Key Challenges & How to Solve Them
Forecasting is fraught with error
Accurate forecasting of sales revenues is absolutely critical for businesses and their ability to adapt. If your forecasts are too high, overinvestment in capacity and excess or impaired inventory will be the consequence. Too low, you forego sales opportunities and disgruntle customers. Key causes for forecasting errors despite traditional budgeting processes and systems are as follows:
- Distorting biases: Conflicting interests, hopes and perspectives taint our expectations. Sales people lowball their forecasts for higher commissions, new product developers overestimate the demand for their ideas to secure approval, customers overpromise on future purchases to get a lower price.
- Things change: The future is always uncertain, for many reasons. Competitor actions, geopolitical events, technology breakthroughs, regulatory changes, or sourcing issues can all result in expensive forecasting errors.
- Blackbox problem: With statistical forecasting methods, such as correlation analysis, trend analysis, or dynamic modelling, deviations are hard to interpret and forecasts are highly dependent on the algorithms applied.
- Data issues: Data analytics depend on the availability of historical data and its quality. In the event of significant market events, humans will understand the meaning of input data more profoundly than statistical algorithms.
The Prediki Solution
Tap collective intelligence for better forecasting
With Prediki's simulated stock market mechanism you can harness the proverbial Wisdom of Crowds to produce significantly more accurate and reliable revenue forecasts. The necessary knowledge already resides with your employees or your customers.
WANT TO IMPROVE SALES FORECASTING? COMBINE HUMAN INSIGHT WITH STATISTICAL FORECASTING.
Besides giving you more accurate sales forecasts, Prediki offers you additional benefits not afforded by statistical methods:
- What if: With Prediki, you can also produce conditional sales forecasts for possible strategies: general price increases, changes in positioning, large-scale campaigns, or key product launches.
- Collaboration: As a key side effect, crowd forecasting improves internal communication, cooperation, and spontaneous self-organisation.
- Price forecasts: In the same way, your crowd can also forecast likely changes in the market price of commodities.
Applications: Sales and demand forecasting, market price predictions, revenue and turnover projections.