Dynamic Business Planning with Standard Deviation

The Quarter-Long Exercise of Planning.

Business Planning is a time consuming task. Most businesses dedicate between 1-3 months to put together their annual business plans for the coming year. No matter the type of business,  this task is always challenging, open to bias and in very few cases is actually justified with hard data. The outcome of the planning exercise in many cases, is subject to immediate adjustments, rendering this time consuming exercise almost useless right from the start. Standard Deviation can be a very powerful tool that can help businesses find the right drivers to increase their profits, and it can also aid in reducing the amount of time needed to come up with this planned figures.

Using Standard Deviation in Business Planning.

Standard Deviation is a basic statistical concept that represents the dispersion of any given set of quantifiable data. Using Standard Deviation, businesses can formulate a positive or negative scenario, which would server well as an annual plan for any business. Another advantage of this approach, is that the business plan would be created based on previous business facts, this would reduce the chance for bias and it would also improve the time spent in this exercise, as this model can be automated and it would reflect any changes already posted to business data historical records.

A door to new opportunities.

Dynamic business planning via analytical models like this, open the door to multiple new tools that can greatly benefit businesses. One example of such options would be the application of another analytical technique called Classification Trees. Consider the following example. You are reviewing expenses for 1 business line over the past 5 years. In the chart below we can observe the darker line in the center being the mean of this data set while the standard deviation is represented by the shaded area surrounding the mean.

Business Executives can create projections based on standard deviation and can dynamically adjust those projections based on new data being incorporated in the historical records. Furthermore, the application of classification trees to the outliers of this dataset (the highest and lowest peaks of the shaded area) would yield details behind those transaction that can be used to create new dashboards to aid in the monitoring and control of such incidents.

Sounds interesting?, feel free to email us at contact@ionrva.com for more information!