人员查询Person queries

人员查询分析组织中每个单独的视图的数据点的数据。The person query analyzes data from the point of view of each individual in the organization.

这为分析数据带来了很大的灵活性。This creates a lot of flexibility in analyzing data. 例如,您可以学习:For example, you can learn:

  • 不同组织属性的时间使用情况有何不同?How time use varies by different organizational attributes?

  • 组织中的特定子组如何花费时间?How specific subgroups in the organization spend their time?

  • 协作的一个方面如何影响其他时间使用习惯?How one aspect of collaboration influences other time-use habits?

    人员查询问题

人员查询指标在四个广泛的类别中。The person query metrics fall within four broad categories. 您可以将每个类别中的标准指标添加到查询中。You can add standard metrics from each category to your query. 根据分析的不同,您可以按天、周或月汇总人员的协作指标。Depending on the analysis, you can summarize a person’s collaboration metrics by day, week, or month.

四种类型的人员指标

每个查询为每个用户返回一个在每个期间的一行。Each query returns one row per person, per period.

查询结果行

该文件将包含您指定的任何标准或自定义的指标。The file will include any standard or customized metrics you specify. 如果员工在指定时间段内发送至少一封电子邮件或一封即时消息,则输出文件中的 IsActive 列为 True。The IsActive column in the output file is True if the employee sent at least one email or one instant message during the specified time period for the query.

查询结果指标

你的结果将包含你的工作区分析管理员已上载的任何员工组织数据属性。And your results will include any employee organizational data attributes that your Workplace Analytics admin has uploaded.

查询结果属性

您可以使用组织属性进一步汇总人员结果,并创建功能强大的分析,以比较和对比组织中不同组的协作。You can use organizational attributes to further summarize the person results and create powerful analyses that compare and contrast the collaboration of different groups in the organization.

查询结果摘要

创建人员查询Create a person query

设置人员查询很简单。It's simple to set up a person query.

  • 选择是否希望按天、周或月汇总每个人的指标以及要分析的时段。Select whether you want each person's metrics summarized by day, week, or month, and the period you’d like to analyze.
  • 选择要从计算中排除会议的自定义规则集,否则将使用默认值。Select a custom rule set to exclude meetings from the calculations, otherwise it'll use the default.

创建人员查询

选择指标Select metrics

你可以选择要了解的有关员工的指标。You can select metrics for what you want to know about your employees. 这些选项因指标类型而异,但可以包含与其工作活动相关的条件,例如会议和电子邮件:The options vary based on the type of metric, but can include criteria related to their work activities, such as for meetings and email:

  • 会议发生时When the meeting occurred
  • 邀请了多少人How many people were invited
  • 主题行关键字Subject line keywords
  • 与会者/组织者属性Attendee/organizer attributes
  • 发送电子邮件的时间When email was sent
  • 电子邮件中包含多少人How many people were included in the email
  • 主题行关键字Subject line keywords
  • 收件人/发件人属性Recipient/sender attributes

例如,您可以添加一个指标,以获取电子邮件中至少包含一个来自销售组织的人员的每个人的电子邮件计数。For example, you can add a metric to get an email count for each person where at least one person from the Sales organization is included in email.

人员查询基本指标

您可以向基本指标中添加筛选器,并使用筛选器编辑指标名称。You can add a filter to a base metric and edit the metric name with the filter. 例如,下面显示 发送给 Sales 的电子邮件,它将成为输出文件中的列标题。For example, the following shows Emails sent to Sales, which will be the column header in the output file.

人员查询自定义指标

若要获取有关添加指标筛选器的更多详细信息,请参阅 自定义指标To get more details on adding metric filters, see Customize a metric.

标准化工作时间Standardize working hours

在人员查询的结果中,工作时间、小时数和聚焦时间指标的报告将受到个人在 Outlook 中设置的工作时间的影响。In the results for person queries, the reporting for the working hours, after hours, and focus hours metrics is influenced by the working hours that individuals have set in Outlook. 如果个人设置了超长的长时间工作时间,这会导致计算 erors。This can cause calculation erors if individuals have set unusually long working hours. 若要避免此问题,分析师可以对查询用来计算这些指标的工作时间进行标准化。To avoid this problem, analysts can standardize the working hours that a query uses to calculate these metrics.

分析师可以标准化设置Analysts can standardize settings

在 person 查询的 " 依赖项 " 部分中,分析师可以设置查询在计算时使用的工作日和工作时间。In the Dependencies section of a person query, analysts can set the working days and hours that that query will use in its calculations.

工作日和工作时间

通过使用一组标准值(用于工作时间和日期),分析程序可分析指标指标计算,目的是实现苹果到苹果的比较。This lets analysts benchmark metrics calculations by using one standard set of values for working hours and days, with the goal of achieving apples-to-apples comparisons. 分析师所做的设置仅用于查询及其计算中,不会覆盖任何其他查询或任何用户在 Outlook 或其他地方的设置中使用的任何数据。The settings that analysts make are used only within the query and its calculations and do not override any data that is used in any other queries or in any user's settings in Outlook or elsewhere.

