Picture this: Your sales team just sent out 1,000 quotes with a 10% pricing error. By the time anyone notices, dozens of customers have already accepted them.
Met CPQ automation, what used to be a single manual error can now multiply across thousands of quotes in seconds. While this nightmare scenario keeps CPQ (configure, price, and quote) implementation managers up at night, preventing it is simpler than you might think.
When implemented with proper data integrity practices, CPQ transforms complex processes like Product configuratie, pricing, quoting, and CAD from a weeks-long ordeal into a reliable, error-free operation that takes seconds.
The key to success? A few fundamental data integrity practices that protect your business while maximizing CPQ’s benefits.
Common Data Integrity Challenges
Data integrity (to borrow a definition from IBM) is the “maintenance and assurance of the consistency, accuracy, and reliability of data throughout its lifecycle. It ensures that data remains unaltered and uncompromised from its original state when it was created, transmitted, or stored.”
Data integrity is a massive issue. Without it, you can’t leverage data for automation and decision making. According to Gartner, every year, poor data quality costs organizations an average $12.9 million. And according to Dr. Thomas C. Redman, President of Data Quality Solution, bad data costs the U.S. (very roughly) $3 trillion per year.
During CPQ-implementatie, you’ll face several critical data integrity challenges that need your attention from day one.
First up is the data migration challenge, moving your existing product, pricing, and customer data from legacy systems into the CPQ platform while keeping everything accurate and connected.
Like moving into a new house, you don’t just throw everything into boxes and hope for the best. You need a plan for what goes where (and you need to make sure nothing important gets broken in the process).
Configuration rules present another hurdle. If you’re a manufacturer with thousands of possible product combinations, one tiny error in your configuration rules could allow customers to order physically impossible combinations or products your factory can’t actually build.
QUICK TIP: Before going live, create a “configuration sandbox” where your team can test complex product combinations without affecting real data. It’s like having a flight simulator for your sales team—they can crash all they want without any real-world consequences.
Integration with your external systems adds another layer of complexity to the mix. While a CPQ platform like Epicor CPQ works perfectly fine on its own, you may want to integrate your CPQ system with your ERP, CAD, and CRM platforms to keep everyone speaking the same language and facilitate automation between departments.
Finally, there’s the human element. Even with the most sophisticated automation, your sales team will need to input customer-specific requirements or special conditions. Without proper validation guardrails in place, a single mistyped number or skipped field can send the whole quoting process off the rails.
The Building Blocks of CPQ Data Integrity
CPQ-software consists of multiple interdependent components that must work in harmony to achieve optimal performance. These are outlined below. Once harmony is achieved, you can expect to experience the following improvements which are the average for companies using Epicor CPQ:
- 108% increase in annual sales.
- 105% toename in dealgrootte
- 40% verhoging van de conversieratio
- 38% increase in sales cycle speed
1. Product Catalog
At the heart of your system lies your product catalog, the single source of truth for all configurable items. This catalog must be more than just a list; it needs to be accurate, complete, and structured to grow with your business. Version control and change management are essential here to track every update and modification.
2. Pricing Rules
Pricing rules form the critical foundation for maintaining both accuracy and profitability in your quoting process. They encompass everything from your base costs and list prices to volume discounts, tiered pricing, and market-based competitive pricing data.
Your pricing rules need to handle customer-specific agreements while accounting for regional variations and material cost adjustments. Robust pricing rules also include clear deal approval thresholds to maintain control over margins.
3. Product Rules Logic
Product rules serve as the brain of your operation and enable Epicor CPQ’s Begeleide verkoop functionality. They manage the intricate relationships between your products and features, determining which items work together and what dependencies exist. They guide when to offer optional add-ons, ensure engineering constraints are respected, and enable effective product bundling.
QUICK TIP: Non-technical team members can create pricing and product rules using Epicor CPQ’s intuitive visual interface.
4. Approval Workflows
Your approval workflows establish clear authorization hierarchies for standard quote approvals, manage exception handling processes, and enforce discount approval thresholds. They also oversee special terms protocols, ensuring every non-standard request receives appropriate scrutiny and sign-off, all without the hassle of lengthy email chains.
5. Historical Quote and Customer Data
Historical data is your company’s collective experience transformed into actionable insights. While often overlooked, this component proves crucial for long-term success. It maintains records of past configurations, tracks pricing decisions and their rationale, and stores discount histories. Epicor CPQ uses an intelligent AI model to analyze this data and optimize future win rates.
Three Best Practices: A Phase-by-Phase Approach
Now that we’ve covered the components that make up your CPQ data ecosystem, the question is: “How do we actually make this work in practice?” The answer lies in taking a structured, phase-by-phase approach to data integrity.
Think of data migration like moving into a new house – you need a clear plan for what goes where, and careful handling to ensure nothing gets broken along the way.
Let’s break down each phase and explore exactly what you need to do to ensure your CPQ implementations stand the test of time.
Phase 1: Pre-Implementation
Pre-implementation is your planning phase. Before you start moving data into your new CPQ software, you need to know exactly what you’re working with. That means taking stock of your current data, where it lives, what format it’s in, and any problems you already know about.
This is also the time to set your standards. What does “good data” look like for your organization? What rules need to be in place to maintain quality? Getting this right now will save you countless headaches later.
leidend CPQ-oplossingen like Epicor CPQ automate much of the data validation process, suggesting ways to store data in a logical and efficient manner. This massively accelerates the entire implementation process.
Phase 2: During Implementation
Phase 2 is where planning meets reality. Your main focus should be on watching your data as it moves into the new system. Set up automated checks for your data imports, verify all your pricing calculations, and test your configuration rules with real-world scenarios.
Epicor CPQ lets you create an online “configuration sandbox”. Here, your team can safely test complex product combinations and edge cases without affecting live data.
Phase 3: Post-Implementation
Going live signals the beginning of the post-implementation and maintenance phase. Schedule regular check-ups of your data quality and keep an eye on system logs for anything unusual. If you spot error patterns, speak with your CPQ deployment provider. Have a clear plan for when things go wrong. Know who’s responsible for what, and have documented procedures for fixing issues quickly.
The good news? Most post-implementation challenges are predictable and preventable. Modern CPQ platforms like Epicor CPQ come with built-in safeguards to catch issues early.
The Final Word: Making Your CPQ Investment Count
A CPQ implementation is only as strong as its data foundation. With proper data integrity practices, organizations eliminate costly errors, accelerate quote generation, and build customer trust. Our customers report compelling results: 108% increase in annual sales, 105% larger deal sizes, and 38% faster sales cycles.
By following a structured approach to data management and leveraging Epicor CPQ’s built-in safeguards, you can transform your quoting process from a source of anxiety into a competitive advantage.
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