression for the particular customer and decide on corrective actions.	Bar and line chart shows number of transactions in period (last 12 months). X-axis: time series on a monthly level Y-axis: number of transactions (bars), projection (bars) and regression (line) Data affected by these user inputs: Customer(s), Time Filter.
Customer Detail View – Customer Revenue and Margin Trend in Last 12M & Projection chart	See revenue and margin trends during a given period and projection of these for the following three months.	Understand the revenue and margin trends for the customer and decide on corrective actions.	Bar and line chart shows revenue and margin regression and projection in period (last 12 months). X-axis: time series on a monthly level Y-axis: Revenue total (bars), regression (line) and projection (bars) Z-axis: Margin total (line), regression (line) and projection (line) Data affected by these user inputs: Customer(s), Time Filter.
Customer Detail View – Revenue and Margin chart	See revenue and margin achieved months of a given period.	Understand the revenue and margin progression for the customer and decide on corrective actions.	Bar and line chart shows revenue and margin total values in each period (as per the user input). X-axis: time series on a monthly level Y-axis: Revenue total (bars) Z-axis: Margin total (line) Data affected by these user inputs: Customer(s), Time Filter, Category.
Epic: Customer Insights – Customer Products Portfolio
Customer Products Portfolio – Customer Summary legend	See the Products performance based on the summary of relevant KPIs (revenue/ margin/volume trends and total values, Health Score (calculated by revenue and margin trend), pricing/selling opportunity).	Understand the total performance of a particular customer.	Portlet shows Revenue/margin/volume totals and YTD trends, pricing and selling opportunity, average health score. Data affected by these user inputs: Customer(s), Time Filter, Product Attribute.
Customer Products Portfolio – Product Health Summary table	See the best/worst Products (5,10, 20, 50 or 00) for the Health Score value.	Understand the most/least performing Products by KPI and set relevant action steps.	Table shows Health Score and revenue/margin/volume/margin % totals per product. Data affected by these user inputs: Customer, Time Filter, Product Attribute, Top/Worst Products. Top/Worst Products filter is applied to the value of the Health Score.
Customer Products Portfolio – Trends table	See the best/worst Products (5,10, 20, 50 or 100) for the selected KPI (Revenue, Margin %, Volume, Health Score) and their essential KPIs.	Analyze the most/least performing Products by KPI on the YTD/Last 12M basis and set relevant action steps.	Table shows revenue/margin/volume YTD and Last 12M trends per product. Data affected by these user inputs: Customer, Time Filter, Product Attribute, Top/Worst Products. Top/Worst Products filter is applied to the value of (TBD).
Customer Products Portfolio – Revenue and Margin Contribution	Analyze contribution of products to the total revenue and margin split into 10 buckets (from 10% to 100%), with the option to drill down to see the top 10 contributing products in each bucket.	Understand the lowest performing products and decide on corrective actions if needed.	Bart chart shows Revenue and Margin split into ten buckets to visualize the number of products needed to cover each bucket (cumulative contribution). Each data point displays the number of products in the bucket, the total revenue/margin of the product in the bucket and the revenue/margin representing the bucket. Data affected by these user inputs: Customer, Time Filter, Product Attribute.
Customer Products Portfolio – Pricing Opportunity by Top Products chart	See products (first 5,10, 20, 50 or 100) with the highest pricing opportunity (considering the standards for correlative segment) and its cumulative value.	Do a deeper analysis, determine the least performing products considering the average prices for the segment.	The bar and line chart shows the revenue below target for the number of products (5,10,20,50 or 100) with the highest value. X-axis: revenue below target total (bars) Y-axis: cumulative revenue below target % (line) Data affected by these user inputs: Customer, Time Filter, Product Attribute, Top/Worst Products. Top/Worst Products filter is applied to the value of Pricing Opportunity.
Customer Products Portfolio – Pricing Opportunity by Product Type	See the pricing opportunity (considering the standards for correlative segment) by product types (commodity, specialty).	Understand the overall proportions of product types by pricing opportunity.	The bar and line chart shows the revenue below target by product type. X-axis: revenue below target total (bars) Y-axis: cumulative revenue below target % (line) Data affected by these user inputs: Customer, Time Filter, Product Attribute.
Customer Products Portfolio – Pricing Opportunity by Product Attribute chart	See the pricing opportunity (considering the standards for correlative segment) by defined product categories.	Understand the overall proportions of product categories by pricing opportunity.	The bar and line chart shows the revenue below target by a given product attribute. X-axis: revenue below target total (bars) Y-axis: cumulative revenue below target % (line) Data affected by these user inputs: Customer, Time Filter, Product Attribute.
Customer Products Portfolio – Pricing Opportunity table	See products by their pricing opportunity considering the standards for segment.	Do a deeper analysis, determine the least performing product categories, and make a corrective action.	Table shows pricing opportunity by products. Data affected by these user inputs: Customer, Time Filter, Product Attribute.
Customer Products Portfolio – Selling Opportunity table	See products by their selling opportunity considering buying behavior of the segment.	Do a deeper analysis, determine the least performing product categories, and make a corrective action.	Table shows selling opportunity by products. Data affected by these user inputs: Customer, Time Filter, Product Attribute.
Customer Products Portfolio – Average Invoice Price table	See the average invoice unit price per product, customer revenue class (A, B, C, D), overall average value per all customers and average value for the specific customer.	Understand the balance of prices across all products and customers and set relevant action steps.	The table shows average prices per customer revenue class, overall value, and average value for the specific customer. Data affected by these user inputs: Customer, Time Filter, Product Attribute