Master Data Management
Blog: The Data Center
One of the most important topics when it comes to automating your processes is Master Data. Master Data is an often-forgotten key element of process optimization. As your company grows, complexity increases and the need for automation becomes increasingly important. The degree to which data heavy processes can be automated is often dependent on the quality of the master data that feeds those processes.
Part 1 Data Validation & Control
The first step in any Master Data clean up project is to ensure that the new data coming in is clean. Now this can be accomplished in many different ways.
Method 1: Use Decisions to link forms to the Rules Engine.
Our integrated rules engine and form designer makes it possible to do real time validation and control when customers or employees are entering data. With Decisions, you can do things like build forms that have: dependent drop downs; limited data input options; or auto complete forms.
Method 2: Use Decisions to link forms to External Databases
Another popular way to control inbound master data is to validate it against one or many databases. The Decisions platform allows you to do real time service bus calls to external databases to validate your data as it’s being entered. For example, you could easily setup form validations that make real time service bus calls to external databases (such as the USPS) to validate an address.
Method 3: Use Decisions Workflow to automate Data Entry and to manage exceptions.
While the goal is to automate as much as possible, we all know that it’s rarely possible to automate 100% of the use cases in the real world. Our integrated workflow tools can be used to create a master data workflow in your organization to handle these exceptions. You can even setup custom dashboards with Decisions that tell you how long it takes certain departments to complete their work, that notifies you when people are behind on their tasks, and even automatically escalates issues based on your defined rules.
Part 2: Data Cleanup
Decisions platform is designed to fit nicely into data clean up situations, to easily integrate with your existing systems and to make clean up a breeze. As with data validation, there are a number of ways that the Decisions platform can be used to make master data work for your organization.
Method 1: Data Transformation on the Fly
Decisions has interceptor rules that can be setup to intercept that data that is of a certain format and translate it on the fly, so that it conforms to a new standard. This legacy data that has been transformed on the fly can then be used with new formats.
Method 2: Batch Clean up
With Decisions rule engine you can pull data from any number of systems and use any combination of rules that are relevant for your business to identify items that need to be cleaned up and then you can create batch jobs to do the work. For example, we have one client that has data captured about their customers from two different sources. They use Decisions to run batch transactions that identify duplicates based on a set of rules and merge those records. In Decisions they also run a batch job daily that compares new records in both systems to not only merge duplicate, but to also checks for inconsistencies. Any time inconsistent records are identified by the batch job they are flagged “red” and a workflow is kicked off to notify an end-user that these records need to be checked.
Master data management is important and the task of controlling and cleaning it up can be arduous if you don’t have the right tools in place. At Decisions we recognize these challenges and we have lived through them ourselves. To learn more please reach out to us a email@example.com.