99Miners Analytics – Profitability & Investment Analytics
From operational platform experience to an analytics product concept: structured discovery, business-case modelling and controlled go/no-go decision-making.
Concept and delivery planning of a data-driven analytics initiative focused on profitability, payback period and investment risk analysis for mining hardware. Focus areas included scope definition, roadmap planning, calculation logic, market validation and management-ready decision support.
Context
The idea originated from operational experience in the mining infrastructure space. The goal was to create an analytics product capable of combining technical, financial and operational factors into a structured investment and operations model. The main challenge was translating volatile variables such as network hash rate, asset prices, hardware costs, operating expenses and expected runtime into a reliable decision framework.
I led the project and product discovery process: problem definition, scope, roadmap, data modelling, calculation logic, architecture considerations, market validation and go/no-go decision-making. The focus was not only technical feasibility, but also commercial and operational viability.
- ✓Translated an operational problem into scope, roadmap and prioritised delivery workstreams
- ✓Designed profitability, amortisation and investment-risk calculation logic
- ✓Modelled volatile factors such as hash rate, asset prices, hardware costs, operational expenses and runtime assumptions
- ✓Defined data structures, scenario parameters and decision-making logic
- ✓Evaluated platform architecture, API/backend approach, deployment structure and monitoring requirements
- ✓Prepared and assessed market validation including controlled go/no-go decision-making
Analytics Discovery & Product Delivery
- •Translated complex profitability and amortisation logic into a structured analytical model
- •Mapped volatile technical and financial variables into scenario-based decision logic
- •Created decision-making support for operations, investment planning and fleet management
- •Evaluated API/backend approach, data model and long-term extensibility
- •Integrated deployment, monitoring and operational considerations into the product concept early on
- •Converted operational experience from a client platform environment into a standalone platform concept
- •Validated the business case across technical, operational and commercial assumptions
- •Assessed market demand and target-customer interest
- •Controlled and limited further investment after insufficient market validation
- ✓Designed an analytics and profitability model for mining hardware investments
- ✓Created transparency around profitability, payback periods and investment risk
- ✓Translated operational platform experience into a standalone product concept
- ✓Validated commercial viability and limited further investment in a controlled manner
Tech Stack
I translate complex operational and technical challenges into structured product and decision models. My approach combines platform understanding, business-case modelling and delivery thinking — including controlled go/no-go decisions instead of uncontrolled execution.
Interested in structured product and delivery discovery?
I’m happy to discuss how I turn complex platform or analytics initiatives into reliable decision frameworks and executable delivery plans.