Finance as the Gatekeeper in the era of Big Data

We have data everywhere  and with the advent of new technologies we  are now getting the ability to collect the data , access and use it.  Data brings with itself  the ability to mine new information and provide new insights into trends etc. But with big data also comes into question more risk of the data being compromised to outside sources, data quality issues,inaccurate data etc. The more we use data in decision making, the more important it becomes that  their are controls and compliance around the collection, storage, access and use of that data.

According to  Deloitte's CFO signals Q2 2017 report  more than half of the financial professional surveyed say they are not yet moving beyond the piloting phase for emerging technologies . Of those who cited aggressive use of new technologies 77% reported improved consistency and controls was the top improvement area while improvement in analytical/decision support was next at 75%,

Quoting Isaac Tucker, VP Product Management , Blackline, "The challenges with data will always relate to volume and complexity, and that is only going to increase as companies increase their adoption of technology. As more and more data is collected, someone has to make sure that everything is correct, and the buck stops with the finance chief.”

FP&A Center of Excellence

Issues in data management, access, quality, use etc can cause of lot of problems.  This is further amplified in the area of financial planning and analytics as this data is used for reporting KPIs, developing forecasts, making decisions for the future strategic direction of the company etc. Missing or inaccurate data can lead to incorrect decision making, delays  and missed opportunities  and in some cases compliance  issues with reporting agencies.  As I mentioned in my last blog post , Data Scientist as a Job Function within FP&A,  their is a need for the an FP&A COE or Center of Excellence where data scientists  can work together with FP&A professionals to manage data assets  and develop predictive models for forecasting. It is this centralized group that can develop data governance and compliance. Today much of the financial data  and models are distributed in excel sheets, ERP systems  and the general ledger etc.  This requires  FP&A analysts to spend time consolidating data from different sources, ensuring that the data is accurate and reconciling different versions of truth   which means that today FP&A analyst spend 90 - 95% of their time cleaning the data and getting it ready for analysis and 5-10% actually " doing " the analysis. Data governance becomes a secondary requirement in this activity especially when no central or standard controls exist.

In the end , it is the financial data that gets reported in the market  and  majority of the KPIs used to measure progress and performance  are based on financial data.  All the marketing and sales analytics should reconcile with financial analytics making finance "the gatekeeper" for data governance and compliance for the company.