What can a predictive analytics project cover?
A project can investigate a defined forecast such as weekly product demand or monthly revenue. Agree the decision it will support, the forecast horizon and the level of detail before choosing a method. Results need to be evaluated against a suitable baseline. A forecast remains an estimate; it does not establish what will happen or which business decision is best.
How do you check forecast accuracy?
Reserve later historical periods for evaluation and train only on information that would have been available at the forecast date. Compare errors with a simple baseline at the same horizon and level of detail. Agree the metric and examine results across relevant products, locations and periods. Report limitations and failed cases, rather than presenting a single accuracy percentage without its definition.
How much data is needed?
The requirement depends on the frequency, seasonality, changes in the business and the question being asked. Review missing periods, returns, promotions and changes in how records were collected. More records do not automatically make a forecast better. If the history cannot support a useful evaluation, start with a simpler planning method or improve data collection before considering a model.
Can the project connect to accounting, retail or CRM systems?
Check the exact platform edition, API or export options, permissions and required fields before promising an integration. Agree the approved data, processing locations, retention and reviewer access with the selected providers. A sample export may be enough for an initial evaluation. Live updates and write access should be separately scoped and tested.
Are scenario ranges the same as prediction intervals?
No. A scenario range shows what follows from selected assumptions; it does not assign probabilities. A model prediction interval needs a stated method and evaluation of how it performs on relevant held-out data. The calculator on this page is arithmetic using your inputs. Its lower and higher cases are not model outputs, confidence limits or forecasts.
Can forecasts be used for stock or workforce planning?
They can be one input to a reviewed plan. Stock decisions also depend on lead times, service targets, cash and supplier constraints. Staffing decisions require consideration of skills, availability and applicable workplace requirements by the responsible manager. Do not infer individual health or absence from a demand forecast. Agree who approves any resulting order or roster change.
What happens when actual results differ from the forecast?
Define a review threshold and responsible person during scoping. Check data quality and known changes before attributing a cause. A change in conditions may require pausing use of the forecast, revising assumptions or testing a replacement model. Retraining does not guarantee improved performance; compare the candidate with the current method before adopting it.
How long does a project take and what does it cost?
Agree a quote and milestones after reviewing the data, evaluation plan and required connections. Separate data preparation, model evaluation, deployment and ongoing review in the proposal. This page does not promise a production model within a fixed number of days, a subscription price or a particular financial return.