This article offers a guide for tracking Microsoft Dynamics CRM usage at the record level.
Originally published in H2 2018 D365UG/CRMUG Magazine
For many organizations, their Microsoft Dynamics 365 instance represents a major investment of time and resources as they try to make it the centerpiece of their Customer interactions. They want to get a good return on their investment, so they look to ensure that Users are entering data and using the system to help with daily tasks. With the goal of getting better Customer insights and increasing revenue, the organization is looking to optimize the usage of its Microsoft Dynamics CRM system. There are many ways to measure how much data you are collecting and if the Users are using the system. One way to get an overall view of a system is to use the Attribute Usage Inspector plugin for XrmToolBox.
This plugin will let you know the overall usage for fields on an entity but won’t tell you anything about a specific record.
We recently had a client that had a requirement to figure out the percentage of fields in an entity that had data. Their sales are largely based on relationships between people and organizations, so they need to have as much data as possible to be able to find any relationships between contacts and accounts. They wanted to see if they were capturing more data as records moved through the sales cycle as this would indicate that employees were entering data into and using the system. They were especially interested in opportunities that were about to close as they should have complete information about all the parties in the opportunity.
The first thing that we had to do was determine what data is significant to their business. Since they don’t send bulk emails or mass mailings, those fields wouldn’t be expected to be filled in. After a review of the standard and custom fields on the entities, we knew what to look for.
The next thing we needed to determine was how often to calculate the percentage of data filled in for the record. The two options were to run a process that would use the last modified date for the record to select the records that needed to be updated or to use a plugin to calculate the information as data in the record changes. We briefly investigated Azure Functions with a timer, but the client wanted the data updated as soon as possible, so we created a plugin that runs asynchronously after a record is created or updated.
For each entity that we wanted to calculate the percentage of data filled in, we modified the entity to have a field to store the result of the calculation. We then registered the plugin to create and update messages on that entity. We used the plugin configuration to pass in a string with information about each entity like the list of fields to use in the calculation and the name of the field to store the result in.
The plugin would retrieve the full set of fields for the entity and then perform the simple calculation to get the percentage, and then, if the value had changed, to update the entity.
The final step for us was to create a view that could be assigned to some of the managers that included the information that they wanted to determine if a User was entering data consistently. This included identifying information about the entity, the User that is the owner of the record, and our calculated field. With this information, the manager can gain a greater understanding of who is using the system and to what extent they are entering data.
This view with test data shows how the information about the percentage of data filled in on the record can be used to find both those records that have been filled out and those that should have more data.
