STEM help / Training / Two-hour tutorial demo

2.2.13 Homework suggestions for further experimentation

If you have enjoyed this tutorial, and would like more practice with the software, then please review the side-notes mentioned in the text as beyond the scope of this tutorial. These are recapped below for your convenience, in two separate categories:

Extensions to the narrative of this case study

  1. more thorough analysis of traffic in the busy period
  2. using optional Maximum Utilisation and Minimum Slack Capacity inputs to provision extra resource capacity as contingency for imminent additions
  3. assuming Distribution = Monte Carlo (i.e., the pure, non-extended version) when a ‘just-in-time’ deployment model is feasible for the first customer at each site
  4. a chassis might need to accommodate other types of cards (even the power supply)
  5. trying a phased roll-out which would limit the initial capex, but also delay revenue
  6. using template replication to model cards and chassis at individual sites
  7. charging for space in whole sq m at each site, or conversely working with the Usage Cost attribute which is charged only in proportion to used capacity
  8. trying a persistent resource for a kW or an aggregate, energy-required transformation as alternatives to the recommended, consumable resource with built-in time factor
  9. comparing Consumption results in years, versus quarters or months
  10. connecting multiple power-required drivers to the same Power resource.

Other software features mentioned in the text

  1. using Consolidation to graph aggregate quarterly/monthly results on an annual basis
  2. working with per-element and global User Data; e.g., to work with multiple currencies
  3. other transformation types, such as Input-Output Mapping or Expression
  4. other resource input bases, such as Installed Capacity or Incremental Units
  5. using a transformation to govern Sites or Planned Units for a resource
  6. other service input bases, such as Traffic or New Connections
  7. efficient pricing based on used or direct cost results
  8. choosing a suitable Discount Rate
  9. considering the terminal value of a business
  10. adding extra scenario dimensions, such as technical evolution or supplier pricing.

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