Asset Analytics & Profitability Evaluation Platform
Asset Analytics
09/2025 – 02/2026
Structured product discovery and concept design for a data-driven platform to evaluate profitability, payback periods and investment risk for mining hardware.
1. Background
The idea emerged from operational experience in the mining infrastructure space: an analytics product combining technical, financial and operational factors into a structured decision model. The central question was whether a reliable framework for evaluating profitability, payback periods and investment risk of mining hardware could be built — taking into account highly volatile input parameters — and whether there was a validated market demand for it.
2. Stakeholders
3. Challenges
- Volatile parameters such as network hash rate, asset prices, hardware costs, energy expenses and expected runtime make stable calculation models difficult
- No validated market interest at the outset — risk of overengineering without demand evidence
- Complex dependencies between platform architecture, data model and domain logic
- Business case required simultaneous validation of technical, operational and commercial assumptions
4. Analysis
The analysis began with a structured product discovery: defining the problem, scoping the initiative and establishing an evaluation framework. From there, the calculation logic for profitability, amortisation and investment risk was designed — embedded in a scenario model that captures volatile parameters such as hash rate, energy prices and hardware values. In parallel, architecture decisions were assessed (API/backend approach, data model, extensibility) and market validation was prepared to test commercial viability at an early stage.
5. Solution Options
6. Evaluation
- ✓The initiative produced a fully developed analytics and profitability model that captures the profitability, payback period and investment risk of mining hardware in a structured way.
- ✓Operational experience from platform work was successfully translated into a standalone product concept — a transfer that would have been difficult without structured discovery.
- ✓The go/no-go decision was made deliberately and transparently, rather than continuing to invest without validation.
- The high volatility of input parameters — hash rate, energy prices, hardware values — would require ongoing model maintenance, representing a significant operational burden.
- Without a dedicated sales setup, activating external market demand is difficult, leaving the platform dependent on a single channel.
- The mining market reacts strongly to external factors such as regulation, network hash rate and asset prices — product demand can shift rapidly as a result.
- Without a validated path to the target customer, there is no foundation for stable, scalable growth.
Product discovery and concept design over approx. 6 months (09/2025 – 02/2026)
7. Recommendation
Decision
No-GoPriority
Controlled termination after insufficient market validation
Next Steps
- Full documentation of all functional and technical aspects — calculation logic, data model, architecture decisions and validation findings.
- Scale down to internal operations for the client: only the core functionality actually needed for ongoing use.
- Preserve the concept and logic so that it can be scaled back up at any point if concrete market demand or a new client emerges.
Ready to collaborate?
I am looking for a permanent position as IT Delivery Lead / IT Project Manager.