Statistical baseline forecasting is an essential part of business planning and involves marketing, sales, finance, production, logistics etc. A good statistical baseline forecast is the foundation for an efficient supply chain that ultimately improves service levels, cash flow, profitability and competitiveness.
The statistical baseline forecast bases its predictions on historical data by attempting to identify trends, patterns and business drivers. Typically, these forecasts are then manually enriched and adjusted by company stake-holders based on in-house knowledge of in-coming sizable orders, extraordinary drop in demand or other external factors not displayed in the historical data.
The use of a trustworthy and reliable statistical baseline forecast tool creates a general forecast process that is calm, transparent, reliable, fast and efficient.
Producing an applicable and trustworthy statistical baseline forecast requires in-depth statistical knowledge and experience. The data is typically infested with errors and needs to be cleansed and then segmented. The correct statistical algorithms chosen, integrated and executed. General ERP solution suppliers have yet to implement a statistical baseline forecasting tool that is intuitive to use, applicable and which delivers a decent predictive accuracy.
Human interaction with the statistical process can be confusing and produce days and even weeks of comprehensive work-loads that still do not provide an applicable statistical forecast due to the high amount of complexity in the data and statistical applications.
Luckily, the technological development of big data analysis tools is on the rise – and allowing your statistical baseline forecast to be outsourced, could be the next strategic step in optimizing your total forecasting process.
Digitalizing and outsourcing essential business processes list high on the executive strategic agenda. Now is the time to consider outsourcing the statistical baseline forecast and focus on your core processes of your business planning, operations and continuous development.
The potential pros of digitalizing and outsourcing your statistical baseline forecast:
- Eliminates the need for hardcore in-house statistical skills
- Cleans and segments large amounts of data providing higher quality forecast
- Creates stability and trust in your general forecasting process and business planning
- Digital On-demand statistical forecasting saves time and potentially FTE
- Higher final forecast accuracy allows for fact-based strategical decision making
The potential cons of digitalizing and out-sourcing your statistical baseline forecast:
- In-house knowledge of non-strategic processes is pushed out
- Technology alone will not create Best Practice Supply Chain Management
- Human behaviour needs to trust new digital processes
But, if you always do what you have always done – do not expect different results.