In this article, we will look at how driver-based advanced analytics has overcome the problems with...
This is the third article in a series of articles devoted to the wide variety of the benefits provided by the next generation budget, the operational budget (OB), and its associated operational income statement (OIS).
This article will describe an OB test case demonstrating that the OB really works. The first two articles focused on:
Part 1: Next Generation Budgeting, described how predictive and prescriptive analytics make OB possible and how easy it is to demonstrate OB’s value for a firm. NOTE: If the reader is unfamiliar with the first article, OB’s benefits described in this and subsequent articles will not be fully appreciated.
Part 2: Operational Budget’s benefits for the budgeting process
This article has four sections: i) background, ii) summary of OB’s results demonstrating it really works, iii) details of the OB’s model structure and data and iv) conclusion.
Background: The Operational Budget (OB) Really Works
After having successfully implemented the intellectual property (IP) in the OB modeling software, the author of this article had a question: would it really work? Where can we get the data to build a test case model?
Fortunately, the author and his colleague had discovered that in addition to the three traditional data sources a fourth data source existed: activity-based costing data. The colleague had such data from a previous ABC engagement at McCoy Belt Company (disguised).
They decided to investigate the extent to which McCoy may have made errors in allocating sales and marketing expenditures last year and the impact of these mistakes on last year’s operational results:
- Was profit lost in the mature markets (North America (NA) and Europe/Middle East (EME))? The firm could have spent sales/marketing resources fulfilling unprofitable demand.
- Had McCoy, an iconic brand with a worldwide reputation, lost profit in its newest market, the Far East (FE) because it had underinvested in sales/marketing expenditures?
McCoy hired a consulting firm to create an OB model of the last year’s results. To answer the two questions above, the OIS model had to be configured as both a profit and a revenue model with the following parameters:
- Maximize revenue: Demand is added to the base case if profitable. Demand is left in the base case even if unprofitable.
- Maximize profit: Demand is added to the base case if profitable. Demand is removed from the base case if unprofitable.
The results included four scenarios:
- Maximize revenue in all geographies: +20% and -20% sales/marketing expenditures (S/M)
- Maximize profit in all geographies: +20% and -20% S/M
- Maximize revenue: NA/EME +20% & FE +200% and in all geographies -20% S/M
- Maximize profit: NE/EME +20% & FE +200% and in all geographies -20% S/M
Summary of Results
Scenario | Revenue ($) | Profit ($) | Sales/marketing ($) | Sales/Marketing ROI % |
Baseline | $136.3m | $12.7m | $28m | 45% |
Revenue max | $143.8m (+6%) |
$16.3m (+28%) |
$28.6m | 57% |
Profit max | $140.9m (+3%) |
$19.8m (+56%) |
$23.6m | 84% |
Table 1: McCoy Belt Buckle Company Results (FE +20%)
Scenario | Revenue ($) | Profit ($) | Sales/marketing ($) | Sales/Marketing ROI % |
Baseline | $136.3m | $12.7m | $28m | 45% |
Revenue max | $173.4m (+27%) |
$30.0m (+136%) |
$34m | 88% |
Profit max | $170.5m (+25%) |
$33.5m (+164%) |
$33.5m | 116% |
Table 2: McCoy Belt Buckle Company Results (FE +200%)
Table 1 and 2 illustrate the power of the operational budget (OB) to identify any firm’s unrealized profit and revenue opportunities that were left on the table last year. Such a test case also serves as the business case for the firm to deploy the OB.
The assumptions made for this test case are detailed below.
Details of the Model’s Structure
Test case operational budget model structure included:
One facility: US plant/distribution center
Two products: standard and custom
Nine customers:
- 5 regions in North America
- 2 each in Europe/Middle East and Far East areas
Links between plant and all customers for all products
Eight response functions
- 6 for the 3 areas (NA, E/ME and FE)
- One for +/- 20% sales/marketing expenditures off baseline in each area
- One for custom and one for regular product
- 2 for FE area
- One for + 200% and -20% sales/marketing expenditures off baseline
- One for custom and one for regular product
Thirty three activity cost functions
- Costs of Goods Sold (COGS)
- 7 direct manufacturing
- 11 indirect manufacturing
- 2 warehouse
- Selling, General and Administrative Expenses (SG&A)
- 6 Selling expenses
- 7 G&A expenses
NOTE: The OB data associated with this structure is too voluminous for this article. For more details, please click here.
Conclusion
The next three articles will describe how the operational budget can enhance three techniques that have been developed prior to the OB to improve on the traditional budget. They are i) the rolling forecast, ii) a management model that eliminates the traditional budget altogether and iii) zero-based budgeting.
Following those three articles, there will be an article describing benefits for two functions outside Finance (S&OP/manufacturing and sales/marketing) and a cross-functional application (scenario planning).
The concluding article will describe how OB’s analytics can be applied to extend M&A’s current advanced analytics.