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Research Management - Shopping List - Dashboard View

Download and customize a free Research Management Shopping List Dashboard View Excel template. Perfect for business, legal, and personal use. Editable and ready to boost your productivity.






Item Name Quantity Unit Price ($) Total Price ($) Purchased
Total Amount: $0.00

Research Management Shopping List Dashboard View Excel Template

This comprehensive Excel template is specifically designed for Research Management teams and principal investigators who require an organized, real-time tracking system for procurement of research materials, equipment, and consumables — presented in a visually intuitive Dashboard View. Unlike generic shopping lists, this template integrates research-specific metadata such as grant codes, project phases, approval workflows, and vendor performance metrics. The Shopping List functionality is enhanced with dynamic dashboards that turn raw procurement data into actionable intelligence for budget control, inventory forecasting, and compliance reporting.

Sheet Names

  • DashBoard — Central analytics hub with charts, KPIs, and summary widgets.
  • Shopping_List — Master transactional table of all procurement items.
  • Vendors — Reference list of approved suppliers with performance ratings.
  • Grants_Projects — Lookup table linking funding sources to research projects.
  • Status_Log — Audit trail of order changes, approvals, and delivery status.
  • Inventory_Snapshot — Monthly snapshot of stock levels for trend analysis (optional).

Table Structures & Columns

The Shopping_List table is the core data engine with the following columns:

Date the item was added to the list.
<
Detailed specifications, catalog number, CAS number for chemicals, etc.
<
Amount required for experiments or lab use.
List price per unit before discount.
<<
= Quantity * Unit_Price.
<
Based on experiment deadlines or protocol requirements.
<
Status of the procurement process.
Name of budget approver or PI.
Date approval was granted.
Planned delivery date from vendor.
Actual receipt date for inventory reconciliation.
<
E.g., “Requires dry ice shipping,” “Replace with equivalent SKU.”
= Total_Cost * (Project_Budget_Percent / 100) from Grants_Projects.
Column Name Data Type Description
IDNumber (Auto-increment)Unique identifier for each shopping item.
Date_RequestedDate
Project_CodeText (Dropdown)Linked to Grants_Projects sheet (e.g., NIH-2024-BIO-017).
Item_NameTextName of the research consumable or equipment.
DescriptionText (Multi-line)
QuantityNumber (Decimal)
Unit_PriceCurrency
Vendor_NameText (Dropdown)Linked to Vendors sheet for compliance tracking.
Total_CostCurrency (Calculated)
Priority_LevelText (Dropdown: High/Medium/Low)
StatusText (Dropdown: Pending / Approved / Ordered / Delivered / Cancelled)
Approved_ByText
Date_ApprovedDate
Date_Expected_DeliveryDate
Actual_Delivery_DateDate (Optional)
NotesText
Grant_AllocationCurrency (Calculated)

Formulas Required

  • Total_Cost = Quantity * Unit_Price — Auto-calculated in column G.
  • Grant_Allocation = Total_Cost * VLOOKUP(Project_Code, Grants_Projects!$A:$D, 4, FALSE) — Dynamically allocates cost to the correct grant.
  • =COUNTIFS(Status,"Pending") — Used in Dashboard for “Pending Items” KPI.
  • =SUMIF(Status,"Delivered",Total_Cost) — Total spent on delivered items.
  • =AVERAGEIFS(Unit_Price, Project_Code, "NIH-2024-BIO-017") — Average cost per item for a specific project.
  • =IF(TODAY()>Date_Expected_Delivery, "Overdue", IF(AND(TODAY()<=Date_Expected_Delivery, TODAY()>=TODAY()-3), "Due Soon", "On Track")) — Dynamic delivery status indicator.

Conditional Formatting

  • Pending Orders > 14 days old: Red background in Date_Requested column.
  • High Priority & Not Approved: Orange border on entire row.
  • Total_Cost > 80% of Monthly Grant Cap: Yellow fill in Total_Cost column.
  • Status = "Delivered": Green checkmark icon using Symbol font or conditional icons.
  • Vendor Performance Rating = Low: Red text in Vendor_Name column (linked to Vendors sheet).

Instructions for the User

Step 1: Populate the Vendors and Grants_Projects sheets first with approved vendors and active project/grant codes.

Step 2: In the Shopping_List sheet, use dropdowns (Data Validation) for Project_Code, Vendor_Name, Priority_Level, and Status to ensure consistency.

Step 3: Enter new items daily as needs arise. Avoid manual edits to calculated columns.

Step 4: Update Status after each lifecycle step (Approved → Ordered → Delivered). The Dashboard auto-updates.

Step 5: Weekly: Review the “Expenditure vs. Budget” chart and adjust spending if nearing cap.

DO NOT delete or move columns. Use only the provided data validation lists to maintain dashboard integrity.

Example Rows

89.75
ThermoFisher
5 kits
1,850.00
Integrated DNA Technologies
Eppendorf Microcentrifuge 5430R
IDDate_RequestedProject_CodeItem_NameQuantityUnit_Price ($)Vendor_NameStatusTotal_Cost ($)
10242024-05-15NIAID-2024-MICRO-99Taq Polymerase (5U/μL)10 vialsDelivered897.50
10252024-06-10NHGM-2024-CRISPR-13Cas9 Ribonucleoprotein ComplexPending9,250.00
10262024-06-18NIGMS-2024-DYNAMICS-771 unit4,950.00
VWR
Approved4,950.00

Recommended Charts & Dashboard Elements

The DashBoard View includes:

  • Pie Chart: “Total Expenditure by Grant” — Shows budget allocation consumption.
  • Column Chart: “Monthly Spending Trend” — Compares actual vs. budgeted spending.
  • Gauge Meter: “Current Grant Utilization %” — Real-time percentage of spent funds per active project.
  • Table Summary Widget: Top 5 most expensive items ordered in last 30 days with vendor names.
  • Status Heatmap: Color-coded grid showing count of Pending/Ordered/Delivered items by week.
  • Vendor Performance Scorecard: Avg. delivery time, on-time rate, and cost efficiency ranked from vendors list.

This template transforms traditional shopping lists into strategic research management tools. By embedding grant compliance, real-time budget tracking, and automated reporting into a single dashboard-driven system, it ensures that lab procurement supports scientific goals — not disrupts them. Regular use minimizes delays in critical experiments and maximizes funding efficiency.

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