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Become a strategic business partner using analytics in finance
By Leo Sadovy, SAS Industry and Product Marketing
Collecting, validating and reporting information is no longer enough for finance professionals – it's time to up the ante using analytics in finance. Why? So you can moved from just reporting past results to the role of supporting better decisions for the future. Those who don’t make that transition will be left behind as other businesses move ahead sharing much needed insights with key stakeholders. Here are three tips to get started.
A recent study found that as much as 80 percent of analysts' time is spent doing manual data work and manipulating spreadsheets.
Don't depend on spreadsheets
No one loves a spreadsheet more than a financial professional, right? Unfortunately they’re time-consuming to create and maintain. At best, they provide one-off analyses. And quality control is nonexistent.
Think about all of the data that finance departments have access to. POS and EPR transactional systems. Other systems of record such as customer loans and credit balances. Consumer behavior data from loyalty programs and call centers. Real-time sensor and operational data.
But if you are manually entering data into spreadsheets, or aren’t reconciling data for consistency with business rules, you will never win the quest to spend more time analyzing data and less time collecting and validating data. It’s just not going to happen.
Just thinking of spreadsheet data issues is enough to give anyone a giant headache. Here are just a few to mull over:
- Operator error and rekeying data mistakes.
- Nonstandard data collection templates.
- Deliberate formula manipulation. (Does this really happen? You bet it does.)
- Decoupling from policy and data definitions. (Does this really happen? What do you think?)
A recent study found that as much as 80 percent of analysts' time is spent doing manual data work and manipulating spreadsheets. This leaves little time for analysis, and as mentioned there may be problems with inaccurate and untimely reporting, poor controllership, and low levels of auditability and compliance.
The key is to replace the spreadsheets with a tool that automates data gathering, eliminates the need for all those individual spreadsheets, allows analysts and business users easy access to consistent information and analytic tools, and provides a process that is auditable and compliant.
It’s time to move beyond spreadsheets and use real analytics in your finance department.
Add forecasting and scenario analysis for true analytics in finance
Scenario analysis and forecasting can help project future revenue and mitigate operational risk. And when you think about it, forecasts are your one piece of forward-looking data. So use them! How?
One tip is to move beyond your dependence on just one forecast source, typically a monthly update to the field’s salesforce forecast, and instead use multiple forecast sources as appropriate. These can include industry and government data, shipment and inventory status, pricing and promotion history, marketing and product launch plans, and ERP backlog. Then, make them available in an integrated form to the overall planning process. Or to specific users who need to focus on different areas.
The forecasts then become not just a single input but a collaboration across your organization – and provide a more informed view of what can be expected.
You will also want to follow a planning hierarchy where you feed the forecasts into a scenario planning process, which in turn will trigger resource deployments and priorities. No more knee-jerk reactions to forecast changes – replaced instead by the predetermined scenario corresponding to the updated conditions.
With scenario analysis, you can experiment to see how different factors affect operations and projected profits. Things like sequence and path analysis can answer questions like which resources or operational activities make up the majority of costs of your best-selling products. Or, what might be the impact of an outsourcing initiative or shared services model.
Forecasting and scenario analysis together can put finance in the position of enabling the agile organization by having the right response to changing markets ready to implement at the right time.
Layer in visualization and democratize analytics in finance
Data visualization lets you see – literally – all of the correlations and insights hidden within your data. Instead of looking at rows and columns in a spreadsheet, or a purely numerical report, you can see data represented graphically – and in the proper business context – using things like trends lines, heat maps and numerous other charts and representations.
In addition, viewing different visual formats simultaneously can be extremely helpful. Something that is completely obscured in a spreadsheet may be slightly more evident in a bar graph, but instantly clear when displayed as a decision tree.
Interactive, self-service data visualization lets financial analysts, even those with limited analytical skills, rapidly identify key relationships and uncover insights. And, sharing visualizations with others across your organization means they can explore data on their own as well.
Democratizing analytics with easy-to-use data visualizations can easily enhance others’ perception of the finance organization as a valued strategic business partner.
Leo Sadovy handles marketing for performance management and small to midsize markets at SAS. Before joining SAS, he spent seven years as vice president of Finance for Business Operations for a North American division of Fujitsu. Leo has an MBA in finance, and is the author of a biweekly SAS blog, Value Alley, which addresses the application of analytics to the strategic aspects of managing a business for growth and profitability.