Workpro
Workpro Partners with Syniti to reveal matches and connections that no conventional matching solution would find.
Background
For over 20 years, Workpro has specialised in solutions for complaints handling, HR case management, Freedom of Information (FOI) requests, and other regulated casework.
The company’s flagship product, Workpro Case Management software, is the trusted case management solution of choice for both the public and private sectors. Many Ombudsman and Commissioners in the UK and worldwide use Workpro, giving them unique insight into case management in even the most regulated environments.
"[Other solutions] didn’t really suit the requirement that we had, which was more about matching some addresses to other addresses; Syniti’s product has that additional flexibility."
Project Background
Workpro is utilized by organizations to manage, track, and complete a wide range of different types of casework. One such organization, a UK government department responsible for ensuring that companies comply with the legislation under their jurisdiction, was looking to take the application a step further. This organization was looking to overlap various data sources with Companies House data, a publicly available, government-produced list of registered companies within the UK.
Having previously utilized an alternative tool, this organization needed a faster, more accurate way of matching the Companies House data against manually inputted case data, integrated into their Workpro case management platform. They also wanted to display cases alongside Companies House data on a map to make it easier to find connections or trace companies operating under slightly different names. “This allows them to find the connections between organisations that they otherwise might not have seen,” says Chris Ellis, Chief Technical Officer at Workpro.
Implementation
Syniti team of data experts was instrumental in implementing the data matching solution in their database environment, a complex setup consisting of a clustered database server. After a brief initial setup, Syniti helped fine-tune the matching algorithm to Workpro’s unique set of data in order to deliver the most optimal results.
The data matching solution was successfully implemented and is now utilized by the Workpro client to match customer case data against Companies House data to create a more complete record and view of the company. Workpro now has a nightly process that looks for new records in the customer data, as well as a process that runs monthly when the Companies House data is refreshed.
Why Syniti was Selected
When looking into matching solutions, Workpro found that many conventional data matching services on the market were in actuality data enrichment services, meant for matching against a purchased set of third-party data. “It didn’t really suit the requirement that we had, which was more about matching some addresses to other addresses,” said Ellis. “And Syniti’s product has that additional flexibility.”
Because Syniti’s matching solution is uniquely suited to handle the complexities of contact data, it’s more accurate when it comes to comparing and scoring record details such as contact name, company name, address, postcode, telephone, email, and custom fields individually.
"When we get an update of the Companies House data, we then need to match all of the unmatched records in the customer data against the three million records in the new data set. With Syniti’s matching solution, that process now happens easily and quickly overnight.”
Results
The matching solution’s contextual scoring matrix automatically identifies matches and patterns that otherwise would have remained undetected or taken weeks of record comparison to locate. Users like Workpro’s client then have a chance to review the data and identify records they may not have realized they were or were not matching to. To drill down even further, this fine-tuned and scored data is then rerun to see what patterns can be identified.
With the ability to view and compare data points such as the size of the organization, the annual turnover, directorships, even a precise location that can be viewed on a map, the user is able to look for – and find – patterns and clusters within the data. According to Ellis, that matched upon data is then used and referred to numerous times throughout the case investigation.
“The scoring is really valuable in that area because it allows the user to see very quickly, ‘Does this look like a good match or not?” he said. “This government department has expressed an interest in bringing data from other government departments into the same system so they can start to build up different layers of information.”