查询结果中的列Columns in query results

人员的输出查询将自动包含有关这些标准化设置的信息:The output of person queries automatically contains information that pertains to these standardized settings:

  • 它包含显示在查询计算中使用的工作开始时间、工作结束时间和工作日的列。It contains columns that show the working start time, working end time, and working days that were used in the query's calculations.
  • 它指示查询计算中使用的工作时间的指标。It indicates which metrics used working hours in the query's calculations.
  • 它指示是否在查询的计算中使用了标准化设置。It indicates whether the standardized settings were used in the query's calculations.

选择筛选器Select filters

您可以选择要在查询结果中包含的衡量员工。You can select which measured employees you want to include in your query results. 对于 " 员工",选择是否希望活动、非活动或所有员工包含在查询中。For Employees, select if you want active, inactive, or all employees included in the query. "活动员工" 是指在选定时间段内发送至少一封电子邮件或即时消息的人, (为查询) 设置的聚合期间。Active employees are those who sent at least one email or instant message during the selected time period (the aggregated period set for the query).

然后,您可以选择其他筛选器,以根据个人的组织属性(如函数类型)从输出文件中排除某些行。You can then select other filters to exclude certain rows from the output file based on a person's organizational attributes, such as function type. 例如,以下筛选器将仅列出 "操作" 和 "销售" 组中的人员。For example, the following filter will only list people from the Operations and Sales groups.

人员查询筛选器

添加筛选器时,将看到筛选器组中包含的人员数以及它所基于的已衡量员工的总数。When you add a filter, you'll see the number of people included in the filter group and the total number of measured employees it's based on. 这将帮助您决定是否在运行查询之前为查询设置了正确的筛选器。This will help you decide if you've set the correct filters for the query before running it.

筛选器预览

选择要包含的组织数据Select what organizational data to include

在工作区分析中运行人员查询时,输出 ( .csv) 文件可能比所需的大,但所需的组织数据列比所需的多。When you run a person query in Workplace Analytics, the output (.csv) file can be larger than necessary, with more organizational data columns than you need. 使用 " 组织数据 " 部分选择要包含在输出文件中的数据列,其中:Use the Organizational data section to select which data columns to include in the output file, which:

  • 使用较小的文件中的列改进数据分析。Improves data analysis with fewer columns in a smaller file.
  • 通过从文件中排除列来进一步保护私有数据。Further protects private data by excluding columns from the file.
  • 使您能够选择 " 全部清除 " 以清除所选列,并使用 " 全选 " 来包含所有列。Enables you to select Clear all to clear the selected columns and use Select all to include all columns.

"组织数据" 部分

长会议的示例人员查询Example person query for long meetings

您可以创建人员查询,以调查长会议是否为运营的会议总时间量的重要因素。You can create a person query to investigate if long meetings are a significant factor in the total number of meeting hours for Operations. 以下自定义查询使用指标和筛选器来自定义数据。The following custom query uses metrics and filters to customize the data.

查询条件Query criteria

  • 时间范围:显示每周聚合的数据Time frame: Shows the data aggregated weekly
  • 谁:筛选操作Who: Filters on Operations
  • 哪些数据:指标What data: Metrics
    • 会议时间是所有会议时间的总和Meeting hours are the total of all meeting hours
    • 长会议时间(包含最近2个或更多小时的长会议)Long meeting hours that include long meetings that last 2 or more hours
    • "会议数" 是会议总数Meetings is the total number of meetings
    • 发送的电子邮件数是发送的电子邮件总数Emails sent is the total number of emails sent

为长会议创建自定义人员查询To create a custom person query for long meetings

  1. 在 "工作区分析" 中,选择 "分析 > 查询 > 人员"。In Workplace Analytics, select Analyze > Queries > Person.

  2. 选择此处并将 " 输入查询名称 " 更改为 " 长操作会议 ",并输入说明。Select and change Enter query name here to Long Operations meetings and enter a description.

  3. 对于 " 分组依据",选择 " 星期"。For Group by, select Week.

  4. 选择日期范围。Select a date range. 查询将仅分析在此日期范围内发生的会议。The query will analyze only the meetings that occurred during this date range.

  5. 在 " 会议排除 " 菜单中,选择适用的排除规则集。In the Meeting exclusions menu, select the applicable exclusion rule set.

  6. 在 " 指标 " 部分中,选择 " 添加指标",然后选择 " 会议时间 " 以添加会议总小时数的指标。In the Metrics section, select Add metric, and then select Meeting hours to add a metric for total meeting hours.

  7. 选择 " 编辑 " 图标,并将指标的名称更改为 " 会议总小时数"。Select the Edit icon and change the metric's name to Total meeting hours.

  8. 若要添加自定义指标用于长会议时间,请选择 " 添加指标",然后选择 " 会议时间"。To add a custom metric for long meeting hours, select Add metric, and then select Meeting hours. 选择 " 编辑 " 图标,并将指标的名称更改为 " 长会议时间"。Choose the Edit icon and change the metric's name to Long meeting hours.

