The different Orgvue dataset types

This article explains the different dataset types, and how these are used in Orgvue to enable Data-Driven Organization Design.

People Datasets and Positions Datasets

People datasets and Positions datasets operate in the same way: 

• Every slide type can be used with either dataset type. 
• Template analysis packs can be used with either dataset type.
• You can model the future organization with either dataset type.

Data about positions can be included in people datasets and vice versa.  For example:

• A ‘Position Title’ property can be included in a people dataset to identify each employee’s current position; and
• An ‘Incumbent’ property can be included in a positions dataset to identify the current holder of each position.

Why does Orgvue recommend Linking People and Positions Datasets?

When an employee leaves the organization, they no longer exist in a people dataset.  If the leaver is a people manager the hierarchy breaks.   However, with people-to-positions linked datasets, when an employee leaves the organization, the position remains in the hierarchy, automatically categorized as ‘vacant’.  You get immediate control over the constantly changing organization. 

Related and additional benefits are summarized below:

A further, incremental benefit is the ability to accommodate, double-hatting (one person performing more than one position) and position sharing in visualizations of the organization.

Additional insight which can be unlocked through people-to positions linking is explained in The value in linking People and Positions Datasets:

• Understand the underlying reasons for differences between the actual and forecast size and cost of the workforce.
• Gain transparency on long-term open positions to reveal hidden costs which could be repurposed.
• Access richer insight to inform talent management.
• Get control over complex, high risk talent selection processes.

Links Datasets

Links datasets connect two different datasets.  They are created in Orgvue by specifying the datasets to be linked. 

When a people dataset is being linked to a positions dataset, the Links dataset contains:

• The unique ID for each employee in the people dataset;
• The unique ID for each position in the positions dataset;
• The ‘Allocation’ used to link individual employees (in the people dataset) to positions (in the positions dataset).  The FTE value is typically used. 

The illustration below shows three datasets in the Workspace Homepage:

1. A Links dataset ‘People to Position Links’ which has been created to connect (2) ‘Position Structure’ and (3) ‘April People Data’. 
   1. An extract of the Links dataset is shown to illustrate this contains only the data required to link the two datasets.
   2. The datasets being linked are shown on the card
2. ‘Positions Structure’, and
3. ‘April People Data’
   3. The Links icon on the card indicates a links dataset has been created using this dataset. 
   4. When this icon is selected, the links datasets for this dataset are shown.  Selecting this sub-card opens a pack with the links activated.

The illustration below shows a slide in a pack using the “Position Structure" dataset with the links activated (2d, above).  When there is a link between the position and an employee, the employee's name (contained in the people dataset) is shown.  When an employee leaves and is therefore no longer included in the People dataset, the link breaks and the position is categorized as ‘vacant’.


Links datasets provide the mechanism for managing and visualizing complex many-to-many relationships.

In addition to linking People and Positions, other Orgvue datasets can be linked.  The illustration below shows how Links connect the components of the The Organisation System, and the 'Allocations' typically used. 



Links are always two-way.  For example, when People are linked to Activities through an Individual Activity Analysis survey you can visualize:

• Every activity conducted by an employee; and 
• Every employee conducting an activity.

Links can be edited in slides.  For example, when an employee advances in a talent selection process, this decision is recorded by editing the ‘Allocation’ value linking the employee to the position.

Activities Datasets

An Activities dataset is a taxonomy of the work activities required to deliver the strategy.

Value Chains (e.g. “HR Value Chain”) are broken down into Processes (e.g., “Talent Acquisition Process”), which are in turn broken down into individual Activities (e.g., “Source Candidates”). 

Activities datasets are used to:

• Define Role accountabilities.  Roles are linked to Activities through target accountabilities with categories from the chosen accountability framework (‘Responsible’, ‘Approve’ etc.) providing the ‘Allocation’.
• Understand how work gets done.  Individual Activity Analysis (IAA) surveys link every employee to the work activities they conduct, with survey responses – the time spent on each activity and the accountability exercised – providing the ‘Allocation’.  
• Model the impact of process optimization levers.  With IAA data revealing the time and cost of each work activity, the impact of process optimization levers (automate, outsource etc.) in the future size and cost of the workforce can be projected. 

Competencies Datasets

A Competencies dataset is a taxonomy of the skills, knowledge and behaviours needed to deliver the strategy. 

Competencies are typically structured by type, for example, Behavioural, Cognitive, and Functional/ Technical.

Competencies datasets are used to:

• Define Role targets.  The skills, knowledge and behaviours required to perform in a Role.  Target proficiency levels provide the ‘Allocation’.
• Analyse the competencies possessed across the workforces.  Through Orgvue Surveys, or by ingesting existing data, the competencies possessed, and the levels of proficiency across the workforce is visualized and analysed.  Actual proficiency ratings provide the ‘Allocation’.
• Model the future workforce skills requirements.   As work activities change due to the impact of AI and other process optimization programmes, an integrated data framework enables the impact on the future demand for specific competencies to be projected.

Roles Datasets

In Data-Driven Organization Design, Roles (Jobs) and Positions are distinct: 

• Roles are defined with target data.  At a minimum, 'Role Title', 'Purpose', 'Role Family', and 'Target Level/Grade' are recorded.  
  An example Role is 'Sales Executive'.   

• Positions are specified in the structure for defined Roles, Typical properties are 'Position Title', planned ‘Position Grade’ and ‘Position Cost’, geographic 'location', the 'function' the position is in and its 'business unit'.
  Example Positions for the Sales Executive Role might include “Sales Executive – North”, “Sales Executive – South”, and “Sales Executive – Corporate Customers”.
  The number of Positions for each Role is projected through rightsizing and workforce planning taking account of business planning assumptions.  

Lookup Datasets

Lookup Datasets provide a central source of data which is referenced to maintain consistency. 

Property values can be specified with reference to a Lookup dataset.  Common examples include:

• Exchange rate lookups to generate ‘standardized cost’ values (see details in the Orgvue User Guide).
• Rate card lookups for calculating position costs.

Lookups can also be used to standardise colors.  For example, specifying the color to be applied to each property value.

Dependent Lookups are used when there is a logical relationship across properties and values, for example, geographic properties spanning ‘Region’, ‘Country’ and ‘Location’ levels.  With a Dependent Lookup, data is edited by selecting values from a dropdown menu; the options presented are based on the value of a related property.  (e.g. 'Canada' and 'USA' being presented for the 'Country' property when 'North America' has been selected as the 'Region' value).  

Related Articles

• The Data Maturity Journey
• The Organisation System
• Key Measures – Workforce size and cost
• The value in linking People and Positions Datasets