The global market in supply chain analytics is estimated at some $2.7 billion[1] — and yet, far too often supply chain leaders use spreadsheets to manage their operation, limiting the real-time visibility into their systems.
Longbow Advantage, a supply chain partner, helps companies get the maximum ROI from their supply chain software products. Moving beyond the spreadsheet and generic enterprise BI tools, Longbow developed an application called Rebus™ which allows users to harness the power of smart data and get real-time visibility into their entire supply chain. That means ingesting data in many formats from a wide range of systems, storing it for efficient reference, and presenting it as needed to users — at scale.
MongoDB Atlas is at the heart of Rebus. We talked to Alex Wakefield, Chief Commercial Officer, to find out why they chose to trust such a critical part of their business to MongoDB and how it’s panned out both technically and commercially.
Tell us a little bit about Longbow Advantage. How did you come up with the idea?
Sixteen years ago our Founder, Gerry Brady, left his job at a distribution company to build Longbow Advantage. The goal was to build a company that could help streamline warehouse and workforce management implementations, upgrades, and integrations, and put more focus on customer experience and success.
Companies of all sizes have greatly improved distribution processes but still lack real-time visibility into their systems. While there’s a desire to use BI/analytics systems, automate manual processes, and work with information in as close to real-time as possible, most companies continue to rely on manually generated spreadsheets to measure their logistics KPIs, slowing down speed to insights.
There had to be a better way to help companies address this problem. We built an application called Rebus. This SaaS-based analytics platform, used by industry leaders such as Del Monte Foods and Subaru of America, aggregates and harmonizes logistics data from any supply chain execution software to provide a near real-time view of logistics operations and deliver cross-functional insights. The idea is quite simply to provide more accurate data in as close to real-time as technically possible within a common platform that can be shared across the supply chain.
For example, one company may have a KPI around labor productivity. When that company receives a customer order to ship, there is a lot of information they want to know:
- Was the order shipped and on-time?
- How efficiently is the labor staff filling orders?
- How many orders are processing?
- How many individual lines or tasks on the order are being filled?
The list goes on. With Rebus, manufacturers, retailers and distributors can segment different business lines like e-commerce, traditional retail, direct to consumer and more, to ensure that they are being productive and meeting the appropriate deadlines. Without this information, a company may miss major deadlines, negatively impact customer satisfaction, miss out on revenue opportunities, and in some cases, incur significant financial penalties.
What are some of the benefits that your customers are experiencing?
Our customers are able to automate a manual and time-intensive metrics process and collect near real-time data in a common platform that can be used across the organization. All of this leads to more efficient decision-making and a coordinated communication effort.
Customers are also able to identify inaccurate or duplicate data that may be contributing to slow performance in their Warehouse and Labor Management software. Rebus provides an immediate way to identify data issues and improve overall performance. This is a huge benefit for customers who are shipping thousands of orders every week.
Why did you decide to use MongoDB?
Four years ago, when we first came up with the idea for Rebus, we gathered a group of employees to brainstorm the best way to build it.
In that brainstorm, one of our employees suggested that we use MongoDB as the underlying datastore. After doing some research, it was clear that the document model was a good match for Rebus. It would allow us to gather, store, and build analytics around a lot of disparate data in close to real time. We decided to build our application on MongoDB Enterprise Advanced.
When and why did you decide to move to MongoDB Atlas?
We first heard about MongoDB Atlas in July 2016 shortly after it launched, but were not able to migrate right away. We maintain strict requirements around compliance and data management, so it was not until May 2017, when MongoDB Atlas became SOC2 compliant, that we decided to migrate. Handing off our database management to the team that builds MongoDB gave us peace of mind and has helped us stay efficient and agile. We wanted to ensure that our team could remain focused on the application and not have to worry about the underlying infrastructure. Atlas allowed us to do just that.
The migration wasn’t hard. We were moving half a terabyte of data into Atlas, which took a couple of goes — the first time didn’t take. But the support team was proactive. After working with us to pinpoint the issue, one of our key technical people reconfigured an option and the process re-ran without any issues. We hit our deadline.
Why did you decide to use Atlas on Google Cloud Platform (GCP)?
Google Cloud Platform is SOC2 compliant and allows us to keep our team highly efficient and focused on developing the application instead of managing the back end. Additionally, GCP gave us great responses that we weren’t getting from other cloud vendors.
How has your experience been so far?
MongoDB Atlas has been fantastic for us. In particular, the real-time performance panel is fantastic, allowing us to see what is going on in our cluster as it’s happening.
In comparison to other databases, both NoSQL and SQL, MongoDB provides huge benefits. Despite the fact that many of our developers have worked with relational databases their entire careers, the way we can get data out of MongoDB is unparalleled to anything they’ve ever seen. That’s even with a smaller, more efficient footprint on our system.
Additionally, the speed of MongoDB has been really helpful. We’re still looking at the results from our load tests, but the ratio of timeouts to successes was very low. Atlas outperforms what we were doing before. We know we can support at least a couple hundred users at one time. That tells us we will be able to go and grow with MongoDB Atlas for years to come.
Thank you for your time Alex.
