How to Solve the 4 Most Common B2B Integration Risks

The idea of growth does not flourish in isolation. This proves foundational for the world of business. 

In order to grow and deliver the value promised to customers, businesses need to connect, transact, and do business with business partners continuously. They need to communicate with those business partners and exchange information in order to meet their needs and demands. However, all that could actually rack up the costs and make transactions complex and time-consuming, especially when traditional B2B integration solutions are used. 

Conventional B2B integration platforms put all the responsibility of creating data connections with business partners on the shoulders of IT. However, with the number of partners increasing, it takes IT a lot of time to implement those connections; sometimes it takes between six and 12 weeks of calendar time. When IT teams manage the business connections, customers are forced to connect with business workers. Conversely, business workers take time to address the customers’ needs, which delays the value they generate. Consequently, business customers feel frustrated, and these unhappy customers refrain from investing in other products or services offered by the company. This negatively impacts the upselling efforts and ultimately revenue generation. 

Companies can address this problem through automated B2B integration solutions. These solutions empower non-technical business users to implement data connections and facilitate faster data exchange between trading partners - at speed and scale. 

But before we discuss modern B2B integration solutions in detail, let’s dive deeper into B2B integration and its challenges for a better understanding. And then, we’ll find out how self-service-powered solutions can help companies overcome those challenges and drive the business forward. 

How Does B2B Integration Prove Challenging for Business? 

B2B integration platforms empower businesses to digitalize and optimize multiple business processes across trading partner ecosystems to drive B2B transactions. 

The current B2B integration environment is facing multiple challenges especially when conventional data integration solutions are used. Here are a few challenges:

Onboarding is slow and complex: When traditional data integration solutions are leveraged by a company, IT teams need to implement onboarding connections quickly. In the process, IT needs to create custom codes and perform complex EDI mappings. Now, that takes IT teams between six to 12 weeks. As a result, onboarding processes become slower than ever. Customers are forced to wait to receive the value promised to them, which triggers frustration in those customers. Such unhappy customers are less likely to buy more products or services from the company, delaying revenue and value generation. 

Data mapping is not up to the mark: Customer data is growing complex each day. Mapping such complex, multi-dimensional customer data is extremely challenging. The problem worsens when manual methods are used. Incorporating AI and machine learning technologies can enable companies to resolve these problems and transform data mapping outcomes. 

Customers become unhappy and unsatisfied: As IT takes time to build data connections, business partners and customers need to wait to have their needs addressed and met. This makes customers unhappy and unsatisfied. This, in turn, slows the company’s revenue generation process. Also, because IT is responsible for managing data integration and related operations, they fail to focus on more high-value business priorities. 

Using Self-Service Integration to Resolve the Most Common B2B Integration Challenges 

Self-service-powered B2B integration platforms empower non-technical business users to create new data connections and drive business transactions - at speed and scale. 

Business users need to point and click through easy-to-navigate screens to implement data onboarding connections up to 80 percent faster and deliver the value promised to customers much more quickly. 

Users can rely on features, such as pre-built application connectors, dashboards, shared templates, intuitive screens, and AI-data mapping, to integrate customer data with ease and precision. Recent advances in artificial intelligence and machine learning enable business users to map highly complex, bi-directional customer data in an intelligent and accurate way. At the same time, IT is freed to focus on other strategic business projects. 

In short, self-service data integration can empower non-technical business users to overcome those challenges and drive value while freeing IT to drive more high-value tasks.