For years now, we have been hearing about the need for digital transformation from leading consultant firms and specialist alike. Bain, for example, has found that companies wanting to undertake transformation should have four competencies in place: digital strategy, a business model, enablers, and orchestration. Enablers refer to the “current data [and] technology operating model” that will permit a smooth process.
Chances are if you made your way to this page, you are also interested in finding the right pricing solution that you can use to harness the power of digital transformation. Pricefx was recently recognized by Constellation Research as a vendor to keep on a list if you’re on the hunt for pricing optimization solutions. Being recognized for the Constellation ShortList for Price Optimization in Q3 2019 means that we have shown an ability to bring digital transformation to your pricing organization. The following are a list of the requirements for the list and I show how Pricefx is uniquely suited to enable digital transformation in pricing.
Support Multiple Pricing Models
From value-based pricing to cost-plus pricing, promotional pricing models and more, the Pricefx platform can be used to set up and automate multiples aspects of your model for easier and faster implementation. Simply put, pricing logic can be configured to adapt to your specific business requirements. Price calculation logic can also be applied to any strategy, no matter the complexity, using data from various sources, including third-party sources, to perform difficult operations.
Enable Complex Promotion Rules
As your organization grows, so does the complexity of the rules and promotions you need to set to remain profitable. The PromotionManager module can be used to define rules based on a variety of scenarios and variables such as customers, products, and dates. An example would be in the case of bundling in a buy one get the second half off promotion. The promotion rules are sent to your ERP and can be used for quotes or in price lists. Users are also given the option to create specific promotion types with specialized rules and input data. And to make sure that promotions are given to the correct customers, it’s possible to set up approval workflows for promotion contracts.
Manage Price Lists
For anything price list related, we have PriceBuilder. PriceBuilder makes it possible for you to define manual price lists and standard calculated price lists. Live Price Grids are continuously calculated based on various rules. The lists can be structured for specific countries or customer segments. Price lists can also be consumed by an ERP or for quoting purposes. To avoid any unauthorized access or approval, it’s possible to set up line item and price list approval workflows and limit access to a designated group of users. Mass operations and calculation summaries are available for price lists for products within those lists.
Pricing Segmentation
PriceOptimizer is used to define segmentation based on various (configurable) attributes like customers class, product type, volumes and amounts of a product.
Facilitate Markdown Scenarios
Our platform makes it possible to configure dashboards with dynamic filters to analyze transactional data based on dates, products, stores or location, and any other optional data required. The dynamic dashboards can provide calculations and results for specifically configured scenarios.
Deliver Dynamic Pricing
Live Price Grids is a tool within PriceBuilder that calculates prices with variables ranging from weather to transactions from an external data feed. The prices can be calculated periodically or on-demand. This whole process uses calculation logic from input data to adjust prices according to the rules that you define.
Provide Advanced Analytics
PriceAnalyzer is a module that uses existing internal data as well as data from 3rd party systems to produce 13 complex charts that enable a multitude of analyses. The charts themselves can be configured and exported to dashboards with accompanying summaries that can then be used for further analysis of your pricing strategy. But that’s not all, you can filter, drill down, zoom, perform ad hoc calculations and export straight out the box – no further configuration needed.
Create Pricing Optimization Models
PriceOptimizer’s functionality enables optimization and segmentation models which are then used for analysis and further optimization. With built-in languages like R and Python, users can build optimization models of any complexity with ease. We offer out-of-the-box optimization models that can be tweaked to specific business needs. All of the calculations, models, and policies can be adjusted at any time.
Collect Competitive Insights
Pricefx can be connected to any external source with additional data which can then be used for price calculation or guidance. Changes that occur in a price list and sales quote can be used to improve future prices or in sales guidance. In the eventuality that a deal is lost, sales representatives can mark a specific product with a reason for why the deal was lost. This information is then gathered for analysis or displayed on dashboards or in future quotes.
Apply Machine Learning and Artificial Intelligence
PriceOptimizer can continuously run data analysis on transactions, and because it is easy to configure and supports R-code, organizations can improve their segmentation and policies automatically to focus on specific areas of concern.
Integration with CPQ and Order Orchestration Systems
QuoteConfigurator is our CPQ model and can be used to create quotes, configure products, provide deal guidance, create approval workflows, and allows for e-signatures. It is also possible to integrate our modules using PlatformManager where a more technically savvy user can drag & drop external or internal field maps to other systems. Our out-of-the-box integrations include SAP ERP, Oracle JD, Salesforce, MS Dynamics, and SAP C4C. CRM systems data exchange can work on customizable bases directly interacting with the user in the case of opportunity products, for example.
