Investaura consultants master the science and the art of developing realistic and accurate models of innovative technologies and businesses. The use cases are very diverse and comprise in particular:
- CapEx and OpEx planning for new network roll-out or technology migration
- Total Cost of Ownership (TCO) optimisation
- Service Costing and Profitability Analysis
- Value Selling of complex high-tech solutions
- Business simulation and scenario analysis for the entire company
One of Investaura’s preferred platform for business simulation is STEM from Implied Logic. STEM is a generic modelling tool used for strategic planning of ICT infrastructure and solutions. As a techno-economic planning tool, it looks into the future and generates short-term (6–24 months), medium-term (2–5 years) or long-term (5–10 years) forecasts: financial items such as revenues, costs (OPEX, CAPEX), profitability (e.g. EBITDA, EBIT), and also non-financial items (dimensioning rules, volume of equipment, number of staff, utilisation etc.). STEM is demand-driven, i.e. resources (networks, human resources etc.) are driven by demand (end-customers, services, traffic, revenues), as well as network deployment requirements.
The key strengths of STEM include:
- Graphical interface with object-oriented modelling, making it easy to communicate even large and complex models, their assumptions and their results
- Ability to handle both greenfield and brownfield networks and capture the status of the CSP at the start of the simulation (initial Bill of Material for assets; Balance Sheet / Profit and Loss etc.)
- Hundreds of pre-defined results, as well as an interface to define new results for various types of elements in the model (total business; customer segment; services; resources etc.)
- Shorter time periods (months, quarters, years) with flexible granularity over time and automatic results consolidation
- Scenario management and sensitivity analysis, making it very easy to handle alternative cases and compare their respective benefits
- Models can be exported to the web for multi-user access, enabling a large number of internal staff and external partners with no knowledge of STEM to run their own simulations.
Note that both bottom-up and top-down models can be implemented in STEM. Bottom-up models are usually very detailed and run the risk of becoming not only very complex over time, but also difficult to maintain. Furthermore, they tend to suffer from ‘precision fallacy’, and many aspects included in bottom-up models might only have a small impact on the overall results, while key but difficult-to-quantify issues might be forgotten.
For more information or a demo of STEM, feel free to contact us.