Strategic forecasting is the translation of a company’s ambitions and long term goals into a Strategic Forecast, where different scenarios can be simulated to support various business cases.
Ambitions and long-term goals are translated into high-level goals for the organization. Strategic forecasting is the process that you go through as an organization to determine your long-term expectations. It describes the top priorities of the company and where energy and resources should be focused on.
A strong strategic forecast is created based on both internal and external drivers and is on a less detailed level compared to a regular budget or forecasting process. A strategic forecast can cover 5 or 10 years, or even longer.
Strategic forecasting begins with defining drivers that lead to certain expected outcomes/goals. This is in contrast with the general long-term planning process which is currently in use at most companies. Most planning and forecasting (or long-term) processes start with the current status (latest actuals) and are used to meet estimated future needs.
For example, in other long-term planning and forecasting processes, the sales-forecast is the starting point (top-down). In strategic forecasting, the focus is rather on drivers like the marketing efforts (FTE), economic growth rates, purchasing power which all have an influence on the sales forecast.
Purpose of Strategic Forecasting
The purpose of the strategic forecast is to gain a more in-depth knowledge of the effects that result from various business cases. Common business cases are price fluctuations, supply shortages but also investments and divestments. Since these type of business cases have a large impact on the company it is desirable to know what the impact can be on the business.
For example, selling a certain non-profitable business-unit, will this decrease or increase our total profit? Or acquiring another company, what will the effect be on the company as a whole? What extra resources do we need and are these available? With strategic forecasting, you can predict various scenario’s and define if the specific business case that seems to be beneficial to your company is actually beneficial.
The results of Strategic Forecasting:
Early insight into market behaviour effects and the ability to use internal strengths to respond agile to possible external opportunities and threats
Get a more accurate and in-depth view on the effects of various business cases and scenarios for acquisitions, investments or divestments
Ability to benchmark your past performance against competitors and future performance to your strategic forecast.
Strategic Forecast in SAP Analytics Cloud
What is SAP Analytics Cloud?
SAP Analytics Cloud (SAC) is a solution that combines analysis, visualization, planning and predictive capabilities in one product. The strength of the product is that it aims for “simplicity” so that the business can master all parts of the tool and is not dependent on IT and/or in-depth BI or needs Predictive skills. For more information about SAP Analytics Cloud, read this article.
Why Strategic Forecast in SAP Analytics Cloud?
Sap Analytics Cloud offers a number of advantages that make this solution ideal for strategic forecasting:
Structured data and one version of the truth
Database connection to various source systems (e.g. SAP Business Planning and Consolidation, BPC)
Easy simulation of different scenarios to support your business case
Predictive-based on past results
Accessible from various devices
How to implement Strategic Forecasting in SAP Analytics Cloud?
When using the predictive possibilities of SAC, you can create a forecast for the coming months, this forecast is based on the actual data available in SAC. SAC uses machine-learning, therefore, the forecast becomes more reliable as the years available in the system increase, more years available also gives the opportunity to forecast larger periods at once.
This automatically generated forecast can be easily updated by using a value driver tree or by adjusting top and base level members in your story.
Value driver tree
A value driver tree helps you to answer the “what if” questions based on actual data and company-specific drivers. A value driver tree allows you to simulate a scenario in one area and directly see the effects it has on other areas of the business and your business.
There are 2 types of simulating your scenario’s in a value driver tree
Using a Year on Year Node
Simple calculation node
The main difference between a Year on Year node and a Simple Calculation node is that the simple calculation node is used for more detailed calculation while Year on Year node is used on a higher level.
Year on Year node
A year on year node uses previous data and a driver, this driver can be all kinds of percentual drivers. Examples of drivers are for example revenue growth percentage, Material cost growth percentage etc. If you put in a +3% in the revenue growth driver, the revenue will be simulated with a 3% growth rate, by using filters different simulations can be done for different products/business units.
Simple calculation node
The simple calculation node works like calculated measures in a story, it is calculated on a detailed level. An example of a simple calculation node is to multiply the volumes with the price to calculate the gross sales of a company. The simple calculation nodes can be easily generated by the usage of auto-complete, SAC uses the account structure and member formulas to easily generate a value driver tree.
Public vs Private Version
SAC gives the possibility to copy data from a public version to a private version (e.g. Forecast to Private Forecast). The private version is the version only accessible by the user who created this version and the ones who have been granted access to this private version (with ‘Read Only’ or ‘Read and Write’ restrictions).
By doing this, the user can simulate scenarios without other users being able to see the changes in the strategic forecast. When the desired goal has been reached, the user can choose to overwrite the existing public version or copy the data to a new public version.