Configure, Price, Quote and Propose (CPQ-P):
Over last few years we all understood that the complex
engineering industries and project-based install-bases needs millions of parts
and offerings and services and with every overhaul a simple deal open up
several up-selling opportunities. A stand-alone quoting platform that embeds
AI, ML effectively and other key ingredients improves the win rate in a highly
competitive market.
By aggregating massive amount of Sales, Commercial, Plant
& industrial engineering data that associated with Artificial Intelligence
or Machine Learning or Predictive analytics takes Customer’s preference into
account shall make your CPQ a center of your selling strategies in overall Digital
Thread.
CPQ and the CRM naturally fits into the eco-system and complement
each other quite well. Most of the market leading vendors use standard webservices
driven, scalable managed package to interface with each other. This ensure that
the key data like Accounts, Legal Entity, bid submission date, RFQs and price
& product books are seamlessly transitioned over to CPQ from the legacy CRM
tools. This not just jump starts the commercial quote building process ahead of
the curve but also initiates the collaboration between Sales and Commercial
& Engineering teams or specific to your Org’s function. I have extensively worked in an Engineering
and Energy Industry so my examples will be more relevant to the industries of
similar domain.

CPQ helps in supporting your Org’s strategies to drive the
Commercial growth, reduce margin erosion, improves proposal cycle time in-turn variance
to want (VTW cycle) and increases the revenue.
Listed below are the components of CPQ that shall help your
org in supporting the strategies, KPIs and goals:
·
Efficient Internal Processes
·
Guided Selling
·
Product configuration
·
Pricing Accuracies
·
Standardized Contents
·
Increased Quoting Efficiency
Sales team or even third-party channel partners and
distributors create an opportunity in their CRM system. They are navigated to
CPQ tool where they start exploring the products, models and digitally start
building the quotes per the RFQ needs. Data-enriched configurator digitally tags
the Item masters, parts (SKUs) and prices with pre-defined compatibility rules
and organization’s selling policies. These parts and prices are in-turn
harmonized with back-end ERPs which boosts supports in Order creation at some
stage.
Strategy Supported: Commercial
Growth. By 2022 CPQ market is expected to hit $2.5B.
Guided selling framework helps users with various up-selling
and cross-selling opportunities. By enforcing the compatibility & relationship
rules between the variants and options even a newbie sales person can easily
create a very complex quote with latest parts and price information. Rules integrated
with the guided selling framework helps commercial team in error-proofing the key
contents.
Strategy supported: Increased
Revenue due to cross-selling/Up-selling capabilities.
Configurator is rich in its database. Parts, price and other
commercial master data are the key elements of every CPQ platform. Digitally
set up product family tree in CPQ simplifies the org’s complex engineering product
portfolio structure and hierarchy. Rule-based engine in CPQ which is tied up
with the parts & price master ensures that the options and variants can be
quoted as per the customer needs with much ease.
Strategy Supported: Accuracies
and Consistent quoting.
Data-enriched configurator and the rules are digitally
tagged with the Item masters, Parts and SKU. Each of these parts have the price
details stored in pricing masters which are harmonized with Organizations’ ERP
systems as a single source of truth. With this tight integration prices are
auto-populated based on the configured products/models. Sales and Commercial
teams can even refer to past sales made, previous quotes. This ensures the contribution
margin (CM) is as per the org-level policies and margin proliferation is controlled.
Users can quickly review the Guideline pricing, CM% and take a decision on
discounting which in-turn triggers the deviations and digital workflow
approvals.
Strategy Supported: Reduced
margin erosion and profit leakages.
Standardized Contents:
Sales, commercial Ops, App engineers even Channel partners
are creating the quotes without having to worry about the pricing inaccuracies as
well as other critical information like customer legal entity, Quality standards certificates, Org policies and T&Cs
because of the standard contents and accuracies enabled by using the artificial
intelligence and relevant templates as part of the proposal automation engine.
Built-in integration for proposal automation picks up the critical opportunity,
quote, scope of work data and helps in generating the professional looking,
well-formatted output document. Users can submit the same as part of the Bid. The
other in-built capabilities like version control, saving as favorite gives
right control on such contractual & legal documents
Strategy Supported: Consistent
and Accurate contents. Improved VTW and proposal Cycle time.
Increased Quoting Efficiency:
System is up-scaled
and digitally built-in with the complex engineering algorithms so that
Commercial App Engineers and Channel partners can even configure the
precision-sensitive engineered products in energy industries like valves in
custody transfer, Flares, Flowmeters, Gas & Moisture analyzer by sizing
them right after reviewing customer’s varied plant, site conditions to comply
with regulatory authorities and even help in generating the complex ‘Engineering
to Order’ quotes.
Strategy Supported: Improved
Cycle time, Productivity
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