Data-Driven Manufacturing: Customer Insights and Production Performance
This manufacturing business dashboard tracks two critical sides of the operation side-by-side: how customers behave once they've bought from you, and how reliably the factory floor delivers what those customers ordered. Two views are open in this free sample — Customer Insights & Performance and Production & Supply Performance. The Overview, Sales & Profitability, and Inventory sections are part of the full, purchased report.
1. Customer Insights & Performance
The customer view tracks a base of 4,000 active customers, generating a $7.83K Cr total sales figure and $15.63M in average revenue. Both average revenue and average revenue growth registered a steep -90.20% month-over-month swing, while repeat purchase rate fell 88.34% MoM to just 0.98% — a combination that points to a sharp falloff in reorder activity rather than a one-off reporting blip.
Health Status & Concentration Risk
The health-status breakdown is stark: the dashboard classifies the customer base as almost entirely "At Risk," with 493 customers flagged individually as at-risk and churn currently holding at 0.00%. The Top Customers Driving Revenue (80/20) panel confirms a concentration problem — average revenue per customer of $15.6M is being carried by a narrow slice of accounts, all under the single "High Value" segment, rather than being spread across a broader mix.
Aging and Credit Exposure
The Customer Health & Risk table lists high-value accounts (e.g. Global 0051 Corp, Global 4420 Corp, Global 0619 Corp) with days-since-last-purchase stretching from the 890s into the 930s — well past a healthy repurchase window — and a combined current revenue-at-risk figure north of ₹7.45B across the table. Average credit days sit at 40.12, up slightly on last month, and the alerts panel separately flags 3,246 customers with credit days above 60, a cash-flow exposure worth monitoring alongside the return-to-purchase gap.
Customer Alerts & Insights:
• 5,000 customers are flagged at risk and need immediate follow-up.
• Revenue is declining compared to the last period.
• Revenue is well distributed across the customer base overall.
• 3,246 customers carry credit days above 60 — a cash-flow risk to monitor.
2. Production & Supply Performance
On the factory side, the plant network produced 543K total units, up 2.78% MoM, running at a strong 95.62% capacity utilization. Supply fulfillment sits at 91.11% (+0.55% MoM) and the rejection rate has improved to 1.59% (-0.04% MoM) — both healthy directional signals for a plant network of this size.
The On-Time Delivery Gap
The standout number here is on-time delivery at just 47.77%, meaning more than half of orders are shipping late despite production keeping pace with planned output. The dashboard's own banner alert ties this directly to a specific cause: "Production shortfall driven by maintenance downtime in West region." Average downtime sits at 6.11%, a small MoM increase, which is consistent with delivery slipping even while raw output holds steady.
Plant-Level Breakdown and Downtime Root Causes
The Production Efficiency Overview table shows the Ahmedabad, Chennai, and Pune plants each running at 0.96 utilization, with individual downtime hours in the 166–170 range and a combined network total of 542,522 units produced against 504.03 downtime hours. The Downtime & Loss Analysis chart ranks the causes: Maintenance is the single largest downtime driver, followed by Labor Issues, Power Failures, and Material Shortages — a ranking that lines up with the West-region maintenance issue called out in the alert banner.
What's in the Full Report
The Overview, Sales & Profitability, and Inventory sections — along with the downloadable PBIX file — are part of the complete, purchased dashboard. Use the button below to get in touch about full report access or a custom build.
Conclusion: Two Halves of One Operation
Read together, these two views tell a connected story: a shrinking, increasingly at-risk customer base on one side, and a production network that's hitting its output targets but failing to deliver on time because of maintenance downtime on the other. For a manufacturing operator, the fix for one likely depends on the fix for the other — customers don't reorder from a supplier who ships late, and late shipping traces straight back to the maintenance and labor issues flagged in the downtime chart.