Look ahead with data
Historical patterns are turned into an evidence-based estimate of what may happen next.
Optimise planning with AI
Compare more scheduling options and align capacity more closely with what happens in practice.
Planners have to balance many constraints at once. As scheduling becomes more complex, it becomes difficult to compare all the options manually. Data science and optimisation techniques help create a workable schedule.
From an isolated possibility to a useful application
An application only becomes meaningful when it aligns with a specific task and the information available for that task.
Planners can assess the outputs and adjust them based on information outside the model. That is why we decide in advance what the solution should and should not do, how its outputs will be checked and who remains responsible.
What it delivers
Support planning
The results help staff weigh up future capacity, stock or maintenance needs.
Make uncertainty visible
Predictions are tested and remain a tool to support decision-making.
Our approach
-
Define the decision and forecast horizon
We establish what needs to be predicted and how far ahead.
-
Examine the data
We assess the quality and predictive value of historical data.
-
Develop the model
We start with a simple method and compare performance.
-
Validate the results
We test predictions against historical periods and with experts.
-
Integrate and monitor
We bring the results into the process and monitor model performance.
Aligned with your organisation
This service is relevant for organisations with complex staff, maintenance or capacity planning. The exact setup depends on the process, the available data and the risks involved in its use.
We therefore start with a clearly defined application and only expand it once the initial setup works in practice.
Other solutions
One data platform for fragmented sourcesBring data from separate systems together in one place, where everyone sees the same figures.
Dashboard for day-to-day operationsSee how things stand on one screen, without having to build reports first.
Predicting when maintenance is neededPlan maintenance based on what the data says, not on a fixed schedule.
Frequently asked questions
This service addresses the following challenge: using data science and optimisation techniques to help create a feasible schedule. Exactly how it works depends on the process and the data available.
The service may be relevant to organisations with complex staffing, maintenance or capacity scheduling. A clear need and usable information matter more than the size of your organisation.
That depends on the application. We start with the question you need to address, then determine which data or sources are necessary and suitable.
No. For routine, predictable tasks, conventional automation may be enough. We choose the simplest approach that addresses the challenge effectively and add complexity only when needed.
We define the scope of the application, check the results with users and put appropriate controls in place. Once it is in use, we monitor how it performs and adapt the solution when the data, how it is used or the context changes.
Discover what optimising planning with AI could mean for your organisation
Want to explore where it makes sense to start optimising planning with AI? Together, we’ll map out the challenge, the available information and the constraints.