Consistent, correct data. That doesn’t sound too complicated, does it?
Consistent, correct data. That doesn’t sound too complicated, does it? But actually, one of the most daunting challenges facing CFOs and their staffs today is how to ensure that the financial information they supply to stakeholders, both externally and internally, is consistent and correct.
The checklist for compliance seems to grow whenever you turn around. Sarbanes-Oxley, US Patriots Act, HIPAA. MiFID, Basel II, PCI data security standards, etc. – were these even part of our vocabulary several years ago?
Even when we have achieved statutory compliance, can we really audit our data from the point of origin to consumption? Why do we rely on so much manual reconciliation to audit and trace the data flows across systems each month, whether for cash flow forecasting or revenue recognition validation? Wasn’t each one of these financial systems supposed to get us the “single version of the truth?”
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Sure, the enterprise application vendors promised information nirvana. All the business intelligence (BI) and corporate performance management (CPM) vendors promised the same thing. Now we have “multiple versions of the truth.” Talk about an oxymoron. As a result, we’re performing more manual reconciliations than ever before!
Why are we in this “Twilight Zone” of data silos? Quite frankly, we have neglected to treat our data as an enterprise asset just like we treat other assets. Gathering all our data into spreadsheets is not managing data – it’s just masking our problems. Not only do we risk creating incorrect numbers, but it drains our productivity by requiring our skilled and highly paid staff to spend inordinate amounts of time hunting and gathering data.
This is where Enterprise Data Management (EDM) comes in. With EDM you’ve got executive sponsorship, alignment and collaboration between business and IT, and shared metrics. Now we’re talking.
EDM also calls for data governance procedures with internal controls over financial reporting and other business processes. To make it work, you need to design and implement a holistic data integration architecture that is application-neutral, with inherent data quality and integrity.
I will share with you more details over the coming weeks and months how to take this seemingly daunting challenge and be highly successful in establishing data as an enterprise asset.
