Demand planning is an essential part of business planning and involves marketing, sales, finance, production, logistics etc. A good demand 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.
Producing an applicable and trustworthy statistical baseline forecast requires processes, skills and tools. However in practice:
- Processes are not transparent and built for improvement
- People with business knowledge are not supported by data insight
- People with demand planning knowledge do not have knowledge to operate statistics and tools
- Tools are not intiutive and too complex to operate
- Tools do not provide newest technology with focus on how to improve the forecast and process
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.
Now is the time to consider digitize the demand planning and focus on your core processes of your business planning, operations and continuous development.
The potential pros of digitizing the demand planning:
- Simplify demand planning and more focus on market insight
- Transparent process with focus on improvements
- Creates stability and trust in your general forecasting process and business planning
- Eliminates the need for hardcore in-house statistical skills
- 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 digitizing:
- Risk of data. Therefore ensure data encryption
- Change management: People have to adopt to new processes and Technology
- Only focus on Technology: People and process area are more important than technology
At sophub we are mitigating the potential risks by data encryption, provide a change management consultant to ensure proper process and load process and people training that exactly match the situation of the company.