Today’s business executives love to talk about data. Machine learning, AI, digital transformation, data-driven analytics, algorithmic business—these concepts all rely on data’s ability to paint very detailed, accurate portraits of how businesses, markets, and products are performing and behaving.
But more and bigger data doesn’t necessarily mean more or better truth, and as BlackLine’s Platform Director of Product Management, that’s what’s on Stephen Wolfman’s mind.
BlackLine Magazine: What’s wrong with the way business promotes and relies on data?
Stephen: The phrase “data-driven” sounds great, but it’s become such a cliché that people don’t think about what it really means. It suggests that in business, we rely on data, which is true.
But by itself, that may not be a good thing, because not all data is good data. So some businesses may be relying on the wrong thing, and that can be harmful, not helpful.
BlackLine Magazine: What’s an example of this?
Stephen: Any time you move data from one place to another—from one application to another—there’s a risk that something could change. For instance, if you load GL data from an ERP system into a spreadsheet, you’re at risk because the data may be changed in the process.
Even within the ERP’s GL system, you’re not getting the same controls for validating and substantiating data that you’d get in BlackLine.
This can be very harmful if you’re going to use that data in financial reports, or for analysis by business intelligence software.
If a 10K or 10Q report goes out with incorrect data, your company can suffer in a variety of ways. A misstatement is embarrassing, but it can also erode investor confidence or damage customer relationships.
BlackLine Magazine: What can companies do to maximize trust in their financial data?
Stephen: They can make sure they’ve got strong controls across the breadth of data. This is something that’s hard to do if data is passing through many peoples’ hands, from ERP systems to spreadsheets, and so on. A major benefit of process automation is that you can apply controls across all processes that touch the data.
For instance, an important control in BlackLine is segregation of duties. This makes sure that a preparer and a reviewer cannot be the same person. That’s just one example.
With process automation, your financial data and its documentation are always visible. You can look into that data and see all the relevant accompanying documentation.
You can see who the reviewers are and trace the workflows to make sure the right reviewers are getting the right materials for checking. And if you’re using automated connectivity controls, you can make sure that the data flowing into your finance system from IT is also trustworthy.
BlackLine Magazine: How does BlackLine build trust into that connectivity?
Stephen: We put a lot of effort into our application programming interfaces (APIs) and connectors in order to strengthen the integrity of data imports and exports. For instance, in a more tightly coupled data transfer process, we can catch disruptions or errors automatically, so they can be brought to our attention immediately.
Enhancing the integration between BlackLine and the ERP allows for controls and workflows to be placed around operations activities, so the status of those controls is visible in real time.
This is good for IT teams who might not be familiar with BlackLine, and it promotes the idea of using more of BlackLine—and better finance controls—throughout the organization.
Read our latest issue of BlackLine Quarterly to discover more about how your organization can increase the quality of and trust in your data.