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HENGSHI SENSE connects data entry, data integration, modeling, and metric analysis, allowing budgets, targets, and stocktaking results entered by business users to participate in business analysis alongside actual operational data.
Regional managers submit monthly targets, finance teams maintain expense budgets, and stores record stocktaking discrepancies. These management inputs matter as much as orders, inventory, and collections, yet they often remain scattered across spreadsheets. Management teams need more than collected files: they need to analyze the inputs using consistent organizational identifiers, periods, and calculation rules.
1. Organize business data before designing the entry point
To calculate monthly sales target attainment, first agree on how actual sales are recognized, which period a target belongs to, organizational codes, and monetary units. Targets may be recorded by store and month, while orders may be at item-line level. Joining these grains row by row can count the same monthly target multiple times.
Hengshi data entry collects information through forms and writes it to configured database output tables. Data teams can connect those tables to analytical models, establish appropriate relationships with operational data, and use HQL and metric management to express calculations such as target attainment and budget utilization. Entry forms, models, and metrics have separate responsibilities; business definitions remain a shared responsibility of the team.
| Business object | Rules to agree on | Role in analysis |
|---|---|---|
| Organization and period | Use stable organizational codes and specify calendar months or fiscal periods | Align submitted and actual data to the same scope |
| Targets and budgets | Specify currency, units, budget version, and effective status | Avoid mixing versions or incompatible monetary units |
| Fact grain | Distinguish monthly targets from order details and aggregate at an appropriate grain | Prevent one-to-many joins from multiplying targets |
| Business metrics | Define numerator, denominator, null handling, and zero-target handling | Reuse calculation meaning across dashboards and subsequent analysis |
2. Reduce entry errors with form components and templates
Hengshi provides drag-and-drop form design. Administrators select text, numeric, date, single-choice, and other components according to business fields. Numeric fields can enforce integers and upper or lower limits; required fields collect essential information; single-choice fields standardize a finite set of categories. Organizational codes still need to be checked against master data. Component validation does not replace a complete data quality review.
Before collecting submissions, enable the form and configure its output path and table name. The output connection must support the relevant write operations, and the database account needs appropriate permissions. Internal budgets and performance targets can use identified submissions with a restricted set of submitters. Configure and verify submission scope separately from subsequent analytical permissions. Anonymous collection serves other information-gathering needs and is unsuitable for named accountability.
3. Bulk import: follow the template and distinguish inserts from updates
Bulk import reduces individual entry when business departments have already prepared consolidated data. Download the target form’s template first, preserve field names and header structure, avoid merged cells, and check codes, dates, amounts, and null values. For files with multiple worksheets, verify selectable sheets and import scope against the deployed version and specific entry point, then check the result to prevent omissions or unintended imports.
When modifying existing submissions, record identifiers matter more than filenames.
Hengshi form data uses the system-generated hs_row_id to identify records. For bulk modifications through form data management, the template must include each record’s hs_row_id and complete modification content. A matching identifier updates the corresponding record; an empty hs_row_id is treated as an insert. Reuploading a target file without record identifiers may therefore create new records. Business uniqueness, such as store plus month plus budget version, still needs a separate check.
| Operation | Checks before execution | Checks after execution |
|---|---|---|
| Initial import | Template fields, business keys, row count, and key amounts | Target record count and grouped totals |
| Modify submitted data | Export existing records and retain the correct hs_row_id | Confirm only intended records changed and review insert and update results |
| Consolidate multiple contributors | Organization list, duplicate business keys, and budget versions | Identify missing submissions, duplicates, and abnormal values |
| Correct exceptions | Check what was already written before choosing updates or supplemental imports | Avoid importing the entire file again as new records |
4. Review process information together with data versions
Form data includes system fields such as creation and update times and user information. Identified and anonymous modes record different identity information. Administrators can use these fields to review record origins and recent changes. If the enterprise needs before-and-after values for every modification, approval comments, or historical budget snapshots, design dedicated version tables or integrate an existing approval system to retain suitable financial review records.
For failed or incomplete imports, compare execution results with actual output and identify data already written before choosing a supplemental import, modification, or recovery. Whole-batch transactional rollback, financial approval, and historical version restoration must be verified against the target database and actual implementation; support for import alone does not establish these capabilities. Production dashboards should use only reconciled budget versions and show the relevant period and data status.
5. Example scenario: monthly target attainment across retail stores
The following is a hypothetical solution example. Regional managers at a retail chain submit monthly targets for each store, while the order system provides daily actual sales. Headquarters first establishes store-code mappings and budget-version rules, then collects targets through Hengshi forms. Administrators import regional consolidation files using the template and check store coverage and total targets.
The data team aggregates orders by store and month, compares them with targets at the same grain, and uses HQL and business metrics to maintain actual sales, targets, attainment, and variance. When a target is zero or has not been submitted, the dashboard shows an unset status according to business rules, avoiding the treatment of missing values as zero attainment.
Headquarters observes differences across regions and stores through management dashboards; regional users see their authorized scope. When targets need to change, administrators confirm the budget version and record identifiers before updating and reviewing the result. This supports a continuing analytical process in Hengshi: management inputs, actual operations, metric calculations, and business review.