全年生产数据与图表看板

A is the more reliable tracker: it preserves the supplied Week 1 data, leaves later daily outputs blank, and links selected-week and YTD summaries to the start/end validation lists. B populates Weeks 2–48 with unsupported production data, producing a 1,898,790-unit YTD total when the supplied data supports only 38,880 units. This contaminates its YTD leaderboard and chart source. B’s validation selectors also drive a separate snapshot rather than its pivot reports. A remains incomplete because its blocks labelled “PivotTable” are SUMIFS-based formula summaries, not the requested genuine PivotTables.

B is the more accurate, usable tracker. It preserves the supplied Week 1 outputs, maintains machine/shift assignments through Week 48, and leaves future output inputs blank with blank-aware average and total formulas. Its KPI formulas correctly produce 38,880 units, Operator 1 at 4,720 units, Machine 3 at 13,300 units, and 4,320 units per operator. The rendered Week 1 results also highlight high and low performers. A instead populates Weeks 2–48 with unsupported production figures, contaminating its YTD reporting with a 1,898,790-unit total. B still falls short: its sections labeled 'PivotTable' are SUMIFS/INDEX/LARGE formula summaries rather than native PivotTable results.

Both workbooks have the two required sheets. Both carry the Week 1 source data exactly (for example, Operator 1 reads 950/930/940/945/955). Both keep each operator on the same machine and shift for all 48 weeks and calculate Average and Total Output with formulas. Both apply conditional formatting: A highlights the top and bottom Week 1 rows green and red, while B uses a colour scale plus red bottom-performer rules. Both include a complete Week 1 KPI block with correct-looking logic: 38,880 total; Operator 1 at 4,720; Machine 3 at 13,300; 4,320 per operator; about 58.4% day and 41.6% night. Both also have Start and End week data-validation dropdowns and four charts. The decisive difference is the explicitly required PivotTables. A's 'PivotTable 1–4' sections are SUMIFS, INDEX and LARGE formula tables relabelled as PivotTables, so they are not genuine PivotTables. A does link its dropdowns cohesively to those tables and its charts. B's Dashboard shows true PivotTable output: 'Week #' page filters, 'Sum of Total Output' and 'Average of Total Output' captions, Grand Totals, and sorted operator rows for (a) operators, (b) machines, (c) shift averages and (d) a YTD leaderboard, plus a separate formula leaderboard. B's dropdowns drive a Week Range Snapshot rather than the pivots themselves, which is a weaker link. B also stores cached calculated values, whereas A's formula cells have none. B's weeks 2–48 are invented sample data and are not clearly labelled as such. As a result its YTD figures (1,898,790 units) are not real. A's blank weeks 2–48 form an honest template. Even so, A misses a core named deliverable, so B better satisfies the task overall.

Submission A better meets the task, mainly because it has PivotTables and B does not. **Submission A** - **Data sheet:** It has all 432 operator-week rows, and each operator keeps the same machine and shift throughout. - **Week 1 data:** Week 1 matches the input file exactly. - **Calculations and formatting:** Average and Total are formulas (ROUND/AVERAGE and SUM). The rendered pages show conditional formatting: a colour scale plus red highlighting for bottom performers. - **PivotTables:** The Dashboard shows four PivotTable-style blocks. They use 'Sum of Total Output' / 'Average of Total Output' headers, 'Grand Total' rows and 'Week #' page filters, and hold static cached values. - **PivotTable values:** I checked the Week 1 figures by hand and they are correct. Operators total 4720 down to 3800, with a grand total of 38,880. Machines are 12,935 / 12,645 / 13,300. Shift averages are 4,543 (Day) and 4,041.2 (Night). - **YTD leaderboard:** A YTD pivot and a ranked leaderboard are both present. - **Week selection:** Start and End week dropdowns (data validation lists, B5 and D5) drive a 'Week Range Snapshot' block. - **KPI table:** All Week 1 KPIs are present and correct: 38,880 total; Operator 1 at 4,720; Machine 3 at 13,300; 4,320 per operator; 58.4% Day and 41.6% Night. - **Charts:** There are four charts. - **Weaknesses:** - It fabricates output for Weeks 2–48 without labelling it as sample data, so the YTD chart is not strictly based on Week 1. - Its AVERAGE formula would return #DIV/0! if those rows were cleared. **Submission B** - **Data sheet:** The table structure, Week 1 values, conditional formatting (top 3 green, bottom 3 red) and blank-safe formulas are correct. Leaving Weeks 2–48 empty fits a tracker. - **No real PivotTables:** The four 'PivotTable' blocks are SUMIFS/INDEX/LARGE formula tables relabelled as PivotTables. This misses an explicitly named requirement. - **No cached values:** The workbook was saved without calculated results. In the text extraction, all KPI and pivot-block cells and the data-sheet Average/Total cells are blank. Only the recalculated render shows numbers. - **Other features:** It has data validation dropdowns, four charts and a complete KPI formula set. On balance, A delivers real PivotTables with verified-correct values, a more complete analysis, and cached results that display without recalculation.