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Big Data – at the Core of Productivity and Financial Forecasting

Large, complex organizations rely heavily on intricate forecasting methods when establishing their operating plans. Utilization of unit/standard costs linked to projected revenue growth is key to many corporate forecasts. However, this approach alone can mask true OPEX cost drivers, creating risks to the validity of the forecasted numbers.

Clearly, unit costs serve a purpose and are required, however for large enterprises with myriad product lines, they often mask visibility to complex cost structures. Without a clear understanding as to what is actually driving operating costs, companies manage in gross terms by using averages and expected standard costs. This may be good enough in a fairly static environment. However, in today’s current operating environment, so many industries are undergoing massive change.

Industries such as health care, communications, media, and energy are going through periods of major transformation as a result of regulation, consumer demand, and technology advancements. Forecasting and managing OPEX in these industries are increasingly difficult. Firms learn that products and revenues are shifting at a rapid pace. As a result, their traditional methods for forecasting their OPEX requirements often let them down. The unit costs are based upon the old paradigm.

Companies whose product mix shifts significantly in relatively short time-frames risk missing key revenue to expense relationships that will materially change future operating margins because they lack visibility to the real cost drivers. It is critical for companies to understand what is really driving the need for specific headcounts, such as skill sets, inventory, raw materials, etc.

To solve this problem, large enterprises must question their traditional forecasting methods. Identification of true cost drivers starts with doing a deep dive on the cost data, recognizing the business levers’ needed to manage outcomes. Data analytics can determine work drivers.

Determining Work Drivers

Traditionally, finance organizations don’t have access to or leverage the vast, rich data sources used by other departments (operations, human resources, etc.)  By evaluating data sources used by operations and human resources, finance will gain insights far greater than the traditional unit costs. These insights are particularly important for businesses going through significant change.

By leveraging new sources of data, businesses can create much better forecasting models. They gain greater visibility to the true cost drivers by providing management with the business levers they need to proactively manage OPEX in advance of any major changes.

Project timelines vary based on complexity. While there is no set time for programs to be revisited, it’s important to stay up-to-date with your forecasting models. But if you’re unable to update your forecasting, you should always take a step back and look at your cost drivers to enable better planning.

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