UC- Digital Service Estimator

Description

The Digital Service Estimator is a low-code application designed to streamline the effort and cost estimation process for digital services. It supports both predictive ROM (Rough Order of Magnitude) estimation and detailed estimations across various service areas such as Program Management, Solution Design, Infrastructure Setup, Data Migration, Testing, Go-live Support, and Managed Services.

The tool integrates AI-driven keyword extraction to generate instant ROM estimates based on opportunity briefs or inputs. It also employs a rule-based engine for generating structured, detailed cost and effort breakdowns, leveraging historical data, reusable estimation assets, resource profiles, and rate cards. Estimation outputs can be visualized and shared via integrated Power BI dashboards.

Actors

• Estimator / Pre-sales Consultant – primary user responsible for preparing estimates.

• Delivery Manager / SME – provides reusable assets, templates, and validates detailed estimates.

• Sales / Account Manager – reviews high-level ROM and estimation results for client proposal.

• AI Model (via AI Builder) – extracts key entities and parameters from briefs or RFPs.

• Dataverse – acts as the centralized data store for assets, profiles, and estimation logic.

Preconditions

• The Estimator app is deployed and accessible via Power Apps.

• Required reusable estimation assets, resource profiles, and rate cards are populated in Dataverse.

• AI Builder is trained to extract relevant keywords (e.g., service types, volumes, durations) from textual input.

• Rule-based estimation logic is configured and mapped to service categories.

Flow of Events

1. User logs in to the Power Apps-based Estimator interface.

2. Inputs a brief (e.g., opportunity description or client RFP text).

3. AI Builder analyzes the text and extracts service keywords, expected timelines, volumes, etc.

4. ROM Estimator module generates a high-level estimation based on AI-extracted inputs.

5. User optionally switches to Detailed Estimation mode.

6. User selects applicable service areas (e.g., Infra, Migration, Testing).

1. The rule engine fetches reusable estimation templates and populates effort/cost based on input parameters and resource rates.

2. User reviews/modifies outputs, adds assumptions, and submits for review if required.

3. Finalized estimation is visualized in Power BI and can be exported to PDF/Excel.

4. Results are stored in Dataverse for tracking and reuse in future estimations.

Postconditions

• A completed, AI-assisted estimation is generated and stored.

• Estimation artifacts (ROM and detailed) are available for download and internal review.

• Data is logged for future analytics and continuous improvement of estimation logic.

Benefits

• Reduces estimation cycle time from days to hours using AI-driven ROM estimation.

• Improves estimation accuracy with rule-based detailed costing and reusable assets.

• Standardizes estimation process across teams and engagements.

• Ensures historical estimations and assumptions are centrally stored and auditable.

• Enhances visibility for sales, delivery, and finance teams through Power BI dashboards.

Tools & Technology Used

• Power Apps – to build the Estimator user interface.

• AI Builder (Power Platform) – for keyword/entity extraction and predictive estimation.

• Microsoft Dataverse – as a centralized data repository for assets, profiles, templates, and rate cards.

• Power BI – for visualization and reporting of estimation results.

• Power Automate (optional) – to automate notifications, approvals, or versioning of estimation outputs.