My series on planning visualizations has so far explained how to use the right chart types to tell your plan’s story. Today I’ll wrap up with a focus on using visualizations to show how your plan will hold up as the fiscal year progresses. The charts below display forecasts that are based off of 12-24 months of historical data used to predict future results.
Plan vs. Actual Spend: Bullet Visualization with Linear Regression
Good planners know that a plan shouldn’t simply be created, approved and then left to rot on a shelf somewhere. Plans should be managed and updated throughout the year. Even the best plans require changes, especially when it looks like you might be getting off track.
Say you’re a marketing director for a retailer and your fiscal year begins in January. In March, you’re starting to wonder if there will be enough funds in the budget by September to do your holiday season advertising. There’s a way to predict this information, even if you’re only a few months into the fiscal year. A finance professional might run a linear regression and stick a table in Excel to show the progressions of the budget over time. But as a marketer, you’re a visual person and might better understand a bullet chart. Plotting the actual data (in yellow) against the plan data (in gray), it’s easy to see that marketing expenses were understated in the plan from the beginning, or you simply overspent early on and won’t recover without making adjustments to spending. The red bars show just how far off spending will be vs. the plan if you don’t take corrective action:
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.
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…
Everyone is throwing around the term “analytics” – about as much as they’re throwing around the term “big data.” While I might put big data on my list of the Most Overused Phrases, analytics gets a pass. As companies realize the amount of insight and value they can glean from their ever growing volumes of data, there has been a surge in analytics initiatives. The goal of these projects is to use data to analyze trends, the effects of decisions, and the impact of scenarios to make improvements that will positively impact the company’s bottom line, improve processes, and help the business plan for the future.
In order for analytics to remain relevant and always provide value, organizations must continually up their game. One way to do this is with predictive analytics, which is becoming more mainstream every day. If you stick around to the end of the article, I’ll tell you a simple way to bypass its complexity and still get the predictions you need.
Gettin’ Predictive With It
Predictive analytics involves making predictions about the future or setting potential courses of action by analyzing past data. A 2012 benchmark study by Ventana Research revealed that predictive analytics is currently used to address a variety of business needs, including forecasting, marketing, customer service, product offers and even fraud detection. While predictive analytics used to be in play in only a small number of companies, two-thirds of companies participating in Ventana’s survey are using it, and among those, two-thirds are satisfied or very satisfied. These results indicate the maturity that predictive analytics has undergone over the last few years, as technology has advanced to make it less expensive and more approachable, and therefore easier for more areas of the business to make use of. At this point, it’s safe to say that most Fortune 500 companies are churning out predictive insights on a regular basis, but that doesn’t mean smaller companies without “big data” can’t do the same thing. They can supplement their internal data with external data from social media, government agencies, and other sources of public data to get the insights they need.
Let’s take a look at finance institutions, which have predictive analytics down to a science….
Regression analysis finds the relationship between two variables and is often used for projecting future data. It’s an extremely complicated formula that starts with…
Regression Equation(y) = a + bx
Slope(b) = (NΣXY – (ΣX)(ΣY)) / (NΣX2 – (ΣX)2)
Intercept(a) = (ΣY – b(ΣX)) / N
…but that’s just the beginning. You may want to leverage software to do the heavy analytical lifting for you.
In the example below (video), we’ll go over how regression analysis can predict 12 months of future sales data based on 3 years of historical data. arcplan Enterprise business intelligence software includes a linear regression formula that takes all the guesswork out of your calculations. You can change your assumptions with the click of a mouse and the system instantly delivers a new regression line that projects updated future data. Check it out and let me know what you think!