EnergyPro.
Unlocking South Africa's energy with software.
- Role
- Product Designer
- Platform
- Web · SaaS
- Domain
- Energy wheeling
- Scope
- Full platform + design system
About
A SaaS platform that turns months of specialist energy analysis into proposals generated in minutes.
EnergyPro simplifies and accelerates energy wheeling in South Africa. Traditionally, a single wheeling proposal takes months of specialist quantitative analysis. EnergyPro automates the whole workflow — from tariff modelling to deal structuring — and delivers accurate proposals in minutes.
A tariff engine covering Eskom and municipal tariffs, customer and point-of-delivery onboarding, consumption profiles, generation-asset configuration for solar and wind, dynamic deal structuring, escalations, and team permissions throughout.
Months of specialist analysis, compressed into a same-day proposal.
Outcomes · Post-launch
Measured against the legacy manual workflow.
98%
Proposal time reduced
From weeks to under an hour — rapid quoting and deal velocity.
99.9%
Calculation accuracy
Tariffs, escalations, yields — a major cut in financial risk.
30–50
Deals / analyst / month
Up from 4–6 — a step-change in throughput.
~100h
Saved per proposal
Same-day
Turnaround
Centralised
Tariff data
Auditable
Workflow
Secondary metrics — time, consistency, and governance gains against the legacy spreadsheet process.
Phase one · The problem
Weeks of work, per proposal.
The friction
- Overlapping tariff structures
- Inconsistent consumption data
- Manual yields & escalations
- No governance or audit trail
Energy wheeling in South Africa is slow, complex, and heavily dependent on manual spreadsheets and specialist analysts. A single proposal means navigating multiple tariff structures, validating inconsistent consumption data, modelling generator yields, applying escalations, and comparing deal options — often over weeks.
Frequent tariff updates, fragmented workflows, and a lack of governance drive up errors, slow the sales cycle, and make the whole process hard to scale across a team.
Process
Competitor reviews, interviews, and behavioural analysis — insight drove the personas, which steered the design.
- 01
Discovery
- 02
Research
- 03
Strategy
- 04
Ideate
- 05
Prototype
- 06
Validate
- 07
Delivery
Phase two · The people
Three roles, one workflow.
Three roles shaped the platform — the analyst who builds the model, the BD manager who sells it, and the ops lead who has to trust it. Every flow had to serve all three.
Sarah
Energy analyst
Builds the models. Wants a tool that removes manual calculation and modelling errors so she can focus on strategy.
What she needs
Automated tariffs, consumption data, and generator modelling — accurate proposals, fast, under tight deadlines.
Michael
Business development
Sells the deals. Wants to model pricing scenarios instantly during client engagements and respond before competitors do.
What he needs
Configure tariffs, yields, and deal options quickly — communicate value clearly and close faster.
Daniel
Operations & compliance
Owns the oversight. Wants accurate tariff data, consistent outputs, and clear visibility of team activity.
What he needs
Confidence in escalation accuracy, tariff logic, and team permissions — an audit-ready environment.
Phase three · How I solved it
Four problems, four systems.
- 01
Problem
Manual, spreadsheet-driven modelling
Analysts spent 40–100 hours per proposal navigating overlapping spreadsheets, applying tariffs, yields, and escalations by hand. Errors compounded with every cell.
Solution
Automated calculation engine
A single engine running tariffs, yields, escalations, and deal structures in minutes — analysts shifted from data entry to high-value strategy.
- 02
Problem
Fragmented, outdated tariff data
Eskom and municipal tariffs sat in scattered spreadsheets that went stale between updates. Every proposal risked being modelled on outdated assumptions.
Solution
Centralised tariff engine
A searchable, structured tariff library — kept current and applied consistently across every proposal.
- 03
Problem
Inconsistent inputs, weak governance
Customer details, consumption profiles, and generator setups were captured differently by every analyst — no audit trail, no clear permissions.
Solution
Standardised inputs with governance
Standardised customer, consumption, and generator inputs, with role-based permissions, system logs, and a governance layer admins configure per team.
- 04
Problem
Slow scenario comparison
Comparing deal structures meant rebuilding spreadsheets — analysts couldn't show clients side-by-side options in real time, and deals slipped.
Solution
Guided proposal wizard
A five-step wizard with configurable deal options and a real-time overview showing client cost, savings, and wheeler profit side by side.
Phase four · Key decisions
Three decisions that shaped it.
A guided wizard, not a spreadsheet replacement
Reframed the whole proposal workflow as five steps — Create, Add Customer, Add Generators, Add Points of Delivery, Review. That forced the right inputs at the right time, killed the empty-canvas problem, and made the platform usable by BD managers, not just analysts.
The tariff engine as a first-class object
Tariffs were the single biggest source of error in the legacy workflow. Making the tariff engine a top-level, searchable, structured section — bound to every proposal automatically — eliminated an entire category of compliance risk.
Show outcomes, not just inputs
The proposal overview surfaces client cost, savings, and wheeler profit in one view, with an interactive graph for consumption and generation — so users validate outcomes immediately, instead of digging through spreadsheet tabs.
Phase five · The platform
One platform, every workflow.
Dashboard
Total generation, proposal-linked capacity, and energy sold at a glance, with quick access to the proposal wizard.
Generation Sites
Configure solar, wind, and other assets with yield, generation splits, tariffs, and escalations.
Tariff Engine
Centralised Eskom and municipal tariffs — searchable and structured.
Customers & Points of Delivery
Organised customer records with assigned tariffs and supply locations.
Global Escalations
Apply consistent escalation rates across an entire portfolio.
System Logs
A transparent audit trail across the platform for compliance and traceability.
Phase six · Design system
A system to scale on.
Foundations
- Typography
- Palette
- Components
- Templates
I built EnergyPro's design system from atomic principles — atoms through pages — to drive consistency and scale. It gave the team a flexible foundation that accelerated iteration and kept the UI coherent across the proposal wizard, tariff engine, generator configuration, and customer management flows.
- Typography — Nunito Sans, Bold through Light, documented across the system.
- Palette — Ethereal Blue #EAF0FE, Beacon Blue #23209F, Black #212121, White #FFFFFF.
- Components — buttons, form fields, cards, and tariff rows built for reuse.
- Templates — dashboard, proposal wizard, and tariff-engine list view.
Phase seven · Selected screens
Selected screens.
The core flows at a glance. Detailed UI breakdowns live on Behance.
Onboarding — invitation to active workspace in minutes, so new users are productive from the first session.
Reflections
The deal-options model carried more cognitive load than it needed to. Comparing short / medium / long term works, but the side-by-side table breaks down past three options or custom variants — given the brief again, I'd design it as a flexible compare-and-stack pattern from the start, and push harder on the IA between Customers, Points of Delivery, and Generators.
EnergyPro also pre-dated the current generation of AI tools. Designing it today, AI-assisted research synthesis would have shortened the domain-discovery phase considerably, and prototyping the wizard against simulated analyst behaviour would have caught at least one IA decision I'd later want to revisit. Same product; a faster, sharper path to it.
The highest-leverage move wasn't a feature — it was reframing the whole proposal as five guided steps, so anyone could build one, not just a trained analyst.
— What I learned
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