全年生产数据与图表看板

A submitted no deliverable. B provides both requested worksheets, all 432 operator-week rows with consistent machine/shift assignments, correct Week 1 inputs, automatic average and total formulas, visible top/bottom conditional formatting, start/end-week validation lists, KPI formulas and four chart objects. However, the four sections labeled “PivotTable” are SUMIFS/RANK/LARGE/INDEX formula summaries rather than actual PivotTables, so B does not fully satisfy the explicit PivotTable requirement.

A provides both named worksheets, 432 operator-week rows with fixed assignments, matching Week 1 inputs, automatic averages/totals, visible top/bottom highlighting, week-range dropdowns, KPI formulas and four chart objects. However, its sections labeled “PivotTable” are populated by SUMIFS and ranking formulas rather than actual PivotTables, leaving an explicit requirement unmet. B submitted no deliverable.

Submission A has no deliverable file, so it meets none of the requirements. Submission B provides a workbook with both required sheets. **'Operator Output Data' sheet:** - It has 432 rows covering Weeks 1–48 × Operators 1–9. - Machine and shift assignments stay the same every week and match the input (Op1 M1 Day, Op2 M2 Night, etc.). - Week 1 Mon–Fri values copy the input exactly. - Average and Total use formulas (`=IF(COUNT(E2:I2)=0,"",AVERAGE(...))` and the matching SUM). The render shows correct results, e.g. Op1 944.0/4,720 and Op4 760.0/3,800. - Visible green/red conditional formatting marks the top and bottom performers in both columns. **'Dashboard' sheet:** - Start Week and End Week dropdowns (D4/H4) use list validation on Week 1–Week 48. - Four tables are driven by those selections: operator performance with rank, machine totals, Day/Night shift averages, and a YTD leaderboard built with LARGE/INDEX. - It contains 4 charts. - A Week 1 KPI table uses formulas that I verified by hand: - Total units: 38,880 - Top operator: Operator 1 at 4,720 - Top machine: Machine 3 at 13,300 - Average per operator: 4,320 - Day share: 58.4%; Night share: 41.6% **Weaknesses:** - The 'PivotTables' are SUMIFS formula tables labelled as PivotTables, not native Excel PivotTables. - The leaderboard's INDEX/MATCH could repeat names when totals tie. Despite these, B is a substantive and largely complete answer, while A delivers nothing.

Submission B submitted no file, so it delivers none of the requested workbook. Submission A delivers a two-sheet workbook with correctly named 'Operator Output Data' and 'Dashboard' tabs. The data sheet has 432 rows (48 weeks × 9 operators) with every required column. Week 1 matches the input file exactly (e.g., Op1 950/930/940/945/955 = 4,720; Op4 = 3,800; Op9 = 4,550). Machine and shift assignments stay the same for all 48 weeks. Average and Total Output use auto-formulas, and conditional formatting visibly marks top performers green and bottom performers red. The Dashboard has list data validation on D4/H4 (Start/End Week, drawn from the Week 1–48 list) and four SUMIFS-driven summary tables that respond to the selected week range: operator performance, machine total, shift averages and a YTD leaderboard using LARGE/INDEX. It also contains 4 charts whose titles match the required operator, machine, shift and YTD views. The KPI block holds formulas for total units, top operator and machine with their outputs, average per operator, and day/night %. These logically resolve to 38,880 total; Operator 1 at 4,720; Machine 3 at 13,300; 4,320 average; and about 58.4%/41.6%. The main weakness is that the 'PivotTables' are formula tables labelled as PivotTables, not native PivotTable objects. Chart types and quadrant layout could not be visually confirmed. Even so, A is a substantive, functional deliverable, while B has nothing.