Use Cases we solve.
10 real problems companies face when data starts piling up — and how we turn scattered spreadsheets, ad-hoc extracts and rogue dashboards into clean, reliable, available data and confident decisions.
No real data platform. Excels, manual extractions and a few Power BI reports built by different people keep piling up. Numbers don't match between teams, and decisions depend on whoever happens to hold the latest file.
We run a data assessment: we inventory every source, map how data flows, and diagram the current situation in plain, non-technical language so leadership can actually decide. Then we deliver a prioritized action plan — quick wins now plus a roadmap toward clean, reliable, available data.
- Consolidate the 3 most critical reports into one trusted dashboard.
- Define metric owners and a shared glossary so everyone counts the same way.
- Retire duplicate and contradictory files.
Central data store with automated refresh; one trusted version of key reports.
Governed self-service BI and a culture of decisions made on clean data.
Sales live separately in the POS, the online store and the marketplace. Inventory is reconciled by hand, so stockouts and overstock are discovered far too late.
We integrate every channel into one model, standardize SKUs into a clean product master, and build a near-real-time sales & stock dashboard with alerts on the products that matter most.
- Daily consolidated sales report across all channels.
- Low-stock alerts on best-sellers.
- Clean, de-duplicated product master.
Automated channel ingestion feeding one sales & stock model.
Demand-aware replenishment and margin analytics by product and store.
Production data is trapped inside machines and paper or Excel logs. Downtime causes are anecdotal, and OEE is unknown or roughly estimated.
We capture and clean production data, define OEE (availability, performance, quality) consistently, and visualize where losses happen by line and shift.
- Automated daily output and downtime report.
- Pareto of the top stoppage causes.
- Reliable OEE baseline per line.
Trustworthy OEE per line, refreshed automatically.
Predictive maintenance signals and scrap-reduction analytics.
Deliveries, routes and costs are tracked in personal spreadsheets. There are no reliable on-time or cost-per-delivery KPIs to manage the operation.
We model the operational data into one dataset and build a KPI cockpit — on-time %, cost per delivery, route efficiency — with drill-down to the problem cases.
- Automated on-time and cost dashboard.
- Exception list of late or expensive deliveries.
- Single, agreed operational dataset.
One operational data model powering daily KPIs.
Route optimization and SLA forecasting.
Patient, appointment and billing data sit in separate systems. Monthly reports are built by hand, while data quality and privacy remain ongoing concerns.
We consolidate sources with privacy by design, clean and standardize records, and automate the operational and financial reporting that today eats hours every month.
- Automated occupancy and no-show report.
- De-duplicated patient master record.
- Access-controlled reporting layer.
Governed reporting layer with role-based access.
Capacity planning and clinical outcome analytics.
Ad spend is spread across channels and ROAS is argued from each platform's own numbers. There is no unified, comparable attribution.
We unify spend and revenue into one marketing mart, build a comparable channel attribution and ROAS model, and deliver a marketing performance dashboard the whole team trusts.
- Blended ROAS and CAC dashboard.
- Weekly channel performance view.
- Unified spend and revenue dataset.
Single marketing data mart across channels.
Attribution modeling and budget-allocation scenarios.
The monthly close and board reporting run on fragile Excel files — slow, error-prone, and dependent on one person who holds all the knowledge.
We model finance data in a warehouse, automate the core metrics (MRR, churn, margin), and deliver board reports that update themselves and reconcile to the source.
- Automated MRR and churn dashboard.
- Reconciled revenue report.
- Documented, repeatable metric definitions.
One finance data model feeding self-updating reports.
Scenario planning and forecasting.
Headcount, turnover and recruiting are tracked in disconnected spreadsheets, leaving leadership without a clear, current picture of the workforce.
We consolidate HR data with privacy in mind, define the core people KPIs, and build a leadership people dashboard that answers the recurring questions instantly.
- Headcount and turnover dashboard.
- Time-to-hire report.
- Clean, consolidated people data model.
Reliable people data model with core KPIs.
Attrition-risk analytics and workforce planning.
Each venue runs its own POS and performance is compared by emailing spreadsheets around. There is no timely, fair cross-location view.
We centralize POS data, standardize the menu and product catalog, and build per-location and group dashboards so every site is measured the same way.
- Daily group sales with per-venue ranking.
- Labor-versus-sales view by site.
- Standardized menu and product catalog.
Automated multi-venue ingestion into one model.
Menu engineering and demand forecasting per site.
Time tracking, costs and invoicing are scattered. Nobody knows which projects or clients are actually profitable until it is too late to act.
We join time, cost and revenue data, define project and client profitability consistently, and build a live margin dashboard that flags trouble early.
- Project margin and utilization dashboard.
- Automatic flag of loss-making projects.
- Unified delivery and finance dataset.
One delivery-and-finance dataset powering margin views.
Pricing insights and capacity forecasting.