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CPQ Transformation for
US Technology Giant
Success Story
Our partners had just started a CPQ transformation process and quickly realized they could do with a helping hand from an experienced vendor. Multiple legacy systems, underperforming CPQ applications, and a lack of .NET and DevOps resources meant they were facing an uphill battle and quickly approaching deadlines and were in dire need of a well-oiled team of professionals to take charge of the project.
Scalefocus successfully collaborated with their overseas teams and, despite the substantial geographical distance and time difference, managed to avoid any communication breakdowns whatsoever. Our teams did all the scoping and development per our partners’ requirements and passed the demanding test with flying colors while delivering world-class new features at astonishing speed.

Streamlined and error-proof processes

Multiple new
CPQ features

Accelerated database query response time
The Client
An American multinational information technology giant and provider of comprehensive software and hardware solutions. On the 2018 Fortune 500 list, it is ranked within the top 60 largest United States corporations by total revenue. A worldwide leader in technology and corporate culture for over 80 years, the brand is synonymous with innovation and impeccable quality.
The Solution
We had the daunting task of improving the current quality and agility of the feature development as part of the company’s 4-year program for CPQ transformation using SAFe methodology. Our partner lacked the resources to oversee such a large-scale transformation project with very tight deadlines and desperately needed to leverage the expertise of a reliable vendor.
Before the CPQ transformation program, they depended on multiple systems and manual workarounds, which complicated all processes. The main goal was to provide an integrated system that automates configure, price and quote activities, resulting in a better experience for all stakeholders. Significant delays meant they had to hire an up-and-running team to speed the feature delivery and reduce the defects leakage for their CPQ application, which is the go-to system for special pricing.
Scalefocus provided a team of experienced specialists (.NET, DevOp, UI, API and Scrum master) who managed to deliver 9 new CPQ features within just 6 months as part of the Digital Pricing train, with 12 more projected for delivery by the end of Q1 Y2023. Our software engineers’ expertise helped them to leverage the existing technology they had in place to work with – .NET backend network, Google RPC framework, AWS cloud services, etc.
We collaborated in a SAFe environment with over 9 teams organized in the Agile train. Our team was responsible for scoping, analysis of requirements, and both front and backend development. Scalefocus’ effortless collaboration in an international environment effectively served as a bridge between teams in India and USA, resolving numerous issues while developing new functionalities at breakneck speed.
Architecture
The CPQ application had .NET 6.0 version as the backend framework. Therefore, our first task was to create a new service for the Business justification form application using that .NET 6.0 framework. The app backend services also use a common internal layer for the .NET framework that we also had to integrate.
Since the app services overall have Clean architecture as service implementation, team Scalefocus followed the same principle to implement the new backend service. A major advantage of Clean architecture is that it allows for loose coupling between different components of the system, which can improve its flexibility and adaptability.
gRPC and GraphQL
The CPQ backend services communicate via gRPC (Google Remote Procedure Call). It is a high-performance RPC framework that uses binary encoding and HTTP/2 to provide efficient communication between services. So instead of, let’s say, HTTP, we implemented gRPC for our own services and interaction with other CPQ services.
UI only uses GraphQL to communicate with the backend, so we had to implement a GraphQL endpoint in a common GraphQL for each service. This enables clients to specify the exact data they need and its shape in a single request, which can improve the performance and efficiency of the API. Hence, we implemented the necessary Data Loaders, Queries, and Mutations on the GraphQL layer. gRPC is also responsible for the communication between GraphQL and Service.
Data Model and Database Layer
Since our team started developing the Business justification form application from scratch, our first challenge was to define the data model. Defining the data model meant our design could support the CPQ app users’ business requirements and needs. As a result of our data-model design, we could optimize data storage and component access.
Another challenge was to implement the Database Access Layer in the backend using the Entity Framework Core Code-First approach. For the Querying database, we also used the Dapper ORM framework. Basically, we designed our Db Access layer using both Entity Framework Core and Dapper to work with the app database, which is ORACLE.
Entity Framework code-first helped us to define the data model and interact freely with the database. We used Dapper for our read queries since it is swift and lightweight, making it ideal for applications requiring a high volume of database operations. That reduced our database query response time to under 10ms.
Authentication
Authenticating users was also quite a challenge. The application used by our partners’ employees meant we needed to integrate a single sign-on (SSO) service. We did user authentication through SSO and business justification service using JWT tokens generated by the same SSO service.
External Integration
The backend service was integrated with the TERA system external tool to get large amounts of critical business data. We used HTTP protocol for the integration. After that system got the large amounts of data, it cached it to Redis Cache so that when it needs the same data, it does not need to make the same call. It is an excellent performant solution from a backend perspective.
Cloud
Our partners had selected AWS as their cloud vendor, so we needed to use AWS services as the main PAAS, IAAS, and SAAS solutions in our system design.
The application was deployed to an EKS service that ran the shared Kubernetes cluster of Pricehub. Logging was done in the AWS CloudWatch service and we had full observability in our logs. And finally, we used AWS S3 service for object storage.
Тhe Benefits
Team Scalefocus managed to design, deliver, and successfully launch in production:
- Workflow for exchanging questions and answers between Bid desk and Sales users for a respective business justification of a new deal and keeping all history in the CPQ app
- Administration module for business justification form templates in the customer’s legacy app
- New report for account history. If bid desk users want to negotiate and approve prices for the deal, they can view quoted revenues and margins as well as actuals for all of the company’s past deals with the account of the current deal to be approved and make an informed pricing decision.
- Advanced analytics data visualization for products empowers bid desk users to negotiate better guidance with sales.
New Insights features are in progress for implementation so that we can enhance the analytics and display more reports for better deal pricing decisions and improvements of the already designed features.
The Results
- Accelerated and streamlined processes due to CPQ automation
- 9 new CPQ features with 12 more projected for Q1 of 2023
- <10ms database query response time
- Reduced defect leakage of the CPQ application
Our Work
We have a global client base that includes Fortune 500 companies, innovative startups and industry leaders in Information Technology, E-Commerce, Insurance, Healthcare, Finance and Energy & Utilities.