    1. 若要自定义长会议时间指标,请选择 " 编辑 " 图标。To customize the Long meeting hours metric, select the Edit icon.
    2. 选择 " 添加筛选器"。Choose Add filter.
    3. 在 " 长时间会议时间 " 部分中,选择 " 会议",然后选择 " DurationHours > 大于或等于 > 2"。In the Long meeting hours where section, select Meeting, and then select Duration­Hours > greater than or equal to > 2.
    4. 选择 " 确认"。Select Confirm.
  9. 若要为会议总数添加指标,请选择 " 添加指标",然后选择 " 会议"。To add a metric for total number of meetings, select Add metric, and then select Meetings. 选择 " 编辑 " 图标,并将 "名称" 更改为 " 会议总数"。Choose the Edit icon and change the name to Total number of meetings.

  10. 若要为已发送的电子邮件添加指标,请选择 " 添加指标",然后选择 " 发送的电子邮件"。To add a metric for sent email, select Add metric, and then select Emails sent. 选择 " 编辑 " 图标,并将指标名称更改为 发送的电子邮件数Choose the Edit icon and change the metric name to Number of emails sent.

    Note

    • 如果某个指标的人员/日期组合没有数据,则查询结果将不会有对应于该人员/日期组合的行。If no data exists for a person/date combination for a metric, the query results will not have a row for that person/date combination.
    • 按周或月聚合数据时,您可能希望包含具有零值的指标。When aggregating data by the week or the month, you might want to include a metric that has a zero value.
    • 若要确保每个人的数据行和指标的日期组合,请添加作为一个指标 发送的电子邮件To make sure you have a line of data for every person and date combination for the metrics, add Emails sent as one of your metrics.
    • 导出结果后,将所有 null 值替换为零,以确保求平均值和其他统计信息的计算包括所有人员和日期组合。After you export the results, replace all null values with zeros to ensure that calculations for averages and other statistics include all person and date combinations.
  11. 在 " 筛选器 " 部分的 " 员工" 中,选择是希望 仅活动仅非活动还是 所有员工 包含在查询中。In the Filters section, for Employees, select if you want Active only, Inactive only, or All employees included in the query. "活动员工" 是指在此查询) 设置 (日期范围的总时间段内发送至少一封电子邮件或即时消息的人员。Active employees are those who sent at least one email or instant message during the aggregated time period (date range) set for this query.

  12. 选择 "添加筛选器",然后在菜单中选择 " FunctionType > 等于 > 操作"。Select Add filter, and then in the menus, select FunctionType > Equals > Operations.

  13. 在 " 组织数据 " 部分中,您可以选择要在输出 ( .csv) 文件中包含的数据列。In the Organizational data section, you can select what data columns to include in the output (.csv) file. 选择 " 全部清除 " 以清除所有选定列,然后选择要从列表中包含的列。Select Clear all to clear all selected columns, and then select which columns you want to include from the list. 使用 " 全选 " 可包含默认的所有列。Use Select all to include all columns, which is the default.

  14. 选择右上角的 " 运行 " 以运行查询。Select Run at the top right to run the query.

  15. 在 "查询 > 结果" 页上,查询状态显示为 "已提交"。On the Queries > Results page, the query status shows as Submitted. 在查询状态更改为 " 成功" 后,您可以查看、共享、下载 (.csv 文件格式) 、删除或 复制 OData 链接 以在可视化工具中使用,例如 Power BI 或 Excel。After the query status changes to Succeeded, you can view it, share it, download it (in .csv file format), delete it, or Copy an OData link to use in a visualization tool, such as Power BI or Excel.

人员查询结果 下面列出了在前面步骤中创建的自定义查询的查询结果中包含的列,以及您可能会看到的数据行类型的示例:Person query results The following are the columns included in the query results for the custom query created in the previous steps and an example of the type of data rows you might see:

  • 人员 ID-在指标中表示的人员的已取消标识的 ID 号。Person ID - De-identified ID number for the person represented in the metric.
  • Date-聚合 (的开始日期,即,如果一周是6/3 到6/10,则为6/3。Date - The start date of the aggregation (i.e. if the week is 6/3 to 6/10, then it is 6/3. 如果是一个月,则它是您的数据包含) 的月份的开始。If it is a month, then it is the start of the month your data encompasses).
  • Person 属性-数据集中的人员属性(由组织数据提供)。Person Attributes - Each of the person attributes in the data set supplied by the organizational data.
  • 指标-查询中包括的任何其他指标。Metrics - Any other metrics that you included in the query.
人员 IDPerson ID DateDate **人员属性 1 (部门) **Person attribute 1 (department) **人员属性 2 (角色) **Person attribute 2 (role) 电子邮件小时数Email hours 会议小时数Meeting hours
P1P1 04/25/201904/25/2019 HRHR 管理员Administrator 5 5 11 11
P2 04/24/201904/24/2019 营销Marketing Executive 4 4 14 14

指标说明Metric descriptions

查看、下载和导出查询结果View, download, and export query results

使用 CRM 数据进行查询Queries with CRM data