CLORASBigCommerceDistribution One

BigCommerce Distribution One Integration: Overcoming Challenges

By October 10, 2020 No Comments

Learning Is A Never-Ending Process

This blog briefly describes the problems faced and how they were solved in Integrating Distribution One (ERP) with BigCommerce (eCommerce) using our middleware Cloras.

When it comes to integration, there will be minimum clarity at the beginning stages while we onboard the customer. Both the customer and our team would not be completely aware of the limitations of the platforms which we are going to be integrating. Along the course of the project, based on the analysis of our customer’s pain points and requirements, we will come to know the real barricades which might pop up. Our team has worked on a handful of Distribution One projects and numerous BigCommerce projects in the past.

Despite being familiar with working on these two platforms, challenges were inevitable along the course of this project. As we all know, whenever there is a challenge, there is always learning out of it. This project enabled our team to dive deep into the challenges and extract the untapped potential of ourselves and our product.

High Volume – Low Buffer Time Conundrum

Customers do not just expect the system to be faster but also to process large volumes faster.

In this project, we integrated the orders and the product inventory between BigCommerce and Distribution One ERP solution. Our customer had a large number of orders falling into their ERP daily via multiple sources.

Due to some of the limitations of the ERP platform Distribution One, we were enveloped with more and more challenges to achieve quick synchronization of information through Cloras. Given the huge volumes of orders and inventory data, our customer’s buffer time expectation for the successful synchronization sounded seemingly far-fetched.

Overcoming Challenges And Reaping Success

In Cloras, we usually build one pipe per integration services such as customers, products, inventory, online and offline orders, orders processing, and dynamic pricing. Each pipe performs each of these services.

In this project, the customer’s Distribution One ERP failed to support fetching inventory data by any given time. We were only able to fetch data by the last modified date. At the same time, the customer had been getting an enormous amount of orders of about 40000+ SKUs on a daily basis which included multiple packs of products. The inventory stock levels kept drastically altering in a span of a few minutes.

On the other hand, the bulk synchronization of inventory was consuming a few hours to get synced completely. Initially, one pipe was built to sync bulk inventory. There was a delay in syncing the inventory of some of the fast-selling products and because of which the BigCommerce website ended up over-selling some of the products.

Neither the customer was at peace with the delay in the synchronization of data nor the Distribution One ERP supported us with fetching data by time.

When our customer faced the issues:

Customer Challenges - Cloras

Inventory Sync Query

Then, our team embarked on a new venture of handling multiple pipes for fetching different levels of inventory. We created a new pipe and altered the flows in Cloras in such a way that it could quickly fetch the products whose inventory was less than ten.

Meanwhile, the bulk inventory synchronization would still be running in another pipe. With the help of this new pipe, Cloras was able to sync those fast selling products into BigCommerce so that the website would show the correct stock count of such products.

Our customer welcomed this as we addressed their pain point of products getting over-sold and provided an optimum solution.

In later stages, our customer found that there are a few products whose inventory stock level dropped at lightning speeds – within a minute or two. Such cases were also comprising the products having around 250+ of inventory stock.

Then our developers created three different pipes and segregated the inventory services in a robust as well as a productive way where each pipe covers each range of inventory levels simultaneously such as (0 – 10), (11 – 250), (Above 250).

Once the Cloras team provided the solution:

Response from Cloras

BigCommerce Distribution One Integration Support

Special Characters Issue

Our team also addressed one another pain point which was referred to as the “Special Characters issue”. Whenever a customer placed an order, and if that customer’s name or the address contained a unique character such as (-, ~, &, *, ^, etc.) the order failed to sync into the Distribution One ERP.

Cloras has inbuilt modifier functions which indeed came in handy to handle this issue and provide a quick solution.

Customer Delight

Customer’s Feedback Post-Live:

Cloras Customer Feedback

The customer was delighted by our robust product and its service offerings and appreciated our spontaneous support throughout the development phase as well as the post-Go-Live maintenance phase.

Usually, post-live it takes almost a month to settle down. Still, with constant monitoring and support services provided by our developers, we were able to achieve stability within a short time.

Needless to say, there is nothing that can match the contentment and pleasure of reaping the benefits out of our hard work. It was indeed an incredible experience for the Cloras Team.

Girinath A

Girinath A

Girinath is currently working as a Business Analyst with Cloras. He began his career with Amazon and has around six years of work experience in Business Analysis.