In our Boomi implementation practice at Kitepipe, we see many organizations struggling with the same problems around data quality. Of course, data quality issues can vary somewhat depending on the domain — whether customer, employee, or product. But the customer domain offers an excellent example to illustrate this point.
I’ve already written about mastering Salesforce platform data, but the challenges aren’t limited to a single platform. Nearly everyone faces challenges when managing customer data across multiple platforms.
One common challenge involves business analytics.
Various operational platforms capture different aspects of the overall business and, therefore, different types of information about customers. When you’re trying to aggregate that information in a data warehouse for business intelligence (BI) purposes, customer information from those platforms is often out of sync because they have different views of the customer. You may have several conflicting data points for the same company; transaction, revenue, fulfillment, and service data are telling different stories.
Also, parent-child hierarchy issues can emerge because one group is tracking the customer at an enterprise level while another is engaged at an operational or location level.
And if the data can’t be synchronized, then running meaningful analytics becomes virtually impossible.
Which Application Platform Should be the Master?
Not surprisingly, when humans are involved, data quality problems aren’t just about data quality. They’re also related to an organization’s culture.
For example, some organizations are very sales-oriented; for them, the source of customer data is the sales platform. Other organizations are finance-oriented, and for them, the source is likely to be the ERP application or the finance and accounting system. That’s why, when we talk to customers about Boomi DataHub, one of the first questions we ask is, “What’s the authoritative source for customer data in your organization?”
This question may seem straightforward, but it’s not. So we also ask a follow-up: “What is the event for your organization that changes a prospect into a customer?”
Depending on who we ask, we almost always get different answers. Sales leaders might say a prospect becomes a customer when a deal goes to Closed/Won in Salesforce Sales Cloud. But the finance team may say it occurs when the first sales order is submitted, or perhaps when the first invoice is generated.
It doesn’t matter which event is the trigger, but it does matter that everyone agrees. In this example, you can’t synchronize customer data without a shared understanding of when a prospect becomes a customer.
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The Business Impact of Data Quality Issues
When customer data is not kept in sync, that can delay revenue recognition and fulfillment. Likewise, out-of-sync employee data can turn the onboarding process into a frustrating, time-consuming ordeal for both employees and HR professionals alike. Moreover, the time spent solving data quality problems is time not spent making the business run more efficiently and profitably.
Take revenue recognition. There’s a point in the sales cycle where a deal passes from a CRM application to the ERP system. Often, it’s from Salesforce Sales Cloud to NetSuite ERP. At this juncture, data quality is critical, especially because many companies close up to 80 percent of their business at the end of a quarter, when time and data accuracy are critically important. The finance team is under intense pressure to get deals squared away and booked against the correct customer entity. Poor data quality can turn this process into a nightmare for everyone from the CFO on down.
Enter Boomi DataHub
Historically, data mastering projects were large, expensive, exhausting, and seemingly endless, mainly because they couldn’t keep up with changing business requirements.
In the legacy master data management (MDM) model, you’re capturing large volumes of data in a repository, then managing that data with complex data models. All data must originate in the repository and also terminate there, and this can present massive integration challenges.
Boomi DataHub is best thought of as a data synchronization engine. You’re not keeping a lot of data in Hub. You’re storing indexes to the data, which lets you know whether Customer A in the revenue system is the same as Customer A in the CRM platform, and whether both are the same as Customer A in the third-party logistics (3PL) system. Some of the most important data in a Hub golden record is the ID of the entity in each source or destination system. There is some art to what data to store in the golden record, and what to keep in the system of record. The implementation team at Kitepipe can help design your Hub.
Implementing DataHub is much faster and less costly than implementing a legacy MDM solution. In part, that’s because the emphasis is on identity management and synchronizing data across operational platforms, rather than on managing a master of the actual data.
Kitepipe and Boomi helped a rapidly growing biotech organization automate business processes, scale on demand, and alleviate administrative burdens for scientists. Read the case study.
Boomi DataHub: Customer Concerns and Misconceptions
Boomi is often sold by technical people to technical people. The Boomi owner is usually not someone on the business or operational side, such as the CFO, CIO, or controller. More likely, the owner is the IT director or VP of applications.
While people in these technical roles understand technology, they may have only a limited understanding of how to support the business. However, one of their first tasks is selling Boomi up the food chain to senior business or operational executives. So it’s our job to help them build the business case they’ll need to make the internal sale.
Often, the technical side of the house needs some convincing as well. For instance, because Boomi is cloud-based, we sometimes get questions about controlling and securing critical master data. As mentioned earlier, Boomi DataHub is not storing and managing all data of interest in the organization. Operational systems remain the systems of record. Hub’s role is to synchronize master data across those operational systems. There’s a skill to the design of a lean, high-function Hub. The actual data can live either in the cloud or on premises, in operational databases. In fact, at many companies, the data resides in both places.
Master data is not high volume compared with other data in the organization. You could have hundreds of thousands of transactions a month, even though you might have only a few thousand customers. Also, master data is not highly dynamic. The add/change volume is relatively low. As a result, maintaining that data in the cloud is not a constraint.
Because Boomi DataHub resides in the cloud, maintenance, provisioning, and scaling are all on Boomi, so customers don’t have to worry about that. Plus, the Boomi cloud is highly secure and reliable. It’s compliant with both SOC and HIPAA, and it features “five-nines” reliability. Data is encrypted, both in motion and at rest.
Data Synchronization for a Fragmented Application Landscape
There are no longer just one or two systems that have customer data in them — or any other data, for that matter. Today, most companies use dozens of applications. For instance, ten of them may need employee information, and another ten or twelve may need customer information, with each of those applications managing its own specific data set. Ditto for product management and fulfillment.
It no longer makes sense to pull all that data into one repository just to maintain synchronization. You simply need to know that all customer, employee, and product identities are properly synchronized, no matter where the data is housed. And you want an efficient way to find the data when you need it.
Boomi DataHub is simply the best technology to do all that.
To learn how Boomi DataHub can help solve your data quality problems with a simple, cloud-native service for data synchronization, contact the integration experts at Boomi or Kitepipe today.