Big Data

Bridging the gap between data analysts and the finance department

New opportunities for automated data consolidation extend the reach of financial reports and analytics. But will it be enough for CFOs?

Image: Song_about_summer/Shutterstock

When I was a CIO, no department demanded more data than finance. Finance had a team of financial analysts who manipulated data into myriad spreadsheets and reports—and a demanding CFO who would always want more data.

Financial analysts and CFOs were hard to please. They wanted daily, weekly, monthly and quarterly reports, as well as data for risk assessments and what-if scenario analyses. Finance used troves of reports to extract the information that it wanted to see—but it never seemed to be enough.

SEE: Electronic Data Disposal Policy (TechRepublic Premium)

“The primary issue CFOs face isn’t one of lack of access to reports,” said Didi Gurfinkel, CEO and co-founder of DataRails, an automator of financial processes and reports. “CFOs can (eventually) get the information and reports they need to make financial decisions, build models, produce management reports, etc. The bigger concern is the cumbersome process in producing these reports.”

That cumbersome manual process involves a full staff of financial analysts who cull financial data from systems that range from ERP and the general ledger to CRM and sales. Data from each system is reviewed on a daily basis, and at some point, the data from these systems must be hand-aggregated and built into a spreadsheet that is capable of answering standard and non-standard questions.

SEE: 5 challenges to implementing QA strategy in data and analytics projects (TechRepublic)

“When they use that process, what CFOs, financial analysts and business leaders lack is full, unimpeded access to consolidated reports and having all the available insights from the data at their fingertips,” Gurfinkel said.

This is where analytics tools like dashboards and drill-downs begin to make sense. They make the data much easier to navigate and, more importantly, to learn from in a timely manner.

However, to arrive at this point, data from multiple systems must first be consolidated into a central database—and this work should not be done manually by a financial analyst manipulating a spreadsheet. Instead, the data consolidation can be done with system automation. This saves financial analysts time, reduces the potential for human error and produces faster times to market for reports. The end result is a dashboard that summarizes data and that gives you drill-down capability into the details. This enables finance to create numerous reports and scenarios with data that will help it meet its insatiable need for information.

Gurfinkel mentioned a use case in which a company’s finance department spent hours of labor consolidating financial information from multiple data sources manually. Information from QuickBooks was exported into Excel spreadsheets and then reconciled, which required tedious work. Afterward, finance would go through hours of editing to ensure accuracy and prepare the information for company and executive use. By switching to automated data consolidation, the staff was able to see instant version comparisons and generate reports through a single interactive and consolidated platform. “They now save over 15 hours a week, time that was once spent on time-consuming, manual processes,” Gurfinkel said.

SEE: Data privacy laws are constantly changing: Make sure your business is up to date (TechRepublic) 

This doesn’t solve all of finance’s reporting needs. But data consolidation and automation that support analytics can bring together more data from diverse sources faster and save employee time while doing it. The process also makes finance more self-sufficient from an IT perspective.

However, “A principal difficulty when you suggest automated data consolidation is the willingness of companies to take the leap of faith. This is understandable because financial executives who have been crunching numbers and producing reports manually via spreadsheets for decades understandably do not want the whole system to change dramatically in a short period of time,” Gurfinkel said.

That’s a reason IT and other technology leaders must be cognizant of business process change (and resistance) when they try to implement automation for analytics.

As with most analytics and automation efforts, finance must be integrally involved in the project, and be the determiner of how it wants its business processes to change in order to take advantage of automation.

“With the help of automation, data consolidation is a means of revolutionizing the way finance does business, with far-reaching implications for the company; however, the implementation is key to a successful digital transition,” Gurfinkel said.

I’d second that, adding that a successful implementation depends on IT and finance shepherding the new process into full acceptance in the business, beginning with the CFO.

Also see

 Source link

Back to top button
SoundCloud To Mp3