While creating a “Golden Record” might seem to be the panacea for the data catch-22 situation, it comes with its own set of challenges. This single source of truth is the basis of Master Data Management (MDM)—one data record capturing all the necessary information we need to know about a customer, a vendor, or a prospect, that’s assumed to be 100 percent accurate and its power is undeniable. However, achieving this accuracy is extremely difficult when building data sets from disparate sources. There are multiple data sources, duplicated records, incomplete entries, inconsistency, all made stale by the lack of real-time maintenance. This invariably becomes a thorny issue for any enterprise that relies on vast volumes of information and it is the catalyst for companies spending huge amounts of money trying to manage it. As companies wrestle to break the logjam of inconvenience and associated costs created by the need to clean and master their data while integrating files from third-party data sources, Matchbook AI alleviates the problem with a simple and effective solution. Driven by the passion for helping businesses use their data to its full potential, the company is making the integration and management of mastered data more precise and accessible. This enables clients to not only achieve better results but also significantly increase the ROI on the large investment that they are making on 3rd party data. The ability to distribute the stewardship of data to those user groups most familiar with it facilitates not only better and more relevant data, but more timely data as well.
"Our platform is all about mastering data at the source to deliver clean, verifiable, actionable data that can be accessible across the enterprise"
So, how exactly is Matchbook AI doing it?
By starting right at the data source.
“Our platform is all about mastering data at the source to deliver clean, verifiable, actionable data that is accessible across the enterprise,” says Rushabh Mehta, Founder & CEO of Matchbook AI.
How it all began…
With a rich experience of over 20 years in the data and analytics space, Mehta dedicated much of his career to building BI, data warehousing, and analytics solutions for a variety of companies. This is when he realized that most companies spend the bulk of their time trying to clean and master their data to glean meaningful insights by applying BI and analytics to it. However, in doing so, they are faced with a two-pronged challenge. First, the data is being mastered much later in the game by a set of processes that are dissociated in many ways from the source systems. At the same time, aggregating data from across the enterprise for analytics, the right intent behind the data or of the data owners is unknown or unclear at best.
To put things in perspective, Mehta explains, “If we were to onboard a new prospect or vendor, it would be great if we have clean, accurate information about the prospect right at that point of inception—‘do we have any other business relationships with this prospect across our organization?’, ‘who are my customers?’, ‘who are my vendors and what sort of business relationships do we have with them across the enterprise?’ But, in most cases, BI insights come too late to be of any value.”
We allow businesses to get meaningful information that they can use for insights BI and analytics and truly understand business relationships very early in the cycle as they evolve
He elaborates that as enterprises expand through mergers and acquisitions, so do their business-critical systems. There is a host of new ERP and CRM systems within the organizations that rarely if at all talk to each other. This makes it extremely challenging to gain a 360-degree view of all supplier, prospect, and customer relationships, leading to bad, duplicate data at the source and in operational systems. With the latest AML and OFAC regulations emerging as guardrails to keep businesses compliant, it is more imperative than ever for businesses to know the impact of their business relationships in real-time.
“As I was on this journey, I realized that there was a better way to clean and master data by doing it right at the point of inception across the enterprise. And that’s what Matchbook is all about. We allow businesses to get meaningful information that they can use for analytics and truly understanding their business relationships very early in the cycle,” notes Mehta. In essence, Matchbook serves as the world’s premier source of commercial intelligence for better business insights. The company leverages “trusted data, insights and signals for driving superior outcomes through better data.”
Enriched Data at Your Fingertips
As a plug-and-play SaaS platform, the Matchbook portal can integrate seamlessly with line of business applications as well as CRM, ERP, organizational, and financial business systems. Matchbook manages multiple data streams from disparate sources and scales to meet the most demanding of workloads. In addition, Matchbook has also partnered with eminent commercial data providers, such as Dun & Bradstreet, Experian, and others, to help clients connect their data to referential data sets and accurately “master” data related to accounts, customers, and vendors locally. Companies can even run large files faster with batch processing or match a single record, all through the Matchbook’s easy-to-use UI. Matchbook provides a set of APIs that gives its customers greater flexibility to integrate the Matchbook platform with their own internal systems. Through Matchbook, companies can go beyond essential data points and access a 360-degree view of all their partners, suppliers, and customers. Once they are confident in their match rates, Matchbook delivers enriched data into every record they process. That enrichment can come from input from other related records, or 3rd party referential files. If 3rd party reference files are leveraged, updates can be applied as they happen or on a regular schedule, typically much more frequently that it would be available by traditional integration methods. Moreover, with Matchbook’s comprehensive data stewardship functionality, data is democratized across all business units, supporting multiple data stewards and teams of users, so no one needs to fear giving up control of their data.
Matchbook’s capabilities were on full display during their engagement with Johnson & Johnson. While managing multiple ERP systems across different divisions globally, Johnson & Johnson was tasked with mastering their data to gain a comprehensive understanding of their vendors. However, this was painstakingly time-consuming as managing the data from different units and supply chains around the globe was no easy undertaking. To streamline the job, Matchbook allowed J & J to integrate one ERP system at a time and enabled each ERP business owner to manage their information. They could match the data to commercial data providers like Dun & Bradstreet, bring back the information they needed for their supply chain purposes, take the information out of the platform, and master it across Johnson and Johnson. “As more and more ERPs integrated into our platform, they were able to get a comprehensive 360-degree picture of the vendors across their multiple divisions. Not only that, they were able to gain better insights about the vendors, the risks associated with them, and any relationships that exist between the different vendors as well as the class divisions,” remarks Mehta. “J&J had spent years and untold dollars trying to solve this problem, and our platform enabled them to achieve their goals in a short amount of time at a fraction of the cost.”
Steeped in Innovation
Innovation at Matchbook Services is led by a brilliant team of leaders and industry experts with decades of experience in the data space and complex BI solutions and systems. Mehta says, “We have also developed a very deep understanding of connecting data to commercial data providers.” With customer-centricity at the core, today, Matchbook serves five of the Fortune 50 companies and aims to onboard at least five more by the end of this year. The engineering leaders at Matchbook are in constant communication with customers to stay informed about their needs and collect their feedback before building out a new product to ensure continuous improvement and innovation of the platform.
With several initiatives in the pipeline, the company has recently launched a complete trade compliance portal within its platform so that customers can perform real-time compliance checks on companies and people as needed. Matchbook is in the process of constructing a robust master data platform with integration into Snowflake. Additionally, the company looks to foster more product innovation and expand its partnerships with other commercial data providers. “We are currently in talks with Moody’s Analytics and other key data partners so that we can expand and grow the value proposition from those data partnerships as well,” ends Mehta. “Our vision is to provide the most robust tools for data matching, stewardship and mastering within our platform, requiring only a single set of Matchbook AI integrations to all of a company’s systems. All of the 3rd party referential files will be accessed through our platform without the need for multiple and constant API development. Through our years of experience and learnings in this space, the one challenge we know that will always be present is the constant and rapid change of the enterprise’s data requirements and stakeholder needs. Our proven ability to quickly and easily integrate customers into the Matchbook platform effectively eliminates the time and money barriers that have blocked agility and innovation, and prevented companies from achieving their data accuracy goals and realizing the true value of their data.”