Collaborative planning

The information needed for strategic workforce planning processes is often distributed among several stakeholders, residing at different locations and belonging to different levels of the organisation. As an example, not all information might be available to central planners in the necessary detail and desired quality. Local planners usually have better knowledge about demand and supply drivers regarding their specific business unit or region. However, collecting and consolidating this information is a time-consuming and error-prone process.

Together with one of our long-time customers, Deutsche Bahn, Dynaplan has successfully implemented a model-based approach to collect and consolidate the information from multiple regions via Dynaplan’s secure cloud services. There is no longer a need to collect and distribute data using spreadsheets. Not only can local planners easily input data directly into their planning models; they can also assess the impact of different inputs by running simulations in the context of their own region or business unit. For the central planners, the approach greatly simplifies distribution of assumptions, collection of inputs, and consolidation of results. In short, the SWP process has become leaner, more engaging, faster, and more robust, thereby substantially increasing the effectiveness and efficiency of the customer’s strategic workforce planning.

Collaborative SWP

Several features of this collaborative process make it superior to most other solutions (see Figure 1):

  1. There is only one strategic workforce planning model, and its structure can only be changed by central planners.
  2. The model can be filtered – or sliced – along its dimensions, such as job clusters and regions. Hence, a regional filter ensures that regional planners can only see data relating to their own region.
  3. Once the model is set up, central planners can enter data for the model’s input variables and distinguish between central assumptions and historical records that will be read-only to the regional planner, and regional inputs, which can be set by the regions.
  4. If the model needs to be updated later, all regional planners will be informed automatically whenever central planners upload a new model version. Regional planners can then update to the newest version, and choose to keep any inputs they have already made.
  5. Central planners will be automatically informed whenever a regional planner uploads a new data version. For each region, central planners can choose which uploaded data version they would like to import. If variables can be edited by central as well as regional planners, central planners can select which variables should be imported from the selected data version of the respective regional planner. Smia will then automatically import the data of the selected variables for the chosen data version.
Figure 1: Collaboration during SWP
Figure 1: Collaboration during SWP

The automation of big parts of this process saves a lot of time and reduces the likelihood of errors. Smia’s version handling makes it easy to ensure that all regions work with the latest model and data at any time, avoiding version conflicts, time-consuming rework, as well as potential errors due to manual transfer of data both ways between central and regional planners.

In addition, the complexity of this process becomes manageable, making all necessary information for central and regional planners available at a glance, while keeping the process flexible to account for unforeseen changes.

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