The contribution of people is difficult to isolate from other factors such as the economic situation, market forces and customer or social trends.
The value of people is often expressed in qualitative rather than quantitative terms that make it difficult to represent in traditional accountancy models.
HR data has traditionally been collected for administrative rather than evaluation purposes.
HR practitioners do not always have the skills or resources to interpret or explain data to evaluate the contribution of people to business performance.
Find out more in our HR analytics factsheet or read about collecting and analysing data in the CIPD/Oracle report Talent analytics and big data – the challenge for HR.

Different levels of data collection
There are three clear levels of data collection and analysis for human capital data:

Operational data analysis – simple monitoring data with no analysis, for example, reporting absence and retention data.

Basic insights – basic data is analysed and correlations are explored between types of data to draw simple human capital insights.

Insights driving performance – human capital data is triangulated with other business data to identify performance drivers; and may be used to illustrate how organisations can leverage human capital to drive performance more effectively.

The different levels of data collection that might take place, with their likely outcomes, are:

Action
Operational data analysis:
Collect basic input measures such as absence data, turnover data.
Identify useful data already available.
Use this data to communicate essential information to managers.
Basic insight:
Design data collection for specific human capital needs.
Look for correlations between data – for example, whether high levels of job satisfaction occur when certain HR practices are in place, such as performance management, career management or flexible working.
Insights driving performance:
Identify key performance indicators relating to the business strategy, and design data collection processes to measure against them.
Communicate data in ways that are meaningful to differing audiences.
Outcome
Operational data analysis:

Basic information for managers on headcount and make-up of the workforce.
Basic insight:

Information to help design the HR model most likely to contribute to performance.
Communication to managers not just on how to implement processes, but with accompanying information on why they are important and what they can achieve.
Insights driving performance:

Identification of the drivers of business performance.
Information that will enable better-informed decision-making internally and externally.
To find out more on measuring human capital, and some of the important HR theories related to human capital, read our report Human capital analytics and reporting: exploring theory and evidence.

Different types of information will be of value to different stakeholder groups:

Leaders are interested in understanding how effective employees are at creating value for the organisation, and whether people enable the organisation to be sustainable over the long term.
Shareholders seek information on the employee attributes or behaviours that are likely to influence short- or long-term financial performance.
Investors are interested in knowing how organisations value and grow their pools of talent, and whether long-term decision making takes place with people in mind.
Customers wish to know if they will get good service and after-sales support.
Employees want to know their jobs are secure and how they can develop themselves and their skills.
Managers require information on which actions they can take to improve the performance of their business units.
Regulators and policy makers are interested in understand whether organisations are operating within the correct ethical, moral, social and environmental governance boundaries.
External reporting
Reporting is typically done in one of four ways:

unstructured voluntary
systemised voluntary
voluntary for reward
compulsory.
Organisations are becoming more able to capture and report on data, and thus expectations from external stakeholders are that reporting will become standardised and may even become compulsory. Some examples of different types of reporting are:

Method: Unstructured voluntary
Explanation: Isolated pilot studies are initiated by individual enterprises or consultancy companies/ researchers develop and promote approaches and methods.
Example: social reports, knowledge accounts, human resource audit, holistic balance sheet, intellectual capital statements.

Method: Systemised voluntary
Explanation: Develop a consistent framework which can be operational across sectors and countries and promote this at large scale through the inherent rewards and image gains.
Example: ISO 9000 standards, benchmark programmes.

Method: Voluntary for reward
Explanation: Develop a consistent framework supported by rewarding mechanisms once it is introduced and approved at enterprise level.
Example: Investors in People (UK), European Label for Innovative Projects in Language Learning (EU).

Method: Compulsory
Explanation: Identify disclosure on human capital as a public concern and prepare (inter-)national regulations and standards.
Example: Green accounts (Denmark)

Narrative reporting
The Department for Business Innovation and Skills (BIS) has issued regulations for the future of narrative reporting which are a clear call for improved reporting on aspects of human capital: