It's time to reinvent management. You can help.


bruce-lewin's picture

Linking HR Metrics to Financial Outcomes

By Bruce Lewin on June 8, 2013

HR has often struggled to demonstrate it's value, both in absolute terms and when compared to other functions. There is no shortage of research, commentary and writing on the subject, this piece from HR Magazine in 2007 sums things up well:

'A growing literature bears testament to the fact that Human Resource Management (HRM) has failed to deliver on many of its early promises and been unsuccessful in its attempts to achieve status as either a strategic partner or an employee champion.

One possible resolution to this challenge has focused on finance and the use of metrics, analytics and in broad terms, 'speaking the language of finance'. The then DTI review into Accounting for People in 2003 is worth noting (apparently this was revived in 2010) , as are the calls for HR to 'model itself on finance'. What's clear however is the tension that lies at the heart of this.

On the one hand, finance is rightly seen as the most powerful support function and the function holding the purse strings, so building a relationship here makes good sense. There is talk of the CIPD collaborating with CIMA and this extract from Chris Roebuck serves as something of a rallying call:

How many HR functions have presented a clear case to their FD on the financial value they are likely to be adding? How many have identified specific initiatives that have delivered specific value to improve service to end users or customers?

On the other hand, there's currently no obvious, well accepted and widely adopted method for a HR function to report it's financial contribution to a business. Jeffrey Pfeffer wrote this cautionary tale for those who want to dance in time to the Finance Director's tune:

‘Equipping human resource managers with additional analytic tools and language is all to the good, as far as it goes. In the end, however, all one accomplishes is being a more skilled player at someone else’s game. By so doing, one buys into the ultimate sensibility and reasonableness of the basic measures and ideas in the first place; this is often a mistake. Being skilled at the wrong game is not a very promising strategy for either the company or the human resources function. It is unlikely that human resources will ever be able to win playing the number games against those with much more experience who also get to set the rules. Even if they do win, the victory may have extracted a large cost in terms of losing the distinct perspective and competence of human resources in the process of becoming like other staff functions… If all human resources becomes is finance with a different set of measures and topic domains, then its future indeed is likely to be grim.’

While the ability of HR to show a return on investment is going to meet in principle, a receptive audience and help the function boost it's credibility, it would be wise to approach such an initiative in a manner that leverages the unique contributions HR can make. The following hack outlines one approach to achieve this, while still retaining the 'distinct perspective and competence' spoken of by Pfeffer above.

The Hack

Empirical research into 4G validates the fact that the 14 Social Relationships can be ordered from most to least productive. By combining this rank order of Social Relationships and linking the corresponding ratios to people's salary, it is possible to calculate the financial cost of relationships and to return quantifiable measures of team performance, effectiveness and efficiency.

These calculations then offer HR a formula to link the results of various business processes (e.g. team creation, restructuring, training and development outcomes, recruitment, business development, customer service etc.) to KPI's and other quantifiable measures of performance (e.g. sales, staff engagement, group or individual performance data, the time and costs of specific objectives being achieved, task completion etc.).

The Hack in Practice

In diagram 1 and the table below, a random team of 7 is analysed using Relationship Friction1, 2. Everyone in the team is paid £50,000, making the total salary for the team £350,000. Given the 7 Social Profiles and the breakdown of the 21 Social Relationships, the cost of Relationship Friction for this team is £60,195 or 17.2% of the total team salary. In addition, the Relationship Friction Index is 864, allowing Relationship Friction data to be compared across different teams without revealing sensitive salary data.

Name Social Profile Salary
Alberto Boeder 3Ni £50,000
Fraser Corking 4Ne £50,000
Gayle Rhodes 2Se £50,000
Lashanda Kumar 1Si £50,000
Leanne Woods 2Ni £50,000
Louise Calvert 4Te £50,000
Tejash Thiara 3Fi £50,000
  Total Salaries £350,000
  Relationship Friction £60,195
  Relationship Friction % 17.2%
  Relationship Friction Index 864
Hack HR 5 - Quantifying Behaviour and Linking it to the Bottom Line - Diagram 19
Diagram 1 - Click to Enlarge

This example of Relationship Friction shows how simple it is to present the results and how straightforward it is to understand. The second example allows a comparison with the first and allows a 'before' and 'after' scenario to be shown. In this instance, the comparison might be between two different customer service teams, but could equally compare two teams of accountants or two sales teams.

The second table and diagram 2 shows the change in Relationship Friction if the team of 7 is optimised around a particular Social Group, in this case, Social Group 3. By creating a team in which everyone is a member of the same Social Group, not only does everyone experience optimal Social Relationships, but the Relationship Friction figures improve dramatically. In this case, Relationship Friction falls to £18,357 or 5.2% of the team’s combined salary. This is a difference in Relationship Friction of £41,838, or a fall of 12%. Likewise, the Relationship Friction index falls to 264.

Name Social Profile Salary
Alberto Boeder 3Ni £50,000
Claudia Robinson 3Fi £50,000
Hugh Morton 3Se £50,000
Ivan Thomas 3Se £50,000
Jim Rushton 3Ni £50,000
Mark Correra 3Te £50,000
Tejash Thiara 3Fi £50,000
  Total Salaries £350,000
  Relationship Friction £60,195
  Relationship Friction % 17.2%
  Relationship Friction Index 864
Hack HR 5 - Quantifying Behaviour and Linking it to the Bottom Line - Diagram 20
Diagram 2 – Click to Enlarge

While the examples above help illustrate the changes in the 'before' and 'after' scenarios, not every use of Relationship Friction requires the use of a team creation process.


The ability to link typically intangible factors such as relationships and group values to salary data and to show this information as a financial cost or in a quantifiable manner opens up a number of interesting new avenues and benefits:

  • HR can easily show the financial impact and ROI from a number of processes and interventions.
    • Recruitment, team creation, organisational re-design and changes to business process would all benefit from the ability to show an ROI in any improvements that are made. Other examples include sales, customer services, process throughput/process efficiency and various project based tasks.
  • In addition to being able to show a return on investment from the activities above, Relationship Friction ensures that HR retains it's ability to make a unique contribution to the organisation whilst avoiding the trap of 'playing at someone else's game', as Pfeffer wrote.
  • Relationship Friction contributes new and objective data to the performance management process. Whilst some elements of performance management can be overly subjective, the use of Relationship Friction adds a layer of insight and objectivity that may well lead to better decisions and outcomes.
  • Relationship Friction figures are calculated for both teams and individual's in the same way, creating an additional level of granularity and understanding to the performance management process.


1. To create the random team, a spreadsheet was used to simulate different combinations of Social Profiles. By way of context, having run the random team generator over 50 times, the average Relationship Friction % is calculated at 16.3% with a low of 12.3% and a high of 19.2%.

2. Work to date suggests that overall, teams typically have an average or normal distribution of Social Profiles and Social Relationships within them. There are some functional and industry biases (e.g. HR typically has more feeling profiles i.e. those with F in their acronym) but for the sake of this example, the random team presented is a good representation of what might be found if a team was picked by chance from any organisation, regardless of seniority or function.

Please read the other hacks I've submitted:

  1. Predicting Relationships and Group Values - Creating A New Mental Model and Set of Conceptual Skills
  2. Relational Recruitment and Optimising Team Creation for Group Cohesion
  3. Better Engagement through Enhanced Decision Making, Personalised Coaching and Aligning the Management of Processes and People
  4. Predictive Change Management and Creating an “Army” of Change Agents
  5. 6 Processes for HR Transformation
HR process being hacked:HR Metrics and Information Systems

You need to register in order to submit a comment.