Analytics Case Study

IT Inventory, Sales and Vendor Performance Analytics Platform

How we built a centralised Power BI analytics platform for a large scale IT hardware distribution company in Delhi — giving leadership unified visibility across 2000 plus product SKUs, identifying capital tied up in slow moving stock, and replacing manual Excel analysis with real time intelligence.

Power BI Inventory Analytics Vendor Performance IT Distribution
Industry IT Hardware Distribution and Retail
Location Delhi, India
Platform and Tools Microsoft Power BI, Advanced DAX, Multi Year Sales and Inventory Data Models
Portfolio Scale 2000+ Product SKUs Across Multiple Brands and Categories

Overview

A large scale IT hardware distribution company based in Delhi was managing a portfolio of over 2000 product SKUs across multiple brands and categories — all through manual, Excel based analysis. As the business had grown, the limitations of that approach had become increasingly costly. There was no reliable way to see in real time which products were driving revenue, which SKUs were tying up working capital without sufficient returns, or how demand was trending across categories and brands.

Inventory decisions were reactive. Procurement was based on experience and instinct rather than data. Vendor relationships lacked the performance visibility needed to negotiate effectively or identify which supplier partnerships were worth deepening. Leadership recognised that continuing to manage a portfolio of this scale through spreadsheets was becoming a competitive disadvantage — and that the business needed a proper analytics foundation to make faster, smarter decisions at every level of the operation.

The Challenge

Building analytics across a 2000 plus SKU inventory is a different kind of problem to a standard sales dashboard. The platform needed to handle multi year data across dozens of brands and categories, identify performance patterns across product lifecycles, classify stock intelligently by how it should be managed, and surface vendor level insights that could actually change procurement decisions — all in an interface that leadership and procurement teams could use independently without needing a data analyst to interpret every report.

The time intensive Excel workflows that had been in place were also creating bottlenecks — decisions were delayed because the analysis took too long to prepare, and by the time insights were ready the operational window to act on them had often already closed. The solution needed to eliminate that lag and replace it with dashboards that were always current and always accessible.

What We Built

We designed and implemented a comprehensive inventory, sales, and vendor analytics platform using Microsoft Power BI as the central intelligence layer — consolidating multi year sales, inventory, and supplier data into a single unified analytical model that gave leadership a complete picture of portfolio performance for the first time.

Advanced DAX calculations powered the analytical engine, enabling complex product classification logic, multi year trend analysis, and vendor performance comparisons at scale. Every dashboard was built for independent use by non technical stakeholders — procurement teams and leadership could explore the data, answer their own questions, and act on insights without waiting for a report to be prepared.

Product Performance Analysis

Advanced analysis identifying top performing, slow moving, and low impact SKUs across all categories and brands — giving the business a clear view of which products deserved investment, which needed attention, and which were quietly consuming capital without return.

Three Year Trend Analysis

Multi year sales trend analysis revealing seasonality patterns, demand cycles, and long term product trajectories — supporting accurate forecasting and demand planning rather than procurement decisions based on recent memory or historical habit.

Vendor and Brand Performance Analytics

Comparative vendor and brand level analytics based on sales velocity, consistency, and revenue contribution — giving procurement teams the performance data needed to negotiate from a position of knowledge and make strategic supplier management decisions.

Intelligent Stock Classification

Classification logic distinguishing products suitable for regular stocking, on demand ordering, or de prioritisation across the full 2000 plus SKU portfolio — replacing intuition based inventory decisions with a consistent, data backed framework for managing stock intelligently.

Real Time Leadership Dashboards

Scalable, interactive Power BI dashboards replacing time intensive Excel workflows — leadership and procurement teams with live access to portfolio performance, inventory status, and vendor analytics without waiting for a report to be manually compiled.

Demand Forecasting Support

Seasonality and demand cycle insights built into the analytical model — procurement teams could align purchasing decisions with actual sales velocity and demand trends rather than restocking on a fixed cycle that ignored how products were actually moving.

Impact Delivered

The analytics platform gave leadership unified visibility across the full product portfolio for the first time — 2000 plus SKUs, multiple brands, multi year sales data, and vendor performance all in a single environment that could be explored in real time rather than assembled manually for each review cycle. Decision making became faster and more confident at every level of the operation.

Identification of slow moving and low impact inventory gave the business a clear picture of where working capital was being consumed without sufficient returns — enabling targeted action on excess stock, reducing warehouse overhead, and improving cash flow discipline across the portfolio. Procurement decisions shifted from experience based restocking to purchasing aligned with actual demand trends and sales velocity data.

Vendor and brand performance analytics changed how supplier relationships were managed. Procurement teams could now see which vendors were delivering consistent high value returns and which were underperforming relative to expectations — supporting stronger negotiations and more strategic supplier partnership decisions. The manual reporting bottlenecks that had been slowing decision cycles were eliminated entirely, replaced by dashboards that were always current and always accessible.

Key Outcomes

2000+ SKUs in One View

Unified visibility across the full product portfolio — leadership could see performance across all brands, categories, and SKUs in a single real time environment rather than piecing together insights from disconnected spreadsheets.

Slow Moving Stock Identified

Clear identification of slow moving and low impact SKUs consuming working capital without sufficient returns — enabling targeted action to reduce excess inventory, lower warehouse overhead, and improve cash flow discipline.

Demand Aligned Procurement

Purchasing decisions aligned with actual sales velocity and three year demand trends — procurement shifted from intuition based restocking to a data backed approach that reduced both overstock and stockout risk across the portfolio.

Stronger Vendor Management

Vendor and brand level performance data based on sales velocity, consistency, and revenue contribution — procurement teams could negotiate from a position of knowledge and identify which supplier partnerships deserved deeper investment.

Manual Reporting Eliminated

Time intensive Excel workflows replaced by scalable real time dashboards — the bottlenecks that had been delaying decisions were removed, and leadership could access current portfolio insights at any time without waiting for analysis to be prepared.

Intelligent Stock Classification

Every SKU classified by how it should be managed — regular stocking, on demand ordering, or de prioritisation — giving the operation a consistent data backed framework for inventory decisions across the full product range.

By replacing manual Excel analysis with a centralised Power BI intelligence platform across inventory, sales, and vendor performance, the business transitioned from reactive stock management to a structured, data driven operating model — with the visibility and speed needed to make smarter decisions across a portfolio of more than 2000 products.

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