It’s impossible to work with enterprise application software and not be fascinated by The Borg. Advances in automation are constantly and inexorably being assimilated back into the enterprise collective. (Resistance is futile.) General ledger achieves automated input from accounts receivable (financials). Next, AR becomes connected to sales (CRM). Eventually, sales bills directly from the catalog (procurement) and automatically feeds commissions (payroll), which pays employees (human capital management, HCM) via bank accounts (treasury), and it all eventually becomes “ERP.”
Or so we’d like to think…
The first rule of assimilation (sorry, that’s Deep Space 9) is that there’s always value and motivation to venture beyond the current edge of the Enterprise Borg. Finally get those AR-related journal entries into GL? The “G” stands for, “Gee, we’d love to see customer and product information from the billing system in there too” (interface programming estimate: 2 weeks). This process can never stop while newer insights remain to be gleaned from newer automation.
One reason salesforce.com profitably tweaks the noses of their once-larger competitors (who generally prefer to compete by buying out their rivals rather than catch up) is that its customer data remains a window into the wider outside world that will always be most valuable when it’s not limited to that inward “ERP” perspective. The moment Siebel disappeared inside Oracle, it ceased to innovate beyond whatever served the collective. Ask SAP why they acquired Hybris, Callidus, et al., and you’ll receive a laundry list of ERP-relevant advantages. Now ask an SFDC customer why they run that system alongside Oracle or SAP—and you’ll receive a different answer.
However brilliant the value of beyond-the-Borg customer-facing systems, you will inevitably run into the classic wish-it-were-all-ERP gotcha: among dueling data sources, which version is “truth”? In the boardroom, what good is the “right” information from one system, if it’s indistinguishable from conflicting information from another?
Useful approaches attack this “version” problem from all sorts of angles. Master Data Management, as previously examined, eases conflict by standardizing important data elements before the fact. It requires a certain amount of up-front effort, but it pays for itself repeatedly down the line. Data warehouses (what’s the hot term these days, data lakes?) skip past the knuckle-skinning difficulty of rationalizing data and transaction flows before the fact, and simply synchronize the results without the troublesome necessity of debits equaling credits. Caveat emptor (“garbage in, garbage out”), but 80 percent of the value resides in 20 percent of the data, as they say, and you’ll definitely have that.
But what if you could subscribe to a chimera that preloads a schema-agnostic treasure trove of all your best customer-facing stuff, and lets you slice it and dice it?
The ZEOs (a.k.a. Zuora’s employees) have imagined that future and taken advantage of their lead in revenue recognition to partner with Snowflake for the analysis part of things. Even were you to succeed in porting all your disparate revenue system data into one coherent view, you would forever remain hostage to each individual data source and its evolution and spend a lifetime tweaking the feeds. And just like you pay your tax vendor to insulate you from that sort of complexity when it comes to filing, it makes a certain amount of sense to consider a specialist for the analysis view, too.