Business Intelligence Blog from arcplan
22Mar/130

Essential Budgeting & Planning System Components – Part 2: Spreading

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In Part 1 of this series – a planning software buyer's guide – I covered the first essential component of a modern planning system: workflow. Let's keep the ball rolling with another component that is vital to your next planning solution.

Spreading
Spread methods are an efficient way to automate plans for a period without starting from scratch every time. Simply defined, spreading is the system's ability to take a budget value and spread it over a range of periods based on a divisible operator (like percent per month, for example). Your planning system should include built-in spreading functionality, especially the more popular methods – even (the most used method in practice), spread like last year, and spread like last year +/- a dollar value or percent.

Essentially, spreading is a fast data entry method. It will save time to have your system manage and centrally control your corporate spread methods. Users should also be able to create their own. A nice-to-have feature is color changes where data has been entered. Click to expand the image above and you'll see an arcplan Edge system, where blue cells indicate areas where data can be entered and yellow cells indicate that data has been entered during this session.

Note: The terms "spread" and "allocation" are often used interchangeably, but at arcplan we make a distinction between the two. To make it easy for our customers, we say that spreading is bottom-up only and occurs horizontally across financial periods, while allocation is vertically rolled-down spreading. For example, if your company has two divisions – one in the US and one in Europe – and $10 million in sales, you may decide to allocate 50% of that to invest in the US division and 50% to invest in the European division. This is an allocation rolled down from a higher level to a lower level, not a horizontal spread across. This may help you distinguish between the two terms.

The Future of Spreading
Spreading can provide so much more value than it currently does at most organizations. In our newest arcplan Edge deployments, we've embedded "corporate spreading" or "volumetric spreading." It's different in that it's a driver-based spread technique, rather than relying on a divisible operator (like percent per month). Essentially it's multiplication-based rather than division-based. With volumetric spreading, the spread is based on corporate growth drivers like growing transactions or increasing the number of new customers by X amount in the next financial period. The idea is that the costs associated with those drivers should align with the growth rate.

arcplan also enables spreading based on predictive modeling techniques like linear regression to predict a month's spread based on the same month from previous periods…meaning arcplan creates a regression that predicts what the spread for April 2013 should be based on historical data from the last 5 years' Aprils.

We even work with a customer that uses Monte Carlo simulation for spreading. Monte Carlo is a computer model that makes predictions. arcplan uses a historical min, max, and other parameters to simulate what the spread for the following period should be. It uses advanced visualization to show you what your plan data looked like last year, and depending on the spread technique you choose, it simulates a prediction for next year.

Sound complicated? These are all built-in functionalities of arcplan. To add value to your spreading process and ensure the longevity of your planning solution, make sure your vendor is capable of handling these types of spread methods.

Check out the other posts in this series:

Dwight deVera

About Dwight deVera

I'm Senior VP responsible for Solutions Delivery at arcplan in North America. I also present on a lot of arcplan webinars, so you can sign up to hear me - the events listing on our website is located here: http://www.arcplan.com/en/company/events/. You can also follow me on Twitter: @dwightdevera.