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Every budgeting season, CFOs and executive teams put together a plan that represents a snapshot of what they believe will happen in their companies and industry over the next 12 months, based on their best available data. Then business happens.

For instance, overall economic growth has a huge impact on projections, but it can be notoriously difficult to predict. In 2017, the U.S. economy was expected to grow by 3 percent, but growth only clocked in at about 2.3 percent. Growth in the first quarter fell short of expectations, yet economists are optimistic it will pick up in the second quarter, reaching 3.7 percent.

There is one absolute, however: Actuals will always differ from plan for the simple reason that the economy is a highly complex organism. That said, it’s essential that all business users monitor variances in real time to either exploit unexpected opportunities or take steps to mitigate losses.

Course correction requires more than just spotting monthly variances. Business managers need reliable data at their fingertips so they can understand and address the source of variations. In my opinion, a company’s functional managers — the VPs of sales, customer care, operations and so on — should have the ability to run financial reports without the aid of the financial team, so they can monitor how their departments are performing in ways that are meaningful and relevant to them. In other words, we need to democratize financial reporting.

But there are challenges. To begin with, it isn’t easy to generate reports that validate or explain results. ERP systems may be efficient at collecting data, but they can’t easily push the information to business users for analysis. Spreadsheets, the go-to solution for many, aren’t particularly helpful, since they require a lot of time, effort and dexterity to pull together the necessary data into a spreadsheet and to create pivot tables. Besides, one data source alone probably won’t explain a variance. For instance, let’s say the VP of sales notices that revenue is 5 percent lower than expected. A spreadsheet can highlight a problem, but can’t explain why that problem occurred. That VP will need to consult additional data sources in order to understand the root cause.

That’s why I’m a fan of business intelligence solutions. I think of them as a data warehouse that can pull in data from a variety of sources, including ERP, CRM, payroll and GL systems. Business users can easily layer those datasets on top of one another in interesting and relevant ways to them. They also offer visual tools and dashboards, which allow end users to establish their own KPIs and then organize and display data in multiple ways so that issues they need to address are immediately apparent.

Going back to the VP of sales’ need to explain a revenue shortage, he or she can dig into the data to identify the region and the the specific offices that are underperforming. And by layering CRM and payroll data, the VP may further learn that the Chicago office has new sales reps who has just completed training that quarter. The VP can also look for subtleties such as too much deferred revenue via discounts.

Because dashboards incorporate more than just financial data, business people can use them for operational reporting. For instance, by pulling CRM data, one can easily display revenue and sales reports by product, region, salesperson, customer type or other metrics important to the organization. This allows the company to identify which customers are buying which products so that marketing can target them more efficiently and the sales teams can interact with them better. This is why business intelligence enabled self-reporting is mission critical. Each business user should be allowed to choose which data to look at, as well as how to look at that data.

Bringing it back to the opening challenge, there is no easier way to understand why those actuals differ from plan. Let’s say you want to see a combination of your actuals and plan data to assess performance to date. Since it’s April you have four months of actuals to compare to eight months of plan (i.e., a 4 + 8 comparison). Plotting that trend line in a graph allows you to see at-a-glance whether your actuals are in line with your plan, or if a reforecast is required.

Business intelligence isn’t new. BI has been around in many other applications for decades. What makes it so revolutionary for financial teams is that it allows them to make complex and malleable data available to their peers, all while getting them out of the report-generation business.

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